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.
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.
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.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
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.
Energy-aware strategy for data forwarding in IoT ecosystem IJECEIAES
The Internet of Things (IoT) is looming technology rapidly attracting many industries and drawing research attention. Although the scale of IoT-applications is very large, the capabilities of the IoT-devices are limited, especially in terms of energy. However, various research works have been done to alleviate these shortcomings, but the schemes introduced in the literature are complex and difficult to implement in practical scenarios. Therefore, considering the energy consumption of heterogeneous nodes in IoT eco-system, a simple energy-efficient routing technique is proposed. The proposed system has also employed an SDN controller that acts as a centralized manager to control and monitor network services, there by restricting the access of selfish nodes to the network. The proposed system constructs an analytical algorithm that provides reliable data transmission operations and controls energy consumption using a strategic mechanism where the path selection process is performed based on the remaining energy of adjacent nodes located in the direction of the destination node. The proposed energy-efficient data forwarding mechanism is compared with the existing AODV routing technique. The simulation result demonstrates that the protocol is superior to AODV in terms of packet delivery rate, throughput, and end-to-end delay.
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.
A simplified optimization for resource management in cognitive radio network-...IJECEIAES
With increasing evolution of applications and services in internet-of-things (IoT), there is an increasing concern of offering superior quality of service to its ever-increasing user base. This demand can be fulfilled by harnessing the potential of cognitive radio network (CRN) where better accessibility of services and resources can be achieved. However, existing review of literature shows that there are still open-end issues in this regard and hence, the proposed system offers a solution to address this problem. This paper presents a model which is capable of performing an optimization of resources when CRN is integrated in IoT using five generation (5G) network. The implementation uses analytical modeling to frame up the process of topology construction for IoT and optimizing the resources by introducing a simplified data transmission mechanism in IoT environment. The study outcome shows proposed system to excel better performance with respect to throughput and response time in comparison to existing schemes.
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.
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.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
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.
Energy-aware strategy for data forwarding in IoT ecosystem IJECEIAES
The Internet of Things (IoT) is looming technology rapidly attracting many industries and drawing research attention. Although the scale of IoT-applications is very large, the capabilities of the IoT-devices are limited, especially in terms of energy. However, various research works have been done to alleviate these shortcomings, but the schemes introduced in the literature are complex and difficult to implement in practical scenarios. Therefore, considering the energy consumption of heterogeneous nodes in IoT eco-system, a simple energy-efficient routing technique is proposed. The proposed system has also employed an SDN controller that acts as a centralized manager to control and monitor network services, there by restricting the access of selfish nodes to the network. The proposed system constructs an analytical algorithm that provides reliable data transmission operations and controls energy consumption using a strategic mechanism where the path selection process is performed based on the remaining energy of adjacent nodes located in the direction of the destination node. The proposed energy-efficient data forwarding mechanism is compared with the existing AODV routing technique. The simulation result demonstrates that the protocol is superior to AODV in terms of packet delivery rate, throughput, and end-to-end delay.
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.
A simplified optimization for resource management in cognitive radio network-...IJECEIAES
With increasing evolution of applications and services in internet-of-things (IoT), there is an increasing concern of offering superior quality of service to its ever-increasing user base. This demand can be fulfilled by harnessing the potential of cognitive radio network (CRN) where better accessibility of services and resources can be achieved. However, existing review of literature shows that there are still open-end issues in this regard and hence, the proposed system offers a solution to address this problem. This paper presents a model which is capable of performing an optimization of resources when CRN is integrated in IoT using five generation (5G) network. The implementation uses analytical modeling to frame up the process of topology construction for IoT and optimizing the resources by introducing a simplified data transmission mechanism in IoT environment. The study outcome shows proposed system to excel better performance with respect to throughput and response time in comparison to existing schemes.
Communication Cost Reduction by Data Aggregation: A SurveyIJMTST Journal
Wireless Sensor Networks have gained wide popularity in the recent years for its high-ranking applications such as remote environment monitoring, target tracking, safety-critical monitoring etc. However Wireless Sensor Networks face many constraints like low computational power, small storage, and limited energy resources. One of the important issues in wireless sensor network is to increase the network lifetime to keep the network operational as long as possible. In this survey paper, we provide a comprehensive review of the existing literature on techniques and protocols for data aggregation to reduce communication cost and increase network lifetime in wireless sensor networks.
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.
