This document presents a novel scheme for minimizing the number of iterative steps in the particle swarm optimization (PSO) algorithm to extend the lifetime of wireless sensor networks. It first discusses existing literature that uses PSO approaches to address issues like clustering, energy efficiency, and localization in wireless sensor networks. It then identifies problems with existing approaches, such as higher computational complexity due to many iterations of PSO. The proposed solution enhances the conventional PSO algorithm by introducing decision variables and optimizing parameters like inertia weight and learning coefficients to obtain the global best solution in fewer iterations. It aims to minimize the transmission energy of cluster heads using a radio energy model to improve network lifetime. The key contribution is a computationally efficient PSO algorithm that selects effective
The paper presents a technique called as Mobility-enabled Multi Level Optimization (MeMLO) that addressing the existing problem of clustering in wireless sensor net-work (WSN). The technique enables selection of aggregator node based on multiple optimi-zation attribute which gives better decision capability to the clustering mechanism by choosing the best aggregator node. The outcome of the study shows MeMLO is highly capable of minimizing the halt time of mobile node that significantly lowers the transmit power of aggregator node. The simulation outcome shows negligible computational com-plexity, faster response time, and highly energy efficient for large scale WSN for longer simulation rounds as compared to conventional LEACH algorithm.
Multi-Objective Soft Computing Techniques for Dynamic Deployment in WSNIRJET Journal
This document discusses using multi-objective soft computing techniques like genetic algorithms for dynamic deployment in wireless sensor networks (WSNs) to maximize coverage area while minimizing energy consumption. It proposes a framework called Coverage and Energy Balancing Sensor Problem (CEBSP) that uses a Multi-Objective Genetic Algorithm (MOGA) and Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol to optimize both coverage and energy consumption by deploying fewer sensor nodes. The document reviews related work applying genetic algorithms and clustering to improve WSN deployment, coverage, and energy efficiency.
Optimum Relay Node Selection in Clustered MANETIRJET Journal
This document summarizes a research paper that proposes an optimal method for selecting relay nodes in a clustered mobile ad hoc network (MANET) to improve energy efficiency. The key points are:
1) The paper focuses on selecting cluster heads based on the node with the maximum remaining energy and selecting gateway nodes based on the minimum distance to their respective cluster heads.
2) This approach aims to reduce energy consumption in the network by minimizing the distance that data must travel between nodes.
3) The performance of the proposed relay node selection method is evaluated based on energy consumption, packet delivery ratio, and throughput.
Load Balancing for Achieving the Network Lifetime in WSN-A SurveyAM Publications
a wireless sensor network is network form of sense compute, and communication elements which helps to
observe, events in a specified environment. Sensor nodes in wireless sensor network are depends on battery power they
have limited transmission range that’s why energy efficiency plays a vital role to minimize the overhead through which
the Network Lifetime can be achieved. The lifetime of network, depends on number of nodes, strength, range of area
and connectivity of nodes in the network. In this paper we are over viewing techniques which are used in wireless sensor
network for load balancing. Wireless sensor network having different nodes with different kind of energy which can be
improve the lifetime of the network and its dependability. This paper will provide the person who reads with the
groundwork for research in load balancing techniques for wireless sensor networks.
1) The document proposes implementing an efficient K-means clustering algorithm to enhance connectivity and lifetime in wireless sensor networks.
2) It compares the proposed K-means algorithm to an existing Jumper Firefly algorithm based on energy consumption, network lifetime, and end-to-end delay.
3) Simulation results show the proposed K-means algorithm improves performance by reducing energy consumption from 16 to 12 Joules, increasing network lifetime by 96% compared to 83% for the existing algorithm, and lowering end-to-end delay from 3.7 to 2.7 seconds.
Mobile Agents based Energy Efficient Routing for Wireless Sensor NetworksEswar Publications
Energy Efficiency and prolonged network lifetime are few of the major concern areas. Energy consumption rated of sensor nodes can be reduced in various ways. Data aggregation, result sharing and filtration of aggregated data among sensor nodes deployed in the unattended regions have been few of the most researched areas in the field of wireless sensor networks. While data aggregation is concerned with minimizing the information transfer from source to sink to reduce network traffic and removing congestion in network, result sharing focuses on sharing of information among agents pertinent to the tasks at hand and filtration of aggregated data so as to remove redundant information. There exist various algorithms for data aggregation and filtration using different mobile agents. In this proposed work same mobile agent is used to perform both tasks data aggregation and data filtration. This approach advocates the sharing of resources and reducing the energy consumption level of sensor nodes.
A New Method for Reducing Energy Consumption in Wireless Sensor Networks usin...Editor IJCATR
Nowadays, wireless sensor networks, clustering protocol based on the neighboring nodes into separate clusters and fault
tolerance for each cluster exists for sensors to send information to the base station, to gain the best performance in terms of increased
longevity and maintain tolerance than with other routing methods. However, most clustering protocols proposed so far, only
geographical proximity (neighboring) cluster formation is considered as a parameter. In this study, a new clustering protocol and fault
tolerance based on the fuzzy algorithms are able to clustering nodes in sensor networks based on fuzzy logic and fault tolerance. This
protocol uses clustering sensor nodes and fault tolerance exist in the network to reduce energy consumption, so that faulty sensors
from neighboring nodes are used to cover the errors, work based on the most criteria overlay neighbor sensors with defective sensors,
distance neighbor sensors from fault sensor and distance neighbor sensors from central station is done. Superior performance of the
protocol can be seen in terms of increasing the network lifetime and maintain the best network tolerance in comparison with previous
protocols such as LEACH in the simulation results.
This document discusses using a particle swarm algorithm to enhance dynamic load balancing in a cloud computing environment. It begins with introducing centralized and decentralized load balancing approaches. It then describes using a particle swarm optimization technique, which identifies the least loaded, available virtual machine to distribute workload to in order to minimize energy usage and processing time. The document reviews several related works applying genetic algorithms, particle swarms, ant colony optimization and other approaches to optimize load balancing. It suggests a particle swarm algorithm can distribute load more efficiently compared to centralized and simple decentralized methods.
The paper presents a technique called as Mobility-enabled Multi Level Optimization (MeMLO) that addressing the existing problem of clustering in wireless sensor net-work (WSN). The technique enables selection of aggregator node based on multiple optimi-zation attribute which gives better decision capability to the clustering mechanism by choosing the best aggregator node. The outcome of the study shows MeMLO is highly capable of minimizing the halt time of mobile node that significantly lowers the transmit power of aggregator node. The simulation outcome shows negligible computational com-plexity, faster response time, and highly energy efficient for large scale WSN for longer simulation rounds as compared to conventional LEACH algorithm.
Multi-Objective Soft Computing Techniques for Dynamic Deployment in WSNIRJET Journal
This document discusses using multi-objective soft computing techniques like genetic algorithms for dynamic deployment in wireless sensor networks (WSNs) to maximize coverage area while minimizing energy consumption. It proposes a framework called Coverage and Energy Balancing Sensor Problem (CEBSP) that uses a Multi-Objective Genetic Algorithm (MOGA) and Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol to optimize both coverage and energy consumption by deploying fewer sensor nodes. The document reviews related work applying genetic algorithms and clustering to improve WSN deployment, coverage, and energy efficiency.
Optimum Relay Node Selection in Clustered MANETIRJET Journal
This document summarizes a research paper that proposes an optimal method for selecting relay nodes in a clustered mobile ad hoc network (MANET) to improve energy efficiency. The key points are:
1) The paper focuses on selecting cluster heads based on the node with the maximum remaining energy and selecting gateway nodes based on the minimum distance to their respective cluster heads.
2) This approach aims to reduce energy consumption in the network by minimizing the distance that data must travel between nodes.
3) The performance of the proposed relay node selection method is evaluated based on energy consumption, packet delivery ratio, and throughput.
Load Balancing for Achieving the Network Lifetime in WSN-A SurveyAM Publications
a wireless sensor network is network form of sense compute, and communication elements which helps to
observe, events in a specified environment. Sensor nodes in wireless sensor network are depends on battery power they
have limited transmission range that’s why energy efficiency plays a vital role to minimize the overhead through which
the Network Lifetime can be achieved. The lifetime of network, depends on number of nodes, strength, range of area
and connectivity of nodes in the network. In this paper we are over viewing techniques which are used in wireless sensor
network for load balancing. Wireless sensor network having different nodes with different kind of energy which can be
improve the lifetime of the network and its dependability. This paper will provide the person who reads with the
groundwork for research in load balancing techniques for wireless sensor networks.
1) The document proposes implementing an efficient K-means clustering algorithm to enhance connectivity and lifetime in wireless sensor networks.
2) It compares the proposed K-means algorithm to an existing Jumper Firefly algorithm based on energy consumption, network lifetime, and end-to-end delay.
