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.
Data Centric Approach Based Protocol using Evolutionary Approach in WSNijsrd.com
The evolution of wireless communication and circuit technology has enabled the development of an infrastructure consists of sensing, computation and communication units that makes administrator capable to observe and react to a phenomena in a particular environment. In a Wireless Sensor Network (WSN), nodes are scattered densely in a large area. Sensor nodes can communicate with the sink node directly or through other nodes. Data transmission is the major issue in WSN. Each node has limited energy which is used in transmitting and receiving the data. Various routing protocols have been proposed to save the energy during the transmission of data. data centric approach based routing protocol which efficiently propagates information between sensor nodes in an energy constrained mode. This paper proposes a data centric routing Using evolutionary apporoach in WSN.The main objective of this protocol with evolutionary apporoach is to use artificial intelligence, to reduce the energy consumption by the nodes in transmitting and receiving the data. Implementation of Basic SEP, intelligence cluster routing and proposed protocols will be done using MATLAB.
Every cluster comprise of a leader which is known as cluster head. The cluster head will be chosen by the sensor nodes in the individual cluster or be pre-assigned by the user. The main advantages of clustering are the transmission of aggregated data to the base station, offers scalability for huge number of nodes and trims down energy consumption. Fundamentally, clustering could be classified into centralized clustering, distributed clustering and hybrid clustering. In centralized clustering, the cluster head is fixed. The rest of the nodes in the cluster act as member nodes. In distributed clustering, the cluster head is not fixed. The cluster head keeps on shifting form node to node within the cluster on the basis of some parameters. Hybrid clustering is the combination of both centralized clustering and distributed clustering mechanisms. This paper gives a brief overview on clustering process in wireless sensor networks. A research on the well evaluated distributed clustering algorithm Low Energy Adaptive Clustering Hierarchy (LEACH) and its followers are portrayed artistically. To overcome the drawbacks of these existing algorithms a hybrid distributed clustering model has been proposed for attaining energy efficiency to a larger scale.
Modified ccef for energy efficiency and extended network lifetime in wsnsijujournal
The widespread application of wireless sensor networks (WNSs) is obstructed by the severely limited energy constraints and security threat for sensor nodes. Since traditional routing and security schemes are not suited for these networks, a large part of research focusses on energy efficient routing protocols while extending the network lifetime. Uneven distribution of communication loads result in network partitioning.
Traditional novel en-route filtering approaches, notably commutative cipher based en-route filtering (CCEF) saves energy by early filtering of false reports. However this approach main focus is security not network lifetime is limited by fixed paths and underlying routing not suitable for WSNs. In order to cater these problems we propose energy efficient routing and pre-deterministic key distribution with dynamic path selection in CCEF. Modified CCEF (MCCEF) aims at saving energy and extending network lifetime while maintaining filtering power as in CCEF. Experimental results demonstrate the validity of our
approach with an average of three times network lifetime extension, 5.022% energy savings, and similar filtering power as the original scheme
E FFICIENT E NERGY U TILIZATION P ATH A LGORITHM I N W IRELESS S ENSOR...IJCI JOURNAL
With limited amount of energy, nodes are powered by
batteries in wireless networks. Increasing the lif
e
span of the network and reducing the usage of energ
y are two severe problems in Wireless Sensor
Networks. A small number of energy utilization path
algorithms like minimum spanning tree reduces tota
l
energy consumption of a Wireless Sensor Network, ho
wever very heavy load of sending data packets on
many key nodes is used with the intention that the
nodes quickly consumes battery energy, by raising t
he
life span of the network reduced. Our proposal work
aimed on presenting an Energy Conserved Fast and
Secure Data Aggregation Scheme for WSN in time and
security logic occurrence data collection
application. To begin with, initially the goal is m
ade on energy preservation of sensed data gathering
from
event identified sensor nodes to destination. Inven
tion is finished on Energy Efficient Utilization Pa
th
Algorithm (EEUPA), to extend the lifespan by proces
sing the collecting series with path mediators
depending on gene characteristics sequencing of nod
e energy drain rate, energy consumption rate, and
message overhead together with extended network lif
e span. Additionally, a mathematical programming
technique is designed to improve the lifespan of th
e network. Simulation experiments carried out among
different relating conditions of wireless sensor ne
twork by different path algorithms to analyze the
efficiency and effectiveness of planned Efficient E
nergy Utilization Path Algorithm in wireless sensor
network (EEUPA)
A Cooperative Cache Management Scheme for IEEE802.15.4 based Wireless Sensor ...IJECEIAES
Wireless Sensor Networks (WSNs) based on the IEEE 802.15.4 MAC and PHY layer standards is a recent trend in the market. It has gained tremendous attention due to its low energy consumption characteristics and low data rates. However, for larger networks minimizing energy consumption is still an issue because of the dissemination of large overheads throughout the network. This consumption of energy can be reduced by incorporating a novel cooperative caching scheme to minimize overheads and to serve data with minimal latency and thereby reduce the energy consumption. This paper explores the possibilities to enhance the energy efficiency by incorporating a cooperative caching strategy.