Optimal Coverage Path Planningin a Wireless Sensor Network for Intelligent Tr...IJCNCJournal
With the enhancement of the intelligent and communication technology, an intelligent transportation plays a vital role to facilitate an essential service to many people, allowing them to travel quickly and conveniently from place to place. Wireless sensor networks (WSNs) are well-known for their ability to detect physical significant barriers due to their diverse movement, self-organizing capabilities, and the integration of this mobile node on the intelligent transportation system to gather data in WSN contexts is becoming more and more popular as these vehicles proliferate. Although these mobile devices might enhance network performance, however it is difficult to design a suitable transportation path with the limited energy resources with network connectivity. To solve this problem, we have proposed a novel itinerary planning schema data gatherer (IPS-DG) model. Furthermore, we use the path planning module (PPM) which finds the transportation path to travel the shortest distance. We have compared our results under different aspect such as life span, energy consumption, and path length with Low Energy Adaptive Clustering Hierarchy (LEACH), Multi-Hop Weighted Revenue (MWR), Single-Hop Data Gathering Procedure (SHDGP). Our model outperforms in terms of energy usage, shortest path, and longest life span of with LEACH, MWR, SHDGP routing protocols.
Optimal Coverage Path Planning in a Wireless Sensor Network for Intelligent T...IJCNCJournal
With the enhancement of the intelligent and communication technology, an intelligent transportation plays a vital role to facilitate an essential service to many people, allowing them to travel quickly and conveniently from place to place. Wireless sensor networks (WSNs) are well-known for their ability to detect physical significant barriers due to their diverse movement, self-organizing capabilities, and the integration of this mobile node on the intelligent transportation system to gather data in WSN contexts is becoming more and more popular as these vehicles proliferate. Although these mobile devices might enhance network performance, however it is difficult to design a suitable transportation path with the limited energy resources with network connectivity. To solve this problem, we have proposed a novel itinerary planning schema data gatherer (IPS-DG) model. Furthermore, we use the path planning module (PPM) which finds the transportation path to travel the shortest distance. We have compared our results under different aspect such as life span, energy consumption, and path length with Low Energy Adaptive Clustering Hierarchy (LEACH), Multi-Hop Weighted Revenue (MWR), Single-Hop Data Gathering Procedure (SHDGP). Our model outperforms in terms of energy usage, shortest path, and longest life span of with LEACH, MWR, SHDGP routing protocols.
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.
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.
Resource optimization-based network selection model for heterogeneous wireles...IAESIJAI
The internet of things (IoT) environment prerequisite seamless connectivity for meeting real-time application requirements; thus, required efficient resource management techniques. Heterogeneous wireless networks (HWNs) have been emphasized for providing seamless connectivity with high quality of service (QoS) performance to provision IoT applications. However, the existing resource allocation scheme suffers from interference and fails to provide a quality experience for low-priority users. As a result, induce bandwidth wastage and increase handover failure. In addressing the research issues this paper presented the resource-optimized network selection (RONS) method for HWNs. The RONS method employs better load balancing to reduce handover failure and maximizes resource utilization through dynamic slot optimization. The RONS method assures tradeoffs between high performance to high priority users and quality of experience (QoE) for low priority users. The experiment outcome shows the RONS achieves very good performance in terms of throughput, packet loss, and handover failures in comparison with existing resource selection methods.
Optimized Energy Management Model on Data Distributing Framework of Wireless ...Venu Madhav
Data Dissemination is an essential transmitting method for a sensor network to the endusers
across any set of interconnected frameworks. WSN is often used within an IoT system,
in other words. As in a mesh network, a wide collection of sensors can collect data
individually and send data to the web via an IoT system through a router. The conventional
defined solution for data dissemination in Wireless Sensor Networks (WSN) does not
include the wide range of new applications built on the Internet of Things (IoT)systems.
Hence, it is observed that searching for an appropriate transmission link while distributing
data with optimized utilization of energy is a significant challenge in the IoT communication
infrastructure. Therefore, in this paper, an Optimized Energy Management Model for
Data Dissemination (OEM-DD) framework has been proposed to optimize energy during
data transmission efficiently across all sensor network nodes in the IoT system. The efficiency
of the data dissemination across an interconnected network has been achieved by
introducing a Non-adaptive routing approach in which data is distributed effectively from
a single source to various points. Besides, Non-adaptive routing involves the dispersed collaboration
system and the priority task planning principle combined with an integer framework
for the efficient energy processing and grouping of data in the sensor’s network. Optimization
of the energy management model through Non-adaptive routing allows low power
consumption and minimal energy usage for each sensor node in the IoT system to improve
the transfer and handling of data in severe interruption. The experimental results show that
the suggested model enhances the data transmission rate of 96.33%
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.