3) Simulation results show the proposed K-means algorithm improves performance by reducing energy consumption from 16 to 12 Joules, increasing network lifetime by 96% compared to 83% for the existing algorithm, and lowering end-to-end delay from 3.7 to 2.7 seconds.
Mobile Agents based Energy Efficient Routing for Wireless Sensor NetworksEswar Publications
Energy Efficiency and prolonged network lifetime are few of the major concern areas. Energy consumption rated of sensor nodes can be reduced in various ways. Data aggregation, result sharing and filtration of aggregated data among sensor nodes deployed in the unattended regions have been few of the most researched areas in the field of wireless sensor networks. While data aggregation is concerned with minimizing the information transfer from source to sink to reduce network traffic and removing congestion in network, result sharing focuses on sharing of information among agents pertinent to the tasks at hand and filtration of aggregated data so as to remove redundant information. There exist various algorithms for data aggregation and filtration using different mobile agents. In this proposed work same mobile agent is used to perform both tasks data aggregation and data filtration. This approach advocates the sharing of resources and reducing the energy consumption level of sensor nodes.
A New Method for Reducing Energy Consumption in Wireless Sensor Networks usin...Editor IJCATR
Nowadays, wireless sensor networks, clustering protocol based on the neighboring nodes into separate clusters and fault
tolerance for each cluster exists for sensors to send information to the base station, to gain the best performance in terms of increased
longevity and maintain tolerance than with other routing methods. However, most clustering protocols proposed so far, only
geographical proximity (neighboring) cluster formation is considered as a parameter. In this study, a new clustering protocol and fault
tolerance based on the fuzzy algorithms are able to clustering nodes in sensor networks based on fuzzy logic and fault tolerance. This
protocol uses clustering sensor nodes and fault tolerance exist in the network to reduce energy consumption, so that faulty sensors
from neighboring nodes are used to cover the errors, work based on the most criteria overlay neighbor sensors with defective sensors,
distance neighbor sensors from fault sensor and distance neighbor sensors from central station is done. Superior performance of the
protocol can be seen in terms of increasing the network lifetime and maintain the best network tolerance in comparison with previous
protocols such as LEACH in the simulation results.
This document discusses using a particle swarm algorithm to enhance dynamic load balancing in a cloud computing environment. It begins with introducing centralized and decentralized load balancing approaches. It then describes using a particle swarm optimization technique, which identifies the least loaded, available virtual machine to distribute workload to in order to minimize energy usage and processing time. The document reviews several related works applying genetic algorithms, particle swarms, ant colony optimization and other approaches to optimize load balancing. It suggests a particle swarm algorithm can distribute load more efficiently compared to centralized and simple decentralized methods.
Analysis of Genetic Algorithm for Effective power Delivery and with Best Upsurgeijeei-iaes
Wireless network is ready for hundreds or thousands of nodes, where each node is connected to one or sometimes more sensors. WSN sensor integrated circuits, embedded systems, networks, modems, wireless communication and dissemination of information. The sensor may be an obligation to technology and science. Recent developments underway to miniaturization and low power consumption. They act as a gateway, and prospective clients, I usually have the data on the server WSN. Other components separate routing network routers, called calculating and distributing routing tables. Discussed the routing of wireless energy balance. Optimization solutions, we have created a genetic algorithm. Before selecting an algorithm proposed for the construction of the center console. In this study, the algorithms proposed model simulated results based on "parameters depending dead nodes, the number of bits transmitted to a base station, where the number of units sent to the heads of fuel consumption compared to replay and show that the proposed algorithm has a network of a relative.
Reliable and Efficient Data Acquisition in Wireless Sensor NetworkIJMTST Journal
The sensors in the WSN sense the surrounding, collects the data and transfers the data to the sink node. It
has been observed that the sensor nodes are deactivated or damaged when exposed to certain radiations or
due to energy problems. This damage leads to the temporary isolation of the nodes from the network which
results in the formation of the holes. These holes are dynamic in nature and can grow and shrink depending
upon the factors causing the damage to the sensor nodes. So a solution has been presented in the base paper
where the dual mode i.e. Radio frequency and the Acoustic mode are considered so that the data can be
transferred easily. Based on this a survey has been done where several factors are studied so that the
performance of the system can be increased.
A Novel Weighted Clustering Based Approach for Improving the Wireless Sensor ...IJERA Editor
Great lifetime and reliability is the key aim of Wireless Sensor Network (WSN) design. As for prolonging
lifetime of this type of network, energy is the most important resource; all recent researches are focused on more
and more energy efficient techniques. Proposed work is Weighted Clustering Approach based on Weighted
Cluster Head Selection, which is highly energy efficient and reliable in mobile network scenario. Weight
calculation using different attributes of the nodes like SNR (Signal to Noise Ratio), Remaining Energy, Node
Degree, Mobility, and Buffer Length gives efficient Cluster Head (CH) on regular interval of time. CH rotation
helps in optimum utilization of energy available with all nodes; results in prolonged network lifetime.
Implementation is done using the NS2 network simulator and performance evaluation is carried out in terms of
PDR (Packet Delivery Ratio), End to End Delay, Throughput, and Energy Consumption. Demonstration of the
obtained results shows that proposed work is adaptable for improving the performance. In order to justify the
solution, the performance of proposed technique is compared with the performance of traditional approach. The
performance of proposed technique is found optimum as compared to the traditional techniques.
An energy-efficient cluster head selection in wireless sensor network using g...TELKOMNIKA JOURNAL
Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms.
Hyper-parameter optimization of convolutional neural network based on particl...journalBEEI
The document proposes using a particle swarm optimization (PSO) algorithm to optimize the hyperparameters of a convolutional neural network (CNN) for image classification. The PSO algorithm is used to find optimal values for CNN hyperparameters like the number and size of convolutional filters. In experiments on the MNIST handwritten digit dataset, the optimized CNN achieved a testing error rate of 0.87%, which is competitive with state-of-the-art models. The proposed approach finds optimized CNN architectures automatically without requiring manual design or encoding strategies during training.
Artificial Neural Network Based Load ForecastingIRJET Journal
This document discusses using artificial neural networks for short-term load forecasting. It compares the performance of two training algorithms - Multiple Layer Perceptron (MLP) and Least Mean Square (LMS). When MLP was used, the mean absolute percent error was 11.424%. When LMS was used, the error rate decreased and the mean absolute percent error improved to 2.64%, showing more accurate forecasting results. In conclusion, artificial neural networks are useful for short-term load forecasting and the LMS algorithm produced more promising results compared to MLP.
A Novel Technique to Enhance the Lifetime of Wireless Sensor Networks through...IJECEIAES
In the most of the real world scenarios, wireless sensor networks are used. Some of the major tasks of these types of networks is to sense some information and sending it to monitoring system or tracking some activity etc. In such applications, the sensor nodes are deployed in large area and in considerably large numbers [1]-[3]. Each of these node will be having constrained resources whether it might be energy, memory or processing capability. Energy is the major resource constraint in these types of networks. Hence enough care to be taken in all aspects such that energy can be used very efficiently. Different Activities which will be taking place in a sensor node are sensing, radio operations and receiving and computing. Among all these operations, radio consumes maximum power. Hence there is a need of reducing the power consumption in such radio operations. In the proposed work a software module is developed which will reduce the number of transmissions done to the base station. The work compares the consecutively sensed data and if these data are same then the old data then the old data will be retained. In other case the newly sensed data will be sent to the sink node. This technique reduces the number of data transmissions in a significant way. With the reduced number of transmissions, the energy saved in each node will be more, which will increase the lifetime of the entire network.
AN OPTIMIZED WEIGHT BASED CLUSTERING ALGORITHM IN HETEROGENEOUS WIRELESS SENS...cscpconf
The last few years have seen an increased interest in the potential use of wireless sensor networks (WSNs) in various fields like disastermanagementbattle field surveillance, and border security surveillance. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. The process of dividing the network into interconnected substructures is called clustering and the interconnected substructures are called clusters. The cluster head (CH) of each cluster act as a coordinator within the substructure. Each CH acts as a temporary base station within its zone or cluster. It also communicates with other CHs. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption. It can also increase network scalability. Researchers in all fields of wireless sensor network believe that nodes are homogeneous, but
some nodes may be of different characteristics to prolong the lifetime of a WSN and its reliability. We have proposed an algorithm for better cluster head selection based on weights for different parameter that influence on energy consumption which includes distance from base station as a new parameter to reduce number of transmissions and reduce energy consumption by sensor nodes. Finally proposed algorithm compared with the WCA, IWCA algorithm in terms of number of clusters and energy consumption.