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
A COST EFFECTIVE COMPRESSIVE DATA AGGREGATION TECHNIQUE FOR WIRELESS SENSOR N...ijasuc
In wireless sensor network (WSN) there are two main problems in employing conventional compression
techniques. The compression performance depends on the organization of the routes for a larger extent.
The efficiency of an in-network data compression scheme is not solely determined by the compression
ratio, but also depends on the computational and communication overheads. In Compressive Data
Aggregation technique, data is gathered at some intermediate node where its size is reduced by applying
compression technique without losing any information of complete data. In our previous work, we have
developed an adaptive traffic aware aggregation technique in which the aggregation technique can be
changed into structured and structure-free adaptively, depending on the load status of the traffic. In this
paper, as an extension to our previous work, we provide a cost effective compressive data gathering
technique to enhance the traffic load, by using structured data aggregation scheme. We also design a
technique that effectively reduces the computation and communication costs involved in the compressive
data gathering process. The use of compressive data gathering process provides a compressed sensor
reading to reduce global data traffic and distributes energy consumption evenly to prolong the network
lifetime. By simulation results, we show that our proposed technique improves the delivery ratio while
reducing the energy and delay
Data Centric Approach Based Protocol using Evolutionary Approach in WSNijsrd.com
The evolution of wireless communication and circuit technology has enabled the development of an infrastructure consists of sensing, computation and communication units that makes administrator capable to observe and react to a phenomena in a particular environment. In a Wireless Sensor Network (WSN), nodes are scattered densely in a large area. Sensor nodes can communicate with the sink node directly or through other nodes. Data transmission is the major issue in WSN. Each node has limited energy which is used in transmitting and receiving the data. Various routing protocols have been proposed to save the energy during the transmission of data. data centric approach based routing protocol which efficiently propagates information between sensor nodes in an energy constrained mode. This paper proposes a data centric routing Using evolutionary apporoach in WSN.The main objective of this protocol with evolutionary apporoach is to use artificial intelligence, to reduce the energy consumption by the nodes in transmitting and receiving the data. Implementation of Basic SEP, intelligence cluster routing and proposed protocols will be done using MATLAB.
Every cluster comprise of a leader which is known as cluster head. The cluster head will be chosen by the sensor nodes in the individual cluster or be pre-assigned by the user. The main advantages of clustering are the transmission of aggregated data to the base station, offers scalability for huge number of nodes and trims down energy consumption. Fundamentally, clustering could be classified into centralized clustering, distributed clustering and hybrid clustering. In centralized clustering, the cluster head is fixed. The rest of the nodes in the cluster act as member nodes. In distributed clustering, the cluster head is not fixed. The cluster head keeps on shifting form node to node within the cluster on the basis of some parameters. Hybrid clustering is the combination of both centralized clustering and distributed clustering mechanisms. This paper gives a brief overview on clustering process in wireless sensor networks. A research on the well evaluated distributed clustering algorithm Low Energy Adaptive Clustering Hierarchy (LEACH) and its followers are portrayed artistically. To overcome the drawbacks of these existing algorithms a hybrid distributed clustering model has been proposed for attaining energy efficiency to a larger scale.
Modified ccef for energy efficiency and extended network lifetime in wsnsijujournal
The widespread application of wireless sensor networks (WNSs) is obstructed by the severely limited energy constraints and security threat for sensor nodes. Since traditional routing and security schemes are not suited for these networks, a large part of research focusses on energy efficient routing protocols while extending the network lifetime. Uneven distribution of communication loads result in network partitioning.