Performance evaluation of data filtering approach in wireless sensor networks...ijmnct
Wireless Sensor Network is a field of research which is viable in every application area like security
services, patient care, traffic regulations, habitat monitoring and so on. The resource limitation of small
sized tiny nodes has always been an issue in wireless sensor networks. Various techniques for improving
network lifetime have been proposed in the past. Now the attention has been shifted towards heterogeneous
networks rather than having homogeneous sensor nodes in a network. The concept of partial mobility has
also been suggested for network longevity. In all the major proposals; clustering and data aggregation in
heterogeneous networks has played an integral role. This paper contributes towards a new concept of
clustering and data filtering in wireless sensor networks. In this paper we have compared voronoi based
ant systems with standard LEACH-C algorithm and MTWSW with TWSW algorithm. Both the techniques
have been applied in heterogeneous wireless sensor networks. This approach is applicable both for critical
as well as for non-critical applications in wireless sensor networks. Both the approaches presented in this
paper outperform LEACH-C and TWSW in terms of energy efficiency and shows promising results for
future work.
Lifetime centric load balancing mechanism in wireless sensor network based Io...IJECEIAES
Wireless sensor network (WSN) is a vital form of the underlying technology of the internet of things (IoT); WSN comprises several energy-constrained sensor nodes to monitor various physical parameters. Moreover, due to the energy constraint, load balancing plays a vital role considering the wireless sensor network as battery power. Although several clustering algorithms have been proposed for providing energy efficiency, there are chances of uneven load balancing and this causes the reduction in network lifetime as there exists inequality within the network. These scenarios occur due to the short lifetime of the cluster head. These cluster head (CH) are prime responsible for all the activity as it is also responsible for intra-cluster and inter-cluster communications. In this research work, a mechanism named lifetime centric load balancing mechanism (LCLBM) is developed that focuses on CH-selection, network design, and optimal CH distribution. Furthermore, under LCLBM, assistant cluster head (ACH) for balancing the load is developed. LCLBM is evaluated by considering the important metrics, such as energy consumption, communication overhead, number of failed nodes, and one-way delay. Further, evaluation is carried out by comparing with ES-Leach method, through the comparative analysis it is observed that the proposed model outperforms the existing model.
Energy Efficient Techniques for Data aggregation and collection in WSNIJCSEA Journal
A multidisciplinary research area such as wireless sensor networks (WSN) have been invoked the monitoring of remote physical environment and are used for a wide range of applications ranging from defense personnel to many scientific research, statistical application, disaster area and War Zone. These networks are constraint with energy, memory and computing power enhance efficient techniques are needed for data aggregation, data collection, query processing, decision making and routing in sensor networks. The problem encountered in the recent past was of the more battery power consumption as activity increases, need more efficient data aggregation and collection techniques with right decision making capabilities. Therefore, this paper proposed the efficient and effective architecture and mechanism of energy efficient techniques for data aggregation and collection in WSN using principles like global weight calculation of nodes, data collection for cluster head and data aggregation techniques using data cube aggregation.
Data collection algorithm for wireless sensor networks using collaborative mo...IJECEIAES
The simplest approach to reduce network latency for data gathering in wireless sensor networks (WSN) is to use multiple mobile elements rather than a single mobile sink. However, the most challneging issues faced this approach are firstly the high network cost as a result of using large number of mobile elements. Secondly, it suffers from the difficulty of network partitioning to achieve an efficient load balancing among these mobile elements. In this study, a collaborative data collection algorithm (CDCA) is developed. Simulation results presented in this paper demonstrated that with this algorithm the latency is significantly reduced at small number of mobile elements. Furthermore, the performance of CDCA algorithm is compared with the Area Splitting Algorithm (ASA). Consequently, the CDCA showed superior performance in terms of network latency, load balancing, and the required number of mobile elements.
Energy efficient routing in wireless sensor network based on mobile sink guid...IJECEIAES
In wireless sensor networks (WSNs), the minimization of usage of energy in the sensor nodes is a key task. Three salient functions are performed by WSNs’ sensor nodes namely data sensing, transmitting and relaying. Routing technique is one of the methods to enhance the sensor nodes battery lifetime. Energy optimization is done by using one of the heuristic routing methods for data sensing and transmission. To enhance the energy optimization mainly concentrated on data relaying. In this work stochastic hill climbing is adapted. The proposed solution for data relaying utilizes geographical routing and mobile sink technique. The sink collects the data from cluster heads and movement of the sink is routed by stochastic hill climbing. Experimentation is done on the network simulator 2 Platform. The existing routing techniques like threshold sensitive energy efficient sensor network, energy-efficient low duty cycle, and adaptive clustering protocol are compared with the obtained results of chosen algorithm. The proposed work shows promising results with respect to lifetime, average energy of nodes and packet delivery ratio.
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
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
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.
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frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
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Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
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Energy-efficient data-aggregation for optimizing quality of service using mobile agents in wireless sensor network
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 12, No. 4, August 2022, pp. 3891~3899
ISSN: 2088-8708, DOI: 10.11591/ijece.v12i4.pp3891-3899 3891
Journal homepage: http://ijece.iaescore.com
Energy-efficient data-aggregation for optimizing quality of
service using mobile agents in wireless sensor network
Prapulla S. Basappa1
, Shobha Gangadhar1
, Tiptur Chandrashekar Thanuja2
1
Department of Computer Science and Engineering, R V College of Engineering, Bangalore, India
2
Department of Electronics and Communication Engineering Centre for PG Studies, Bangalore, India
Article Info ABSTRACT
Article history:
Received May 6, 2021
Revised Mar 19, 2022
Accepted Apr 2, 2022
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.