AN ENHANCED HYBRID ROUTING AND CLUSTERING TECHNIQUE FOR WIRELESS SENSOR NETWORKijwmn
Wireless Sensor Networks (WSN) have extensively deployed in a wide range of applications. However, WSN still faces several limitations in processing capabilities, memory, and power supply of sensor nodes. It is required to extend the lifetime of WSN. Mainly this is achieved by routing protocols choosing the best transmission path in-network with desired power conservation.This cause is developing a generic protocol framework for WSNa big challenge. This work proposed a new routing technique, described as Hybrid Routing-Clustering (HRC) model. This new approach takes advantage of clustering and routing procedures defined in K-Mean clustering and AODV routing, which constituted of three phases. This development aims to achieve enhanced power conservation rate in consequence network lifetime. An extensive evaluation methodology utilized to measure the performance of the proposed model in simulated scenarios.The results categorized in terms of the average amount of packet received and power conservation rate. The Hybrid Routing-Clustering (HRC) model was determined, showed enhanced results regarding both parameters. In the end, they are comparing these results with well-known routing and well-known clustering algorithms.
1) The document proposes an NSGA-III based energy efficient clustering and tree-based routing protocol for wireless sensor networks.
2) It forms clusters based on remaining energy of nodes initially, then uses NSGA-III to improve inter-cluster data aggregation and select the shortest path between cluster heads and the sink.
3) Simulation results show the proposed protocol significantly improves network lifetime, throughput, and residual energy over other techniques.
Extending network lifetime of wireless sensorIJCNCJournal
One critical issue in designing and managing a wireless sensor network is how to save the energy consumption
of the sensors in order to maximize network lifetime under the constraint of full coverage of the monitored
targets. In this paper, we adopt the common approach of creating disjoint sensor covers to prolong network
lifetime. The typical goal used in the literature is to maximize the number of covers without consideration of
the energy levels of the sensors. We argue that the network lifetime can be extended by maximizing the total
bottleneck energy of the created covers. We formally define the problem of maximizing the total bottleneck
energy of the covers, present for the first time an integer programming formulation of the problem, and develop
two algorithms to solve large problem instances. Extensive experimental tests show that the use of the goal of
maximizing the total bottleneck energy of the covers creates covers with substantially longer network lifetime
than the lifetime of the covers created with the goal of maximizing solely the number of covers.
Novel approach for hybrid MAC scheme for balanced energy and transmission in ...IJECEIAES
Hybrid medium access control (MAC) scheme is one of the prominent mechanisms to offer energy efficiency in wireless sensor network where the potential features for both contention-based and schedule-based approaches are mechanized. However, the review of existing hybrid MAC scheme shows many loopholes where mainly it is observed that there is too much inclusion of time-slotting or else there is an inclusion of sophisticated mechanism not meant for offering flexibility to sensor node towards extending its services for upcoming applications of it. Therefore, this manuscript introduces a novel hybrid MAC scheme which is meant for offering cost effective and simplified scheduling operation in order to balance the performance of energy efficiency along with data aggregation performance. The simulated outcome of the study shows that proposed system offers better energy consumption, better throughput, reduced memory consumption, and faster processing in contrast to existing hybrid MAC protocols.
LOAD BALANCING AND ENERGY EFFICIENCY IN WSN BY CLUSTER JOINING METHODIAEME Publication
In any WSN life of network is depending on life of sensor node. Thus, proper load balancing is very useful for improving life of network. The tree-based routing protocols like GSTEB used dynamic tree structures for routing without any formation of collections. In cases of larger networks, the scheme is not always feasible. In this proposed work cluster-based routing method is used. Cluster head is selected such that it should be close to the base station and should have maximum residential energy than other nodes selected for cluster formation. Size of cluster is controlled by using location-based cluster joining method such that nodes selects their nearest collection head based on the signal strength from cluster head and distance between node and cluster head. Nodes connect to head having the highest signal strength and closest to the base station, this minimizes size of cluster and reduces extra energy consumption. In addition to this cluster formation process starts only after availability of data due to an event. So proposed protocol performs better than existing tree based protocols like GSTEB in terms of energy efficiency
Energy Efficient Clustering Protocol for Wireless Sensor Networks using Parti...IRJET Journal
This document proposes an energy efficient clustering protocol for wireless sensor networks called LEACH-P that uses particle swarm optimization (PSO). It aims to improve the existing LEACH protocol by using PSO to select cluster heads in a way that maximizes the residual energy of nodes. The key contributions are applying PSO to select optimal cluster heads based on residual energy, simulating the proposed LEACH-P protocol and comparing it to LEACH to determine if it improves network lifetime, stability period and data transmitted to the base station.
Sierpinski carpet fractal monopole antenna for ultra-wideband applications IJECEIAES
This summary provides an overview of a document describing a Sierpinski carpet fractal monopole antenna (SCFMA) designed for ultra-wideband applications:
1) The SCFMA is developed up to two iterations to maximize bandwidth by utilizing the space-filling and self-similar properties of the Sierpinski carpet fractal.
2) The monopole patch size is optimized to minimize the overall antenna area.
3) The SCFMA achieves bandwidth ranges of 2.6-4.0 GHz, 2.5-4.3 GHz, and 2.4-4.4 GHz for the base case, first, and second iterations, respectively, on an FR4
Tdtd-Edr: Time Orient Delay Tolerant Density Estimation Technique Based Data ...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Solution for intra/inter-cluster event-reporting problem in cluster-based pro...IJECEIAES
In recent years, wireless sensor networks (WSNs) have been considered one of the important topics for researchers due to their wide applications in our life. Several researches have been conducted to improve WSNs performance and solve their issues. One of these issues is the energy limitation in WSNs since the source of energy in most WSNs is the battery. Accordingly, various protocols and techniques have been proposed with the intention of reducing power consumption of WSNs and lengthen their lifetime. Cluster-oriented routing protocols are one of the most effective categories of these protocols. In this article, we consider a major issue affecting the performance of this category of protocols, which we call the intra/inter-cluster event-reporting problem (IICERP). We demonstrate that IICERP severely reduces the performance of a cluster-oriented routing protocol, so we suggest an effective Solution for IICERP (SIICERP). To assess SIICERP’s performance, comprehensive simulations were performed to demonstrate the performance of several cluster-oriented protocols without and with SIICERP. Simulation results revealed that SIICERP substantially increases the performance of cluster-oriented routing protocols.
IRJET- Sink Mobility based Energy Efficient Routing Protocol for Wireless Sen...IRJET Journal
The document describes a proposed sink mobility based energy efficient routing protocol for wireless sensor networks. The protocol uses both a static centralized sink and a mobile sink that follows a predetermined path with 4 sojourn locations. This is aimed to improve network lifetime by balancing energy load across nodes. Simulation results show that the proposed approach with a mobile sink performs better than the Threshold sensitive Energy Efficient sensor Network (TEEN) protocol alone in terms of number of alive nodes, number of cluster heads, and number of packets sent to the base station over multiple rounds. Using a mobile sink helps scatter the energy load in the network and extends lifetime compared to only using a static sink.
A novel predictive optimization scheme for energy-efficient reliable operatio...IJECEIAES
Wireless Sensor Network (WSN) has been studied for more than a decades that resulted in evolution of the significant applications towards assisting in sensing physical information from human inaccesible area. It was also observed from existing sysem that energy attribute is the root cause of majority of the problems associated with WSN that also gives rise to various operational reliability issue. Therefore, the prime goal of the proposed study is to present a novel predictive optimization approach of data fusion in order to jointly address the problems associated with energy efficiency and reliable operation of sensor nodes in WSN. An analytical research approach is carried out in order to ensure that a time-based synchronization scheme contributes to offer an evolutionary approach towards significant energy optimization. A simulation-based benchmarking analysis is carried out to find that proposed system offers good energy-efficient performance in comparison to existing approaches.
Analytical Modelling of Power Efficient Reliable Operation of Data Fusion in ...IJECEIAES
Irrespective of inclusion of Wireless Sensor Network (WSN) in majority of the research proposition for smart city planning, it is still shrouded with some significant issues. A closer look into problems in WSN shows that energy parameter is the origination point of majority of the other problems in resource-constrained sensors as well as it significant minimizes the reliability in standard sensory operation in adverse environment. Therefore, this manuscript presents a novel analytical model that is meant for establishing a well balance between energy efficiency over multi-path data forwarding and reliable operation with improved network performance. The complete process is emphasized during data fusion stage to ensure data quality too. A simulation study has been carried out using benchmarked test-bed of MEMSIC nodes to find that proposed system offers good energy conservation process during data fusion operation as well as it also ensure good reliable operation in comparison to existing system.