Keywords:
Data forwarding
Energy management
Mobile agent
Quality of service
Transmission
Wireless sensor network
This is an open access article under the CC BY-SA license.
Corresponding Author:
Prapulla S. Basappa
Department of Computer Science and Engineering, R V College of Engineering
Mysore Road, Bengaluru-560059, Karnataka, India
Email: prapullasb@rvce.edu.in
1. INTRODUCTION
Wireless sensor network (WSN) has contributed for the past two decades to facilitating
environmental sensing of physical attributes [1]. At present, various applications make use of cost-effective
sensors in carrying out different ranges of operation viz, environmental monitoring, habitat monitoring,
healthcare, oilfields, climatic condition monitoring, industrial monitoring, and many more, to name [2]. A
sensor node is a small embedded device capable of sensing data, processing it, and forwarding it to the next
destined node. However, it does this job by adhering to a structuring principle called clustering [3]. Various
clustering algorithms mainly target energy efficiency [4].
The definite group is formed during clustering, consisting of member nodes that sense the data and
forward it to the cluster head. In this process, the cluster head consumed maximum energy to transmit data,
thereby safeguarding the excessive energy consumption from other member nodes. A cluster head carries out
two essential operations, i.e., data fusion and data aggregation [5]. Data fusion is carried out to ensure the
collection of unique data from member nodes while data aggregation pertains to forwarding the fused data to
2. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 12, No. 4, August 2022: 3891-3899
3892
the base station or sink. The complete operation of clustering is also associated with the use of various ranges
of routing protocols. Existing studies exhibit three significant categories of routing protocol in WSN, i.e.,
geographical protocol, flat protocol, and hierarchical protocol [6]. Apart from this, there is another concept
where WSN uses the mobile agent to offer a balance between throughput and resource efficiency. The idea of
mobile agents is utilized for mobile computing for effective management and control of the network. Apart
from this, the complete data delivery process to sink solely depends upon the mobile agent, who also brings
various security concerns [7]. However, the biggest problem is to optimize data aggregation's performance
using a single mobile agent to meet specific quality of service demands. Therefore, the proposed system
presents a unique concept that implements transmission provision in WSN to increase maximum path
establishment among the sensors. This fact will significantly affect itinerary planning, where a mobile agent
can obtain maximum data with reduced energy and faster operation. The contribution/novelty of the proposed
system in contrast to the existing system are: i) a novel provisioning approach is introduced for a practical
resource utilization, ii) formulating dynamic routine management to study the impact of transmission of
concurrent use, and iii) dynamic power demand computation for transmittance.
The present manuscript's organization is as follows: section 1 briefs the existing approaches towards
using mobile agents and quality of service in WSN while investigating various techniques used, followed by
highlighting the encountered unaddressed issues from existing studies as well as it also briefs about the
proposed methodology. Briefing of the system design is carried out in section 2 while discussing the
outcomes of the simulation study is carried out in section 3. Finally, the summary of the paper is provided in
section 4.
There are various applications reported in existing approaches [7], which are associated with
potential advantages for introducing them in WSN, which is one of an integral part of internet of things
(IoT) [8]. The existing system has witnessed study associated with various application-specific models, e.g.,
sensory-based parking mechanism remotely [9], emergency evacuation system [10], Water monitoring [11],
fire detection using sensor and vast area network with low power [12], microcontroller-based air quality
monitoring [13]. Furthermore, various studies carried out towards securing sensors in WSN where the
discussion has been carried out towards the need for further improvement in the data aggregation process
[14]–[19]. Apart from this, various optimization approaches [20]–[22], as well as studies towards quality of
services [23], [24], have also been presented toward improving data transmission in WSN. The existing
system [25] reports incorporating the intelligence in the mobile agents in WSN to enhance its performance
towards autonomy, executability, and mobility. The investigation shows that such agents offer learning
capability that dynamically contributes towards path planning for controlling energy consumption. The study
outcome shows that multi-agent energy consumption is lower than single-agents over the increasing number
of source nodes. Study towards incorporating intelligence in multi-agents in WSN is also proven to be
successful by using game theory and reinforcement learning [26]. Yao and Jia [4] also carried out a similar
study's direction, where a multi-agent-based approach is used to address the jamming problem. This approach
makes use of a learning scheme where an error-free path is found. Usage of agent-based solutions is also
reported to help share resources in internet-of-things (IoT), as seen in Yildirim and Tatar's work [5]. Itinerary
planning is another essential focus of current research work. The idea is to minimize the duration of the task
by enhancing the throughput. Sasirekha and Swamynathan [27] have developed a clustering algorithm by
integrating hierarchical and energy-efficient approaches with lesser dependency on clusters to improve
energy efficiency.