Novel framework of retaining maximum data quality and energy efficiency in re...IJECEIAES
There are various unseen and unpredictable networking states in Wireless Sensor Network (WSN) that adversely affect the aggregated data quality. After reviewing the existing approaches of data quality in WSN, it was found that the solutions are quite symptomatic and they are applicable only in a static environment; however their successful applicability on dynamic and upcoming reconfigurable network is still a big question. Moreover, data quality directly affects energy conservation among the nodes. Therefore, the proposed system introduces a simple and novel framework that jointly addresses the data quality and energy efficiency using probability-based design approach. Using a simplified analytical methodology, the proposed system offers solution in the form of selection transmission of an aggergated data on the basis of message priority in order to offer higher data utilization factor. The study outcome shows proposed system offers a good balance between data quality and energy efficiency in contrast to existing system.
Analysis of Genetic Algorithm for Effective power Delivery and with Best Upsurgeijeei-iaes
Wireless network is ready for hundreds or thousands of nodes, where each node is connected to one or sometimes more sensors. WSN sensor integrated circuits, embedded systems, networks, modems, wireless communication and dissemination of information. The sensor may be an obligation to technology and science. Recent developments underway to miniaturization and low power consumption. They act as a gateway, and prospective clients, I usually have the data on the server WSN. Other components separate routing network routers, called calculating and distributing routing tables. Discussed the routing of wireless energy balance. Optimization solutions, we have created a genetic algorithm. Before selecting an algorithm proposed for the construction of the center console. In this study, the algorithms proposed model simulated results based on "parameters depending dead nodes, the number of bits transmitted to a base station, where the number of units sent to the heads of fuel consumption compared to replay and show that the proposed algorithm has a network of a relative.
Reliable and Efficient Data Acquisition in Wireless Sensor NetworkIJMTST Journal
The sensors in the WSN sense the surrounding, collects the data and transfers the data to the sink node. It
has been observed that the sensor nodes are deactivated or damaged when exposed to certain radiations or
due to energy problems. This damage leads to the temporary isolation of the nodes from the network which
results in the formation of the holes. These holes are dynamic in nature and can grow and shrink depending
upon the factors causing the damage to the sensor nodes. So a solution has been presented in the base paper
where the dual mode i.e. Radio frequency and the Acoustic mode are considered so that the data can be
transferred easily. Based on this a survey has been done where several factors are studied so that the
performance of the system can be increased.
A Novel Weighted Clustering Based Approach for Improving the Wireless Sensor ...IJERA Editor
Great lifetime and reliability is the key aim of Wireless Sensor Network (WSN) design. As for prolonging
lifetime of this type of network, energy is the most important resource; all recent researches are focused on more
and more energy efficient techniques. Proposed work is Weighted Clustering Approach based on Weighted
Cluster Head Selection, which is highly energy efficient and reliable in mobile network scenario. Weight
calculation using different attributes of the nodes like SNR (Signal to Noise Ratio), Remaining Energy, Node
Degree, Mobility, and Buffer Length gives efficient Cluster Head (CH) on regular interval of time. CH rotation
helps in optimum utilization of energy available with all nodes; results in prolonged network lifetime.
Implementation is done using the NS2 network simulator and performance evaluation is carried out in terms of
PDR (Packet Delivery Ratio), End to End Delay, Throughput, and Energy Consumption. Demonstration of the
obtained results shows that proposed work is adaptable for improving the performance. In order to justify the
solution, the performance of proposed technique is compared with the performance of traditional approach. The
performance of proposed technique is found optimum as compared to the traditional techniques.
An energy-efficient cluster head selection in wireless sensor network using g...TELKOMNIKA JOURNAL
Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms.
Hyper-parameter optimization of convolutional neural network based on particl...journalBEEI
The document proposes using a particle swarm optimization (PSO) algorithm to optimize the hyperparameters of a convolutional neural network (CNN) for image classification. The PSO algorithm is used to find optimal values for CNN hyperparameters like the number and size of convolutional filters. In experiments on the MNIST handwritten digit dataset, the optimized CNN achieved a testing error rate of 0.87%, which is competitive with state-of-the-art models. The proposed approach finds optimized CNN architectures automatically without requiring manual design or encoding strategies during training.
Artificial Neural Network Based Load ForecastingIRJET Journal
This document discusses using artificial neural networks for short-term load forecasting. It compares the performance of two training algorithms - Multiple Layer Perceptron (MLP) and Least Mean Square (LMS). When MLP was used, the mean absolute percent error was 11.424%. When LMS was used, the error rate decreased and the mean absolute percent error improved to 2.64%, showing more accurate forecasting results. In conclusion, artificial neural networks are useful for short-term load forecasting and the LMS algorithm produced more promising results compared to MLP.
A Novel Technique to Enhance the Lifetime of Wireless Sensor Networks through...IJECEIAES
In the most of the real world scenarios, wireless sensor networks are used. Some of the major tasks of these types of networks is to sense some information and sending it to monitoring system or tracking some activity etc. In such applications, the sensor nodes are deployed in large area and in considerably large numbers [1]-[3]. Each of these node will be having constrained resources whether it might be energy, memory or processing capability. Energy is the major resource constraint in these types of networks. Hence enough care to be taken in all aspects such that energy can be used very efficiently. Different Activities which will be taking place in a sensor node are sensing, radio operations and receiving and computing. Among all these operations, radio consumes maximum power. Hence there is a need of reducing the power consumption in such radio operations. In the proposed work a software module is developed which will reduce the number of transmissions done to the base station. The work compares the consecutively sensed data and if these data are same then the old data then the old data will be retained. In other case the newly sensed data will be sent to the sink node. This technique reduces the number of data transmissions in a significant way. With the reduced number of transmissions, the energy saved in each node will be more, which will increase the lifetime of the entire network.
AN OPTIMIZED WEIGHT BASED CLUSTERING ALGORITHM IN HETEROGENEOUS WIRELESS SENS...cscpconf
The last few years have seen an increased interest in the potential use of wireless sensor networks (WSNs) in various fields like disastermanagementbattle field surveillance, and border security surveillance. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. The process of dividing the network into interconnected substructures is called clustering and the interconnected substructures are called clusters. The cluster head (CH) of each cluster act as a coordinator within the substructure. Each CH acts as a temporary base station within its zone or cluster. It also communicates with other CHs. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption. It can also increase network scalability. Researchers in all fields of wireless sensor network believe that nodes are homogeneous, but
some nodes may be of different characteristics to prolong the lifetime of a WSN and its reliability. We have proposed an algorithm for better cluster head selection based on weights for different parameter that influence on energy consumption which includes distance from base station as a new parameter to reduce number of transmissions and reduce energy consumption by sensor nodes. Finally proposed algorithm compared with the WCA, IWCA algorithm in terms of number of clusters and energy consumption.
AN ENHANCED HYBRID ROUTING AND CLUSTERING TECHNIQUE FOR WIRELESS SENSOR NETWORKijwmn
Wireless Sensor Networks (WSN) have extensively deployed in a wide range of applications. However, WSN still faces several limitations in processing capabilities, memory, and power supply of sensor nodes. It is required to extend the lifetime of WSN. Mainly this is achieved by routing protocols choosing the best transmission path in-network with desired power conservation.This cause is developing a generic protocol framework for WSNa big challenge. This work proposed a new routing technique, described as Hybrid Routing-Clustering (HRC) model. This new approach takes advantage of clustering and routing procedures defined in K-Mean clustering and AODV routing, which constituted of three phases. This development aims to achieve enhanced power conservation rate in consequence network lifetime. An extensive evaluation methodology utilized to measure the performance of the proposed model in simulated scenarios.The results categorized in terms of the average amount of packet received and power conservation rate. The Hybrid Routing-Clustering (HRC) model was determined, showed enhanced results regarding both parameters. In the end, they are comparing these results with well-known routing and well-known clustering algorithms.
1) The document proposes an NSGA-III based energy efficient clustering and tree-based routing protocol for wireless sensor networks.
2) It forms clusters based on remaining energy of nodes initially, then uses NSGA-III to improve inter-cluster data aggregation and select the shortest path between cluster heads and the sink.
3) Simulation results show the proposed protocol significantly improves network lifetime, throughput, and residual energy over other techniques.
Extending network lifetime of wireless sensorIJCNCJournal
One critical issue in designing and managing a wireless sensor network is how to save the energy consumption
of the sensors in order to maximize network lifetime under the constraint of full coverage of the monitored
targets. In this paper, we adopt the common approach of creating disjoint sensor covers to prolong network
lifetime. The typical goal used in the literature is to maximize the number of covers without consideration of
the energy levels of the sensors. We argue that the network lifetime can be extended by maximizing the total
bottleneck energy of the created covers. We formally define the problem of maximizing the total bottleneck
energy of the covers, present for the first time an integer programming formulation of the problem, and develop
two algorithms to solve large problem instances. Extensive experimental tests show that the use of the goal of
maximizing the total bottleneck energy of the covers creates covers with substantially longer network lifetime
than the lifetime of the covers created with the goal of maximizing solely the number of covers.