The inclusion of a multi-mobile agent will always offer a better result in this perspective than a
single mobile agent. However, deploying a single mobile agent is always a cost-effective solution compared
to a multi-agent. Still, it is not suitable when deployed in monitoring areas with uncertain traffic and a
large-scale sense. Few studies considered adopting a single mobile agent to accomplish enhanced quality of
service performance in data aggregation of WSN. There are various temporal parameters, e.g., temporal
factors involved in exchanging beacons, data packets, and change of state of sensors. Until a mobile agent
does not get a highly updated feed of this information, the itinerary planning will never be optimized. For
high-end larger applications, a mobile agent could also drain out its energy if the itinerary planning is
ineffective and not supportive of a dynamic environment. To develop a better form of itinerary planning, it is
always better to reduce the number of time instances allocated for the explicit operation to be carried out
inactive and sleep mode. However, it is not feasible computationally, and hence, a better alternative solution
is required to solve this problem. Therefore, there is a need for a good balance between the communication
demand and computation demand while deploying mobile agents in WSN.
Novel analytical modeling is designed to offer maximum quality of service (QoS) in data
aggregation performance in WSN. The proposed system constructs a primary hypothesis that a single mobile
agent alone cannot perform higher QoS performance in large-scale deployment. The study's secondary idea is
that developing a distributed provisioning scheme for the sensor nodes to forward data could significantly
3. Int J Elec & Comp Eng ISSN: 2088-8708
Energy-efficient data-aggregation for optimizing quality of service … (Prapulla S. Basappa)
3893
assist in optimizing the mobile agent's itinerary planning. Proposed system's architecture is classified into
three main blocks, i.e., computational model, transmission provisioning, and energy model. The
constraint/limitation of the proposed system is that it offers energy improvement without considering
resource allocation used for security operation in WSN. To deploy it in a real-world application, the
initialized values of the sensory parameters (especially associated with the communication model) will be
required to be fine-tuned. Otherwise, it is replicable to all the scenarios. The communication model plays a
contributory role in the proposed system as it introduces routing management unlike any conventional studies
discussed above. The transmission provisioning operation is carried out over the communication model,
where finally, energy modeling ensures computation of demanded energy for data aggregation complying
with proposed routing management in WSN. The proposed concept's core idea is to provide higher path
establishment ranges among the sensors. This will let the mobile agent collect the maximum quantity of data
with lesser exploration towards the defined itinerary. This is made possible by developing a novel routine
that is a defined set of instantaneous operational times for the sensor to perform data transactions. The
proposed model also contributes to developing an effective scheduling policy that allows specific nodes to
perform data exchange while other nodes are maintained in radio-silence mode. An elaborate discussion of
the operation involved in the proposed study is discussed in the next section.
2. PROPOSED METHOD
The proposed system discusses the use of mobile agents to provide extensive QoS performance in
WSN. This section elaborates on the communication model, the role of mobile agents, and energy modelling in
order to provide better QoS support in large-scale WSN implementation. The communication model has two
routines: primary and secondary; the primary routine uses random access, while the secondary routine uses
provisioned access. The transmission for the mobile agent is carried out by the sensor nodes after a series of
operations such as initial route discovery stage, allocation of general routine, and switching to dynamic states. In
order to control energy consumption, the energy model has the capability to fine-tune energy demands.
2.1. Communication model
Figure 1 highlights the steps of the algorithm with steps number for communication establishment.
First, the algorithm takes n (total sensors) input, which will yield p (path establishment) after processing.
Second, the algorithm considers all the sensor nodes n (Line-1). Finally, the algorithm performs a random
deployment of the nodes n, which leads to random positioning of the nodes, i.e. (x, y) (Line-2).Then, the study
performs a pairwise distance between all the sensors to be forwarding the aggregated data to the base station.
First, a specific range of higher and lower bounds of communication range is considered, followed by
performing routing. For this purpose, the proposed system develops a connection matrix Cmat (Line-5), which
should be within the limits of higher and lower communication range cost of transmission (COT) (Line-4).
Then, a Euclidean distance is applied in function f1 (x) that computes the distance between sensor node (SN) and
base station (BS) (Line-3). If this distance d is found within the COT (Line-4), the proposed system updates its
connection matrix Cmat (Line-5). Finally, the proposed method applies another function, f2(x), for obtaining the
shortest path distance between the sensor nodes and base station (Line-7). The variable XY represents a matrix
which stores all the connection between the typical sensors and base station. This function f2(x) is responsible
for computing the shortest path from multiple source sensors to the numerous destination sensor. Suppose a
mobile agent gets connected with sensors with a higher number of paths connected by this function f2(x). In that
case, the mobile agent will extract more information by traveling a smaller number of paths. The
communication model includes a general routine for all the sensors, further classified into a primary and
secondary routine.
In the primary routine, the sensors initiate data communication (transmit and receive), while the
secondary routine allows the sensor to maintain radio silence. The proposed system also considers another
parameter, i.e., Critical Message Priority, which is the primary to secondary routine for each sensor. It helps
formulate decisions for the mobile node to schedule its itinerary planning towards reaching a specific set of
sensors.
The model also considers a dedicated routine where a communication channel is established between
source and destination node via a relay node. To compensate for the delay during the itinerary planning for the
mobile agents, the proposed system also adopts a delay-compensation scheme where the data packet is
represented concerning their significance. By adding a minimum bit (1-5 bit) flag message, the user can
highlight the packet's significance. The source sensor only assigns the degree of importance of the data packet.
The complete communication duration of WSN is carried out based on fixed routines.
4. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 12, No. 4, August 2022: 3891-3899
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Start
Random deployment
of nodes
Compute distance If d>COT
Update
connection matrix
Compute shortest
path
Stop
Y
N
Figure 1. Algorithm and flowchart for communication establishment
2.2. Provisioning transmission for mobile agent
The provisioning of the mobile agent transmission is carried out considering series of operations by the
sensor nodes.
− Initial route discovery stage: The sensor nodes broadcast the request message route request (RREQ) and
wait till its timeout session. After the timeout session, the sensor selects a general routine schedule and
forwards a coordinated packet (CPKT). This packet consists of information about the duration till the
system initializes the next generation of routine. The schedule received is followed by the sensor using the
CPKT while it obtains CPKT from a different sensor. This operation is followed up by forwarding its
CPKT data of its own. If the sensor possesses the schedule, the CPKT data is still heard from different
sensors with a different schedule.
− Allocation of general routine: The proposed study considers that every general routine of the sensor
consists of a uniform size of the duration of coordinated packet CPKT. The study also considers a
uniform size of data and radio silence duration in secondary routine. This is entirely dependent upon the
critical message priority (CMP) score. The study considers the CMP selection in a specific manner
where there is a higher duration of radio silence is considered to facilitate forwarding the data and
conformity message (CNFM). All the sensors are permitted to carry out the data transmission over any
generalized routine except the node with prioritized data. Nodes with increased prioritized data will be
offered higher importance compared to medium and low priority. However, in the absence of any data
packet for any instance of time, the user of the data and the general routine will get the privilege to
reconfigure the priority scale. Every sensor will also compute its dedicated routine based on its available
size of memory, latency, and network load.
− Switching to the dynamic states: It is now known that the proposed system calls for radio silence during the
activation of the routine secondary state. In the secondary routine, the sensor initiates the sensor's logical
clock with a priory configured duration as per the critical message priority considering the dedicated
routine between two communicating sensors. The sensor switches its state to the primary routine by
switching off its prior state of secondary routine after the timer for the secondary routine is over. In this
stage (primary routine), the radio is switched on autonomously, and the sensor initiates reading the
incoming stream of data from its environment. In the absence of any traffic, the sensor reads the idle mode's
message. By idle mode, the sensor exchanges the control messages among themselves but does not transmit
any data along with it. In the presence of any specific traffic, the sensor node opts for carrier sensing
multiple accesses to receive or transmit the data. The sensor node chooses the same radio channel with
multiple other concurrent sensors to carry out transmission and receiving states in the primary routine.
Once the timer is expired, it instantly switches to a secondary routine. If any sensor node is unsuccessful in
coordinating with another node to use the same communication channel, they switch to a secondary routine.
It should be noted that complete operation is carried out considering system active time, a uniform duration
for transmitting the data packet. It will mean that all the forwarding sensors must perform their transmission
after a specific duration of time. This makes the data transmission model quite deterministic for the
construction of the itinerary planning for mobile agents. Furthermore, the proposed system considers an
input of the critical message priority CMP and the size of the general routine route. Figure 2 highlights the
algorithm with respective step numbers and its process flow towards transmission provisioning. A
simplified mathematical expression is used for this purpose as in (1).
𝑇𝑝𝑟𝑖𝑚 = 𝐶𝑀𝑃 ∗ 𝑟𝑜𝑢𝑡
𝑇𝑠𝑒𝑐 = (1 − 𝐶𝑀𝑃) ∗ 𝑟𝑜𝑢𝑡 (1)
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Energy-efficient data-aggregation for optimizing quality of service … (Prapulla S. Basappa)
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Expression (1) is used for computing time for primary and secondary routine, i.e., Tprim and Tsec,
respectively. The algorithm considers all the sensor n (Line-1). The algorithm then considers computing the
beacon arrival time bat by applying a function f3(x), which uses a method g applied over the random index Rid
and several routines Nrout (Line-2). The method g is used for rounding the values owing to the inclusion of
random numbers. The following process is to apply the similar function f1(x) for Euclidean distance d1 between
the specific sensor node SNx,y, and node present in next-hop nhop (Line-4). The proposed system also has an
explicit energy modeling motivated by Ghasempour and Gunther's work [8]. The proposed algorithm then
computes the transmittance energy ETX, where a function f3(x) is used using the proposed energy model. This
function f3(x) offers the computation (2).