Novel approach for hybrid MAC scheme for balanced energy and transmission in ...IJECEIAES
Hybrid medium access control (MAC) scheme is one of the prominent mechanisms to offer energy efficiency in wireless sensor network where the potential features for both contention-based and schedule-based approaches are mechanized. However, the review of existing hybrid MAC scheme shows many loopholes where mainly it is observed that there is too much inclusion of time-slotting or else there is an inclusion of sophisticated mechanism not meant for offering flexibility to sensor node towards extending its services for upcoming applications of it. Therefore, this manuscript introduces a novel hybrid MAC scheme which is meant for offering cost effective and simplified scheduling operation in order to balance the performance of energy efficiency along with data aggregation performance. The simulated outcome of the study shows that proposed system offers better energy consumption, better throughput, reduced memory consumption, and faster processing in contrast to existing hybrid MAC protocols.
LOAD BALANCING AND ENERGY EFFICIENCY IN WSN BY CLUSTER JOINING METHODIAEME Publication
In any WSN life of network is depending on life of sensor node. Thus, proper load balancing is very useful for improving life of network. The tree-based routing protocols like GSTEB used dynamic tree structures for routing without any formation of collections. In cases of larger networks, the scheme is not always feasible. In this proposed work cluster-based routing method is used. Cluster head is selected such that it should be close to the base station and should have maximum residential energy than other nodes selected for cluster formation. Size of cluster is controlled by using location-based cluster joining method such that nodes selects their nearest collection head based on the signal strength from cluster head and distance between node and cluster head. Nodes connect to head having the highest signal strength and closest to the base station, this minimizes size of cluster and reduces extra energy consumption. In addition to this cluster formation process starts only after availability of data due to an event. So proposed protocol performs better than existing tree based protocols like GSTEB in terms of energy efficiency
Energy Efficient Clustering Protocol for Wireless Sensor Networks using Parti...IRJET Journal
This document proposes an energy efficient clustering protocol for wireless sensor networks called LEACH-P that uses particle swarm optimization (PSO). It aims to improve the existing LEACH protocol by using PSO to select cluster heads in a way that maximizes the residual energy of nodes. The key contributions are applying PSO to select optimal cluster heads based on residual energy, simulating the proposed LEACH-P protocol and comparing it to LEACH to determine if it improves network lifetime, stability period and data transmitted to the base station.
Sierpinski carpet fractal monopole antenna for ultra-wideband applications IJECEIAES
This summary provides an overview of a document describing a Sierpinski carpet fractal monopole antenna (SCFMA) designed for ultra-wideband applications:
1) The SCFMA is developed up to two iterations to maximize bandwidth by utilizing the space-filling and self-similar properties of the Sierpinski carpet fractal.
2) The monopole patch size is optimized to minimize the overall antenna area.
3) The SCFMA achieves bandwidth ranges of 2.6-4.0 GHz, 2.5-4.3 GHz, and 2.4-4.4 GHz for the base case, first, and second iterations, respectively, on an FR4
Tdtd-Edr: Time Orient Delay Tolerant Density Estimation Technique Based Data ...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Solution for intra/inter-cluster event-reporting problem in cluster-based pro...IJECEIAES
In recent years, wireless sensor networks (WSNs) have been considered one of the important topics for researchers due to their wide applications in our life. Several researches have been conducted to improve WSNs performance and solve their issues. One of these issues is the energy limitation in WSNs since the source of energy in most WSNs is the battery. Accordingly, various protocols and techniques have been proposed with the intention of reducing power consumption of WSNs and lengthen their lifetime. Cluster-oriented routing protocols are one of the most effective categories of these protocols. In this article, we consider a major issue affecting the performance of this category of protocols, which we call the intra/inter-cluster event-reporting problem (IICERP). We demonstrate that IICERP severely reduces the performance of a cluster-oriented routing protocol, so we suggest an effective Solution for IICERP (SIICERP). To assess SIICERP’s performance, comprehensive simulations were performed to demonstrate the performance of several cluster-oriented protocols without and with SIICERP. Simulation results revealed that SIICERP substantially increases the performance of cluster-oriented routing protocols.
IRJET- Sink Mobility based Energy Efficient Routing Protocol for Wireless Sen...IRJET Journal
The document describes a proposed sink mobility based energy efficient routing protocol for wireless sensor networks. The protocol uses both a static centralized sink and a mobile sink that follows a predetermined path with 4 sojourn locations. This is aimed to improve network lifetime by balancing energy load across nodes. Simulation results show that the proposed approach with a mobile sink performs better than the Threshold sensitive Energy Efficient sensor Network (TEEN) protocol alone in terms of number of alive nodes, number of cluster heads, and number of packets sent to the base station over multiple rounds. Using a mobile sink helps scatter the energy load in the network and extends lifetime compared to only using a static sink.
A novel predictive optimization scheme for energy-efficient reliable operatio...IJECEIAES
Wireless Sensor Network (WSN) has been studied for more than a decades that resulted in evolution of the significant applications towards assisting in sensing physical information from human inaccesible area. It was also observed from existing sysem that energy attribute is the root cause of majority of the problems associated with WSN that also gives rise to various operational reliability issue. Therefore, the prime goal of the proposed study is to present a novel predictive optimization approach of data fusion in order to jointly address the problems associated with energy efficiency and reliable operation of sensor nodes in WSN. An analytical research approach is carried out in order to ensure that a time-based synchronization scheme contributes to offer an evolutionary approach towards significant energy optimization. A simulation-based benchmarking analysis is carried out to find that proposed system offers good energy-efficient performance in comparison to existing approaches.
Analytical Modelling of Power Efficient Reliable Operation of Data Fusion in ...IJECEIAES
Irrespective of inclusion of Wireless Sensor Network (WSN) in majority of the research proposition for smart city planning, it is still shrouded with some significant issues. A closer look into problems in WSN shows that energy parameter is the origination point of majority of the other problems in resource-constrained sensors as well as it significant minimizes the reliability in standard sensory operation in adverse environment. Therefore, this manuscript presents a novel analytical model that is meant for establishing a well balance between energy efficiency over multi-path data forwarding and reliable operation with improved network performance. The complete process is emphasized during data fusion stage to ensure data quality too. A simulation study has been carried out using benchmarked test-bed of MEMSIC nodes to find that proposed system offers good energy conservation process during data fusion operation as well as it also ensure good reliable operation in comparison to existing system.
Novel framework of retaining maximum data quality and energy efficiency in re...IJECEIAES
There are various unseen and unpredictable networking states in Wireless Sensor Network (WSN) that adversely affect the aggregated data quality. After reviewing the existing approaches of data quality in WSN, it was found that the solutions are quite symptomatic and they are applicable only in a static environment; however their successful applicability on dynamic and upcoming reconfigurable network is still a big question. Moreover, data quality directly affects energy conservation among the nodes. Therefore, the proposed system introduces a simple and novel framework that jointly addresses the data quality and energy efficiency using probability-based design approach. Using a simplified analytical methodology, the proposed system offers solution in the form of selection transmission of an aggergated data on the basis of message priority in order to offer higher data utilization factor. The study outcome shows proposed system offers a good balance between data quality and energy efficiency in contrast to existing system.
Energy-efficient data-aggregation for optimizing quality of service using mo...IJECEIAES
Quality of service (QoS) is essential for carrying out data transmission using resource-constrained sensor nodes in wireless sensor network (WSN). The introduction of mobile agent-based data aggregation is reported to offer energy efficiency; however, it has limitations, especially using a single mobile agent, where QoS optimization is not feasible. A review of existing studies showcases some dedicated attempts to use a mobile agent-based approach and address QoS enhancements. However, they were never combined studied. Therefore, this paper introduces a unique concept of retaining maximum QoS performance during data aggregation using a single mobile agent. The model introduces a unique communication framework, transmission provisioning using exceptional routine management, and simplified energy modeling. The proposed model has aimed for a lower delay and faster data aggregation speed with lower consumption of transmittance energy. The implementation and assessment of the model are carried out considering the challenging environment of WSN with multiple scales of data priority. The proposed model also contributes to evolving out with simplified communication vectors in a highly decentralized method. MATLAB's simulation outcome shows that the proposed system offers better delay performance, optimal energy management, and faster response time than existing schemes.
An algorithm for fault node recovery of wireless sensor networkeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Particle Swarm Optimization Based QoS Aware Routing for Wireless Sensor Networksijsrd.com
Efficiency in a Wireless Sensor Network can only be obtained with effective routing mechanisms. This paper uses Particle Swarm Optimization (PSO, a metaheuristic algorithm to perform the process of routing. Since PSO does not have a defined fitness function, it is flexible to incorporate user defined QoS parameters to define the fitness function.