𝐸 = 𝐸𝑇𝑋 ∗ 𝑝𝑙𝑒𝑛 + 𝐸𝑎𝑚𝑝 ∗ 𝑝𝑙𝑒𝑛 ∗ 𝑑1
4
for d1>do
𝐸 = 𝐸𝑇𝑋 ∗ 𝑝𝑙𝑒𝑛 + 𝐸𝑓𝑠 ∗ 𝑝𝑙𝑒𝑛 ∗ 𝑑1
2
for d1<do (2)
The expression (2) is inspired by the standard computation of transmittance energy from the first order
radio energy model. According to this standard, the system computes transmittance energy based on two
conditions of distance. If the distance d1, which is recently computed, is more than a cut-off distance, then the
first expression of (2) is used, or else it uses the second expression. The computation of total energy E is
calculated by considering the standard value of transmittance energy ETX, length of packet plen, amplification
energy Eamp, and energy used for radio antenna resource Efs. Hence, this function f3(x) is used for adjusting the
transmittance energy in Line-5 of the algorithm. The next part of the algorithm considers all the number of
general routine Nrout(Line-6).Considering all the group ngrp (Line-7), the algorithm creates a message flag Mf
associated with the respective cluster-id Cid to identify the data's origination point (Line-8). The proposed
system considers different priority scales pscale of data to allocate the dynamic memory mem accordingly
considering the message's size (Line-9). Finally, the algorithm based on memory allocated with respective
priority scales initiates in the forwarding data packet (Line-10).
Start
Compute beacon
arrival time
Compute distance
Compute
Transmittance
energy
Message
prioritization
Forward
data
Start
Figure 2. Algorithm and flowchart for transmission provisioning
2.3. Energy modeling
Unlike any existing energy efficiency approach, the proposed system can fine-tune energy demands to
control energy consumption. According to this logic, the proposed method uses maximum energy Emax to
broadcast route request (RREQ) and route reply (RREP) control messages. Upon receiving an RREQ message,
the destination node forwards RREP with similar energy, i.e., Emax. The transmitting sensor computes the
demanded energy Edem after obtaining the RREP message based on the receiving energy level ERX. The
mathematical formulation of maximized energy is as (3),
Edem=E1 ∗ δ (3)
In the expression (3), the energy variable E1 will represent the ratio of maximized energy Emax to
receiving energy ERX. In contrast, the variable δ will represent the product of optimal signal strength and network
coefficient. The proposed system computes the demanded energy Edem to forward the data packet to the next
node or sink. The energy level is computed for the destination node when it receives RREQ using signal
strength to transmit a CNFM. The study considers that both transmit and receive sensors possess a similar range
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of signal attenuation to ease energy computation. It is to be noted that the proposed system permits the
forwarding of a data packet between a single pair of communicating sensors corresponding to the primary
routine, with all the adjacent sensors being in radio-silence mode to conserve energy.
3. METHOD
WSN network architecture is modeled as a disjoint set of graph (G,v). The proposed algorithm
constructs a mathematical model to find overlapping region for scalable sensor nodes deployment in such a
way that the trade-off problem of balancing energy consumption and QoS is solved. This is NP-complete
problem which is solved using cross layer design approach of communication protocol considering network
and physical layer parameters. Energy is optimized by balancing placement of sensors and sink node in such
a way that it achieves centrality and avoids packet losses by minimizing collision with the help of effective
scheduling.
4. RESULTS AND DISCUSSION
4.1. Simulation environment
The proposed logic is scripted in MATLAB considering 100-500 sensors randomly deployed in
1100x1200 m2
. The study considers all the sensors to be in a static position with the condition that each sensor
should have at least three neighboring nodes to facilitate edge connectivity. The base station can be positioned
at any position of the simulation area; however, it is the position in the middle of the simulation area for
effective analysis. The simulation parameters are i) priority message: 20%, ii) size of message: 10 bits,
iii) initial energy: 0.5 Joule, iv) length of routine 1 second, v) receiving energy: 25 nj/bits, vi) beacon arrival
time: 1-10, vii) length of the data packet: 200 bytes, viii) channel capacity:10 kbps, ix) Transmittance energy:
50 nj/bits, and x) simulation time: 100 seconds.