Novel Bacteria Foraging Optimization for Energy-efficient Communication in Wi...IJECEIAES
Optimization techniques based on Swarm-intelligence has been reported to have significant benefits towards addressing communication issues in Wireless Sensor Network (WSN). We reviewed the most dominant swarm intelligence technique called as Bacteria Foraging Optimization (BFO) to find that there are very less significant model towards addressing the problems in WSN. Therefore, the proposed paper introduced a novel BFO algorithm which maintains a very good balance between the computational and communication demands of a sensor node unlike the conventional BFO algorithms. The significant contribution of the proposed study is to minimize the iterative steps and inclusion of minimization of both receiving / transmittance power in entire data aggregation process. The study outcome when compared with standard energy-efficient algorithm was found to offer superior network lifetime in terms of higher residual energy as well as data transmission performance.
In order to provide sensing services to low-powered IoT devices, wireless sensor networks (WSNs) organize specialized transducers into networks. Energy usage is one of the most important design concerns in WSN because it is very hard to replace or recharge the batteries in sensor nodes. For an energy-constrained network, the clustering technique is crucial in preserving battery life. By strategically selecting a cluster head (CH), a network's load can be balanced, resulting in decreased energy usage and extended system life. Although clustering has been predominantly used in the literature, the concept of chain-based clustering has not yet been explored. As a result, in this paper, we employ a chain-based clustering architecture for data dissemination in the network. Furthermore, for CH selection, we employ the coati optimisation algorithm, which was recently proposed and has demonstrated significant improvement over other optimization algorithms. In this method, the parameters considered for selecting the CH are energy, node density, distance, and the network’s average energy. The simulation results show tremendous improvement over the competitive cluster-based routing algorithms in the context of network lifetime, stability period (first node dead), transmission rate, and the network's power reserves.
LOAD BALANCING AND ENERGY EFFICIENCY IN WSN BY CLUSTER JOINING METHODIAEME Publication
In any WSN life of network is depending on life of sensor node. Thus, proper load balancing is very useful for improving life of network. The tree-based routing protocols like GSTEB used dynamic tree structures for routing without any formation of collections. In cases of larger networks, the scheme is not always feasible. In this proposed work cluster-based routing method is used. Cluster head is selected such that it should be close to the base station and should have maximum residential energy than other nodes selected for cluster formation. Size of cluster is controlled by using location-based cluster joining method such that nodes selects their nearest collection head based on the signal strength from cluster head and distance between node and cluster head. Nodes connect to head having the highest signal strength and closest to the base station, this minimizes size of cluster and reduces extra energy consumption. In addition to this cluster formation process starts only after availability of data due to an event. So proposed protocol performs better than existing tree based protocols like GSTEB in terms of energy efficiency
Energy efficient intelligent routing in WSN using dominant genetic algorithmIJECEIAES
In the current era of wireless sensor network development, among the various challeng- ing issues, the life enhancement has obtained the prime interest. Reason is clear and straight: the battery operated sensors do have limited period of life hence to keep the network active as much as possible, life of network should be larger. To enhance the life of the network, at different level different approaches has been applied, broadly defining the proper scheduling of sensors and defining the energy efficient communication. In this paper heuristic based energy efficient communication approch has applied. A new development in the Genetic algorithm has presented and called as Dominant Genetic algorithm to determine the optimum energy efficient routing path between sensor nodes and to define the optimal energy efficient trajectory for mobile data gathering node. Dominancy of high fitness solution has included in the Genetic algorithm because of its natural existence. The proposed solution has applied the connection oriented crossover and mutation operator to maintain the feasibility of generated solution. The proposed solution has applied with various simulation experiments under two different scenarios: in first case energy efficient routes among the sensors have explored to deliver the information from source sensor to the sink node and in second case, energy efficient route among all local data hubs for mobile data gathering node has obtained. The proposed solution performances have been analyzed quantitatively and analytically. It has observed with various experimental results that proposed method not only has delivered the better solution but also has faster convergence and high level of reliability in compared to conventional form of Genetic algorithm.
Lifetime centric load balancing mechanism in wireless sensor network based Io...IJECEIAES
This summary provides the key details from the document in 3 sentences:
The document proposes a new mechanism called the Lifetime Centric Load Balancing Mechanism (LCLBM) to improve load balancing and maximize lifetime in wireless sensor networks for IoT applications. LCLBM focuses on cluster head selection, network design, optimal cluster head distribution, and introduces assistant cluster heads to help balance the load. The proposed LCLBM mechanism is evaluated based on important metrics like energy consumption, communication overhead, number of failed nodes, and delay, and shows improved performance compared to an existing ES-Leach method.
Wide Area Monitoring, Protection and Control (WAMPAC) Application in Transmis...IRJET Journal
This document provides a literature review on the application of Wide Area Monitoring, Protection and Control (WAMPAC) in transmission grids. It discusses technologies used in WAMPAC systems such as Phasor Measurement Units (PMUs), Flexible AC Transmission Systems (FACTS) devices, and Phase Shifting Transformers (PSTs). The literature review covers past research on optimal placement of PMUs and FACTS devices in transmission networks to maximize observability and control. It also examines the use of WAMPAC technologies to monitor system oscillations and stability. The review provides background information for a proposed project to model and simulate the application of WAMPAC technologies in a transmission grid.
Routing Optimization with Load Balancing: an Energy Efficient ApproachEswar Publications
The area of Wireless Sensor Network (WSN) is covered with considerable range of problems, where majority of research attempts were carried out to enhance the network lifetime of WSN. But very few of the studies have proved successful. This manuscript discusses about a structure for optimizing routing and load balancing that uses standard radio and energy model to perform energy optimization by introducing a novel routing agent. The routing agent is built within aggregator node and base station to perform self motivated reconfiguration in case of energy depletion. Compared with standard LEACH algorithm, the proposed technique has better energy efficiency within optimal data aggregation duration.
IoT Resource Allocation and Optimization Using Improved Reptile Search AlgorithmIJCNCJournal
The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet. The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively.
IoT Resource Allocation and Optimization Using Improved Reptile Search AlgorithmIJCNCJournal
The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet. The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively.
This document contains two papers. The first paper summarizes a study that designed a prototype smoke detection device for a student dormitory at Klabat University using a microcontroller, MQ-7 and UV-Tron sensors, buzzer, and SMS gateway to detect cigarette smoke and notify users. The second paper proposes a wireless sensor network design for environmental monitoring applications to measure temperature, humidity, CO2, and other factors.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal
Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered as the main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance, which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal
Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered asthe main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance,which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
Short Term Load Forecasting Using Bootstrap Aggregating Based Ensemble Artifi...Kashif Mehmood
Short Term Load Forecasting (STLF) can predict load from several minutes to week plays
the vital role to address challenges such as optimal generation, economic scheduling, dispatching and
contingency analysis. This paper uses Multi-Layer Perceptron (MLP) Artificial Neural Network
(ANN) technique to perform STFL but long training time and convergence issues caused by bias,
variance and less generalization ability, unable this algorithm to accurately predict future loads. This
issue can be resolved by various methods of Bootstraps Aggregating (Bagging) (like disjoint
partitions, small bags, replica small bags and disjoint bags) which helps in reducing variance and
increasing generalization ability of ANN. Moreover, it results in reducing error in the learning process
of ANN. Disjoint partition proves to be the most accurate Bagging method and combining outputs of
this method by taking mean improves the overall performance. This method of combining several
predictors known as Ensemble Artificial Neural Network (EANN) outperform the ANN and Bagging
method by further increasing the generalization ability and STLF accuracy.
Similar to Novel Scheme for Minimal Iterative PSO Algorithm for Extending Network Lifetime of Wireless Sensor Network (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Software Engineering and Project Management - Software Testing + Agile Method...Prakhyath Rai
Software Testing: A Strategic Approach to Software Testing, Strategic Issues, Test Strategies for Conventional Software, Test Strategies for Object -Oriented Software, Validation Testing, System Testing, The Art of Debugging.
Agile Methodology: Before Agile – Waterfall, Agile Development.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Blood finder application project report (1).pdfKamal Acharya
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the user’s time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...Transcat
Join us for this solutions-based webinar on the tools and techniques for commissioning and maintaining PV Systems. In this session, we'll review the process of building and maintaining a solar array, starting with installation and commissioning, then reviewing operations and maintenance of the system. This course will review insulation resistance testing, I-V curve testing, earth-bond continuity, ground resistance testing, performance tests, visual inspections, ground and arc fault testing procedures, and power quality analysis.
Fluke Solar Application Specialist Will White is presenting on this engaging topic:
Will has worked in the renewable energy industry since 2005, first as an installer for a small east coast solar integrator before adding sales, design, and project management to his skillset. In 2022, Will joined Fluke as a solar application specialist, where he supports their renewable energy testing equipment like IV-curve tracers, electrical meters, and thermal imaging cameras. Experienced in wind power, solar thermal, energy storage, and all scales of PV, Will has primarily focused on residential and small commercial systems. He is passionate about implementing high-quality, code-compliant installation techniques.
Height and depth gauge linear metrology.pdfq30122000
Height gauges may also be used to measure the height of an object by using the underside of the scriber as the datum. The datum may be permanently fixed or the height gauge may have provision to adjust the scale, this is done by sliding the scale vertically along the body of the height gauge by turning a fine feed screw at the top of the gauge; then with the scriber set to the same level as the base, the scale can be matched to it. This adjustment allows different scribers or probes to be used, as well as adjusting for any errors in a damaged or resharpened probe.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
2. Int J Elec & Comp Eng ISSN: 2088-8708
Novel Scheme for Minimal Iterative PSO Algorithm for Extending Network Lifetime of …. (Hemavathi P)
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problem (be it engineering or scientific). PSO is completely independent of computing mutation which has
no overlapping. The velocity of the particle can be mechanism for initiating the search process and this
makes the calculation process of PSO very simple. It also offers potentially better results as compared to
other optimization techniques ever used in wireless sensor network. However, there is also certain associated
usage of PSO-based mechanism in wireless sensor network. PSO is associated with partial-optimization
problem that also tend to minimize the accuracy level of velocity factor of the particle as well as its direction.
It is also not a preferred technique for solving the scattering problems in any wireless network. Most
importantly, it is an iterative process and it will be required to store lots of information pertaining to its
intermediate passes in order to perform comparative analysis of the elite outcome with respect to the personal
and global best solution. However, there are various work carried out in existing system where the problems
associated with the energy and clustering in wireless sensor network has been found solved by PSO-based
approaches. In real sense, there are only few works in existing system which has amended original PSO
implementation and hence, it is quite challenging to explore the level of effectiveness of existing system.
Therefore, the proposed paper introduced a novel and simple attempt where the PSO is amended to get itself
free from number of increasing iterative steps as a part of research contribution. The study outcome shows
that proposed revised version of PSO offers better beneficial characteristics to both energy efficiency as well
as data delivery system in wireless sensor network. Section 1.1 discusses about the existing literatures where
different techniques are discussed for PSO based schemes used in solving multiple ranges of problems
followed by discussion of research problems in Section 1.2 and proposed solution in 1.3. Section 2 discusses
about algorithm implementation followed by discussion of result analysis in Section 3. Finally, the
conclusive remarks are provided in Section 4.
1.1. Background
Our prior research work has discussed different forms of approaches for retaining maximum energy
in wireless sensor network [10]. This part of the study will further add different forms of contributions made
by PSO in the area of wireless sensor network. Clustering-based approach was adopted for enhancing
network lifetime using PSO as seen in the work of Zhou et al. [11]. Study towards cluster head selection is
also carried out by Ni et al. [12] where PSO is used along with Fuzzy logic for optimizing clustering
performance in sensor network. PSO algorithm was also found to optimize energy efficiency exclusively for
software-defined aspects in sensory application. Xiang et al. [13] have presented a technique for energy
conservation for software-defined sensor network. Issues of maintaining higher degree of fault tolerance
while scheduling the allocation process of task can be also handled by PSO as seen in the work carried out by
Guo et al. [14]. The work carried out by Parvin [15] has used PSO for overcoming non-participation process
of nodes during aggregation process. Wu and Lin [16] have investigated the effect of PSO for exploring the
specific absorption rate of wireless body area network. Study towards allocation of task is also carried out by
Yang et al. [17] where the focus was laid on formulating transfer function and usage of mutation. Rahman
and Matin [18] have presented their contribution towards enhancing the network lifetime using PSO for
exploring the better position of the base station. Ho et al. [19] have used PSO for assisting in routing process
for unmanned aerial vehicle using cooperative relay. Usage of PSO was seen in the work of Loscri et al. [20]
who have used consensus aspects for searching better area in sensor network field. Chen et al. [21] have
introduced a mechanism of charging deployment in order to enhance the optimality of energy performance in
sensor network. Du et al. [22] have presented a mechanism of eliminating the electromagnetic interference
while performing beaconing in wireless sensor network using PSO. The work carried out by Chen et al. [23]
has used PSO as well as Cuckoo search technique in order to strengthen the security system of WSN. PSO
was also used for addressing the self-localization problem in wireless sensor network by modifying some of
its functionalities as seen in the work of Kun and Zhong [24]. Thilagavathi and Geetha [25] have presented a
search algorithm for enhancing the residual energy of WSN. Elhabyan et al. [26] have presented a technique
for enhancing the clustering operation while Huynh et al. [27] have developed a non-conventional PSO
algorithm for prolonging the network lifetime taking case study of heterogeneous sensor network.
Implementation of binary PSO for assisting in localization problem was seen in the work of Zain and Shin
[28]. Cao et al. [29] have investigated the effectiveness of PSO by comparing with the conventional approach
for solving localization problem. Jing et al. [30] have presented a similar approach where PSO was found to
enhance the clustering operation of WSN. The combined work of Riaz and Srirammanoj [31] presented the
sufficient authentication mechanism and achieved significant power redundancy in WSN lifetime. A novel
review work on PSO based clustering routing protocol in WSN was found in Sun et al. [32] and hints for
performance enhancement in the routing protocol. Rui et al. [33] discussed the clustering routing protocol in
WSN and compared its performance with existing LEECH algorithm. This protocol provides the nodes
energy balance and improves the network lifetime. Therefore, there are various variants of the PSO based
3. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 2, April 2018 : 1084 – 1091
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approaches mainly to solve clustering, energy efficiency, and localization issues in wireless sensor network.
The next section highlights the research problems that has been identified from the above mentioned research
approaches.
1.2. Problem Identification
The problem identification of the proposed study is as follows:
a. Existing approaches using PSO has the split emphasis on clustering, energy efficiency, and
localization problems where energy has not yet received a full proof solution.
b. The extent of amendments towards using the new version of PSO is very less and doesn't turn
out to be a practically viable solution in large scale and dense networks.
c. Existing PSO techniques also renders a higher number of iterations to obtain better convergence
performance. Therefore, it leads to computational complexity.
d. Compliance with standard energy modeling is less found to be adopted in existing literature,
which without benchmarking is very hard to find its effectiveness against energy effectiveness.
Therefore, the problem statement of the proposed study can be stated as “Designing a computational
friendly approach for formulating a novel selection of clusterhead to offer energy efficiency in a wireless
sensor network.”
1.3. Proposed Solution
The proposed system adopts an analytical research methodology to implement the optimization
algorithm by enhancing the operation carried out by conventional PSO. Figure 1 highlight the design flow
signifying that optimization of PSO was carried out by considering decision variables formulated by sensor
nodes and their respective probability of becoming a clusterhead. The decision variables are also dependent
on its size and bound (lower/higher) for effective control over the PSO iterations.
Algorithm for
optimizing
PSO
Algorithm for
Enhancing
Network
Lifetime
Decision
VariablesSize
Bound
Population Size
Inertia Weight
Inertia Weight
Damping Ratio
Learning
Coefficient
update
pbest
gbest
Apply Limits
(p, v)
Select CH
Minimize ETx
1st order Radio-
Energy Model
Figure 1. Design Flow of Proposed System
The contribution of the proposed system is its novelty introduced in PSO algorithm. The algorithm
uses inertial weight, damping ratio, and learning coefficient (both local and global) to initially perform
updating using a novel empirical approach to obtain personal best and global best. Using the limits applied to
position and velocity along with global best outcome is used for selecting the effective clusterheads. An
algorithm for enhancing network lifetime is designed using 1st
order Radio-Energy model for computing
energy required to transmit and receive the data packet. Implementation of this model only ensures that
proposed system adheres to an empirical methodology where energy modeling is formulated by its real-
demands of communication. This operation is followed by minimizing the energy required for transmittance
for the clusterhead that results in significant retention of the residual energy for a long run of the sensory
application. The complete operation of saving the transmittance energy is carried out in two phases where the
first phase focuses on the node to clusterhead and communication among clusterheads while the second
phase focuses on only clusterheads to base station. The specific agenda of the proposed system is to minimize
4. Int J Elec & Comp Eng ISSN: 2088-8708
Novel Scheme for Minimal Iterative PSO Algorithm for Extending Network Lifetime of …. (Hemavathi P)
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the iteration required to explore the global best solution in PSO that assists in minimizing overheads and any
form of bottleneck condition owing to increasing traffic condition in a wireless sensor network. The next
section discusses the algorithm implemented to pursue the flow of proposed research objectives as shown in
Figure 1.