4.2. Results accomplished
Figure 3 highlights the comparative analysis of delay as a performance parameter where it can be seen
that the proposed system offers better delay performance in contrast to the existing system. The proposed
method uses a concurrent transmission approach that ensures faster dissemination of the data packets. Apart
from this, the proposed provisioning scheme is used for controlling the signals while performing data
forwarding. The outcome is obtained by considering 5% of the prioritized traffic in the complete network. With a
low rate of beacon arrival time, the data packet generation could be very high, but it does not affect the quantity of
prioritized traffic. The proposed agent-based approach offers seamless data transmission to the prioritized traffic
by facilitating concurrent data transmission to speed up the rate in contrast to low-prioritized traffic. Hence, delay
performance is significantly controlled. The usual traffic never gets affected owing to the presence of prioritized
traffic. Unfortunately, this operation is not carried out by the existing approach causing an increase in delay. This is
also the reason for energy demands that is exhibited in Figure 4 for energy required per bit.
Figure 3. Delay performance Figure 4. Energy required per bit
Figures 5 and 6 highlight the analysis of remnant energy and processing time, respectively. A closer
look into the energy trends in Figure 5 shows that it is better than intra/inters scheduling. The prime justification
behind this is that intra/inter-node scheduling emphasizes the clustering approach. Thus, the maximum focus is
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on selecting a cluster head that consumes maximum energy in the high-priority data packet. Although the
medium access protocol offers good retention of energy, due to its excessive duty cycle and slot management
usage, the performance is degraded compared to the proposed system. Figure 6 highlights the comparative
analysis of algorithm processing time where it can be seen that the proposed agent-based protocol needs
0.5 seconds in the Core i7 processor. In comparison, intra/inter scheduling approaches consume 1 second, and
medium access protocol consumes approximately 2.5 seconds. Furthermore, it should be noted that the
proposed system offers a simplified provisioning approach where less emphasis is given to cluster formation
and more priority is given to transmission provisioning and allocation of routines. Apart from this, the routine's
content consists of primary and secondary routines that can effectively control the complete traffic management
dealing with all prioritized data levels.
Hence, the proposed system does not need much algorithm processing time. On the other hand,
existing approaches consume maximum iterative steps to carry out slot management and resource allocation
and clustering, demanding higher processing capability and consuming time. Because of this reason, a mobile
agent planning for trip itinerary consumes more time and resources, which cumulatively affect network
lifetime too. Hence, the proposed system is considered to offer better QoS performance using mobile agents.
s
Figure 5. Analysis of residual energy Figure 6. Algorithm processing time
5. CONCLUSION
This paper discusses a novel energy efficiency approach in WSN where a single mobile agent is
assumed. The idea of the proposed study is to optimize the energy-efficient data aggregation considering a
single mobile agent. The contributions of the proposed study are as follows: i) the proposed model introduces
novel provisioning of transmission to ensure a higher degree of utilization of resources, ii) the proposed
system offers a scope to explore the consequences of concurrent transmission by forwarding a data packet
using a dynamic routine management scheme, iii) unlike any existing system, the proposed system does not
allocate static transmission power, but it computes the power which can be fine-tuned and then allocate it for
transmittance purpose. The proposed system's simulation outcome showcases that the proposed agent-based
protocol significantly benefits delay and energy efficiency compared to existing schemes. The future
direction of studies will be further optimizing the scheduling process using a cost-effective approach. A novel
analytical model could be constructed with more inclusion of constraints towards achieving energy-efficient
data transmission. The idea is to achieve cost-effective scheduling using an optimized scheduling scheme.
The potential findings that can be expected will reduce the algorithm processing time and more conservation
of residual energy in dense traffic conditions.
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BIOGRAPHIES OF AUTHORS
Prapulla S. Basappa working as Assistant Professor in Dept. of CSE, R V
College of Engineering, Bengaluru with around 14 years of teaching experience. She has a
Bachelors and Masters’ degree in Computer Science and Engineering, and She is currently
pursuing a Ph.D. Her research interest is in networking. She has published several papers in
international journals and conferences. Email: prapullasb@rvce.edu.in.
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Shobha Gangadhar working as a Professor in Dept. of Computer Science and
Engineering, R V College of Engineering, Bengaluru, with 25 years of teaching and 14 years
of Research experience. Her area of research interest includes Data Mining, Image Processing,
and Networking. She has published more than 150 research papers in International journals
and conferences. Email: shobhag@rvce.edu.in.
Tiptur Chandrashekar Thanuja is working as professor and chairperson, Dept.
Of Electronics and Communication Engineering, Visvesvaraya Technological university,
Belagavi, with 25 years of teaching experience. Researching VLSI for communication,
embedded systems for automotive, and Software Defined Radio. She has published more than
50 research papers in national and international journals and conferences. Email:
tc.thanuja@gmail.com.