2. ALGORITHM IMPLEMENTATION
The proposed system offers an algorithm that is constructed by enhancing the PSO algorithm
ONtwo purposes. The first purpose serves for optimizing the PSO performance by obtaining a global best
solution with extremely less iterative step unlike conventional PSO and the second purpose is mainly to
extend the residual energy of the sensor node as far as possible. The discussions of the algorithm are as
follows:
2.1. Algorithm for Optimizing PSO
This algorithm is mainly responsible for ensuring that an effective cluster head is selected for
offering better optimization performance with energy efficiency. It is believed that if the cluster head is
selected properly than network lifetime could be positively enhanced. Here the selection is completely based
on multiple parameters, e.g., number of nodes, the position of particles, velocity of particles, updating
process, cost function involved in PSO methodology. The algorithm for optimizing the PSO is mainly carried
out for reducing the number of iterative steps involved in exploring the global best function in PSO. For this
purpose, the algorithm considers the input of η(number of population), p (position), v (velocity), σ (variance),
and rmax (maximum rounds) that after processing leads to the result of solbest (best solution).
Algorithm for optimizing PSO
Input:η, p, v, σ, rmax.
Output:solbest
Start
1. Forit=1: rmax
2. For i=1:η
3. p(σmin, σsize), v(σsize), ccf(par(i)), pos)
4. updatev, pbest, gbest
5. par(i). v=w.par(i)+c1.ϕ(σsize).( par(i).pbest-par(i).pos)+c2. ϕ(σsize).(gbest.pos-par(i).pos)// ϕrand
6. par(i).[velpos]=[max min v][max min pos]
7. par(i). pos=par(i).pos+par(i).v
8. par(i).c=cf(par(i).pos)
9. Ifpar(i).c<par(i).cbest
10. par(posbestcbest)=par(posc)
11. Ifpar(i)cbest<c(gbest)
12. gbest=par(i).best
13. End
14. End
14. solbestgbest
16. End
17. End
End
The number of clusters is equivalent to the product of the number of nodes and probability of node
to opt for becoming a cluster head. The algorithm initially finds the position, velocity, and cost of the particle
using minimum variance, size of variance, and position attributes (Line-3) for all number of populations (η).
It then opts for updating the velocity, personal best and global best (Line-4) using position and cost attribute
of the particle. The next part of the study considers updating the other parameters for maximum iteration
rounds using the empirical expression of velocity v (Line-5). The next part of the algorithm is for applying
the maximum and minimum limits of velocity (Line-6) followed by updating the position particles using
empirical expression highlighted in Line-7. The cost attribute is further evaluated considering the particle
position (Line-8). If the cost of the particle is found to be less than the best value of the cost (Line-9) than the
algorithm chooses to assign the normal position as best position and normal cost as best cost (Line-10).
However, if the personal best cost of the particle is found to be less than the global best cost than (Line-11)
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the algorithm applies the personal best cost to the global best cost (Line-12). This global best cost is finally
considered to be the best solution itself (Line-12 and Line-15). For better control of the iteration, the
algorithm can restrict the iteration of best cost to any value (in the proposed system, we have iterated it to 20
times to found better outcomes). Therefore, the proposed algorithm could successfully optimize the best
position of the particle which is directly mapped to the selection process of the cluster head. Hence,
optimizing the existing PSO offers better control of the selection mechanism that directly effects energy
conservation in the data forwarding process.
2.2. Algorithm for Enhancing Network Lifetime
This algorithm is responsible for improving the network lifetime of the sensor network where the
focus is laid to the energy being depleted by the clusterhead itself. It is because if the transmittance energy of
clusterhead Etx is reduced than a significant amount of the energy could be postponed for a faster rate of
depletion of the battery of a node. The algorithm takes the input of E (residual energy) and N (number of
nodes) that after processing leads to a generation of output as Eout (revised residual energy).
Algorithm for Enhancing Network Lifetime
Input: E, N
Output: Eout
Start
1. Did=E≤0
2. For i=1: Nch
3. idx=(Cid= = i)
4. End
5. For i=1: N
6. Etx=α(d, PL)
7. Erx=β(PL)
8. E1=E-Etx& E2=E(CH(idc))-Erx//idc is a matrix that stores identity of the clustered
9. End
10. For i=1:size(CH)
11. Etx=α(d, PL+PL*Pcount(i))
12. E(CH(i))E(CH(i))-Etx
13.End
14. If ∑E(CH)≤0
15. Apply Algorithm-1
16. CHnewCH(CC, Nch, xy, Did)
17. getEoutE
18. End
End
The algorithm formulates a simple condition for identifying dead node Did as the node with lesser
residual energy E (Line-1). The initial part of the study is to obtain the center point of the cluster, and then it
obtains all the index of the ith cluster (Line-3) for all the values of clusterheads (Line-2). For all the number
of nodes (Line-5), the algorithm applies the first order radio-energy modeling to apply function for
computing transmittance energy α (Line-6) and receiving energy β (Line-7). A closer look at the expression
shows that transmittance energy depends on Euclidean distance d and packet length PL (Line-6) while
receiving energy only depends on packet length (Line-7). The next step of the algorithm is mainly used for
minimizing both transmittance energy E1 and receiving energy E2 using the expression shown in Line-8. The
complete process of minimization of the energy (E1 and E2) is only from member node to clusterhead and
clusterhead to another clusterhead. The algorithm now revises the computation by considering only
communication from clusterhead to base station (Line-10) where first the coordinates of the cluster heads are
obtained followed by computation of transmittance energy Etx (Line-11) by applying mathematical
expressions of first-order radio-energy model considering the input arguments of Euclidean distance between
the cluster head and base station, length of the data packet, and number of cluster head. It then reduces the
energy by subtracting it with the Etx recently computed (Line-12). The process is carried out for all the active
clusterheads in the sensor network. Interestingly, in case of the dead of any clusterhead, the algorithm applies
proposed PSO (Line-15) to compute the new clusterhead (Line-14). The complete computation is carried out
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to find the dead node and identifying the position of the dead nodes so that simultaneous updates can be
carried on the PSO that further optimizes the operation process involves in proposed PSO algorithm. In this
case, the proposed PSO algorithm is applied considering the input arguments of (a) best position CC,
(b) number of clusterheads Nch, (c) position information by, and (d) dead node identity Did. Therefore,
irrespective of any position of the sensor node, the proposed algorithm is meant for reducing the
transmittance energy of the cluster head. Hence, the network lifetime of the wireless sensor network is
significantly enhanced with lesser dependencies on the position of the sensor nodes considering both dense
and scarce network. This indirectly minimizes the computational complexities associated with the
implementation of swarm intelligence algorithm in a wireless sensor network. The next section discusses the
results obtained by implementing the proposed algorithm.
3. RESULT ANALYSIS
The implementation of the proposed algorithm is carried out using the Matlab and assessed
concerning both energy and data delivery parameters for assessing the effect of proposed PSO-based
optimization. The study outcome was compared with conventional LEACH algorithm for 1800 simulation
rounds. The outcomes show that proposed system with PSO offers better network lifetime (Figure 2) and
better throughput (Figure 3) as compared to LEACH.
Figure 2. Comparative Analysis of Number of Alive
Nodes
Figure 3. Comparative Analysis of Throughput
The outcome shows that proposed system offers significantly increased retention of alive nodes with
50% improvement as considered too conventional LEACH algorithm whereas it also ensures a smooth
gradient ascent for throughput curve showing better predictability of the throughput performance whereas the
curve of LEACH witness 100% of node death just before even completing 50% of the simulation iteration.
At the same time, proposed system doesn't have any form of storage dependencies, and hence its
computational complexity is highly negligible.
4. CONCLUSION
At present, there are various research-based techniques focused on implementing PSO for solving
multiple problems in a wireless sensor network that comes under the ranges of clustering, energy conservation,
and localization. Although existing PSO-based techniques have made some good problems in obtaining the
better outcome, we find that such solutions have overlooked the problems associated with the computational
complexity in PSO due to its higher involvement of iteration. The proposed system proved that it is quite
feasible to control the iteration of PSO and still obtain better energy efficiency and enhanced data delivery
performance in a wireless sensor network in comparison to the existing system.
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BIOGRAPHIES OF AUTHORS
Hemavathi P obtained B.E from Manipal Institute of Technology, Manipal (University of MAHE),
India. She completed M.Tech from Dr. Ambedkar Institute of Technology Bangalore, (VTU) India.
Her areas of interest are Wireless Sensor Networks, Adhoc Networks. Currently, she is pursuing Ph.D.
at Jain University, Bangalore.
Dr. Nandakumar A N obtained his B.Sc in 1972, BE degree in 1976 both from University of
Mysore, India, and Ph.D. from Berhanpur university in the year 2008 after getting M.Tech from
University Of Roorkee (present IIT ROORKEE) in the year 1990. He is working as Professor, New
Horizon College of Engineering in the Department of Computer science and engineering, Bangalore.
His research is in the field of Image processing, pattern recognition, internet of things and others. He
is a life member of ISTE.