Traditional novel en-route filtering approaches, notably commutative cipher based en-route filtering (CCEF) saves energy by early filtering of false reports. However this approach main focus is security not network lifetime is limited by fixed paths and underlying routing not suitable for WSNs. In order to cater these problems we propose energy efficient routing and pre-deterministic key distribution with dynamic path selection in CCEF. Modified CCEF (MCCEF) aims at saving energy and extending network lifetime while maintaining filtering power as in CCEF. Experimental results demonstrate the validity of our
approach with an average of three times network lifetime extension, 5.022% energy savings, and similar filtering power as the original scheme
E FFICIENT E NERGY U TILIZATION P ATH A LGORITHM I N W IRELESS S ENSOR...IJCI JOURNAL
With limited amount of energy, nodes are powered by
batteries in wireless networks. Increasing the lif
e
span of the network and reducing the usage of energ
y are two severe problems in Wireless Sensor
Networks. A small number of energy utilization path
algorithms like minimum spanning tree reduces tota
l
energy consumption of a Wireless Sensor Network, ho
wever very heavy load of sending data packets on
many key nodes is used with the intention that the
nodes quickly consumes battery energy, by raising t
he
life span of the network reduced. Our proposal work
aimed on presenting an Energy Conserved Fast and
Secure Data Aggregation Scheme for WSN in time and
security logic occurrence data collection
application. To begin with, initially the goal is m
ade on energy preservation of sensed data gathering
from
event identified sensor nodes to destination. Inven
tion is finished on Energy Efficient Utilization Pa
th
Algorithm (EEUPA), to extend the lifespan by proces
sing the collecting series with path mediators
depending on gene characteristics sequencing of nod
e energy drain rate, energy consumption rate, and
message overhead together with extended network lif
e span. Additionally, a mathematical programming
technique is designed to improve the lifespan of th
e network. Simulation experiments carried out among
different relating conditions of wireless sensor ne
twork by different path algorithms to analyze the
efficiency and effectiveness of planned Efficient E
nergy Utilization Path Algorithm in wireless sensor
network (EEUPA)
A Cooperative Cache Management Scheme for IEEE802.15.4 based Wireless Sensor ...IJECEIAES
Wireless Sensor Networks (WSNs) based on the IEEE 802.15.4 MAC and PHY layer standards is a recent trend in the market. It has gained tremendous attention due to its low energy consumption characteristics and low data rates. However, for larger networks minimizing energy consumption is still an issue because of the dissemination of large overheads throughout the network. This consumption of energy can be reduced by incorporating a novel cooperative caching scheme to minimize overheads and to serve data with minimal latency and thereby reduce the energy consumption. This paper explores the possibilities to enhance the energy efficiency by incorporating a cooperative caching strategy.
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
A COST EFFECTIVE COMPRESSIVE DATA AGGREGATION TECHNIQUE FOR WIRELESS SENSOR N...ijasuc
In wireless sensor network (WSN) there are two main problems in employing conventional compression
techniques. The compression performance depends on the organization of the routes for a larger extent.
The efficiency of an in-network data compression scheme is not solely determined by the compression
ratio, but also depends on the computational and communication overheads. In Compressive Data
Aggregation technique, data is gathered at some intermediate node where its size is reduced by applying
compression technique without losing any information of complete data. In our previous work, we have
developed an adaptive traffic aware aggregation technique in which the aggregation technique can be
changed into structured and structure-free adaptively, depending on the load status of the traffic. In this
paper, as an extension to our previous work, we provide a cost effective compressive data gathering
technique to enhance the traffic load, by using structured data aggregation scheme. We also design a
technique that effectively reduces the computation and communication costs involved in the compressive
data gathering process. The use of compressive data gathering process provides a compressed sensor
reading to reduce global data traffic and distributes energy consumption evenly to prolong the network
lifetime. By simulation results, we show that our proposed technique improves the delivery ratio while
reducing the energy and delay
A Fast Convergence and Quick Route Updates Based Energy Aware Tree-Based Rout...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
MULTI-CLUSTER MULTI-CHANNEL SCHEDULING (MMS) ALGORITHM FOR MAXIMUM DATA COLLE...IJCNCJournal
Interference during data transmission can cause performance degradation like packet collisions in Wireless Sensor Networks (WSNs). While multi-channels available in IEEE 802.15.4 protocol standard WSN technology can be exploited to reduce interference, allocating channel and channel switching
algorithms can have a major impact on the performance of multi-channel communication. This paper presents an improved Fuzzy Logic based Cluster Formation and Cluster Head (CH) Selection algorithm with enhanced network lifetime for multi-cluster topology. The Multi-Cluster Multi-Channel Scheduling
(MMS) algorithm proposed in this paper improves the data collection by minimizing the maximum interference and collision. The presented work has developed Cluster formation and cluster head (CH) selection algorithm and Interference-free data communication by proper channel scheduled. The extensive
simulation and experimental outcomes prove that the proposed algorithm not only provides an interference-free transmission but also provides delay minimization and longevity of the network lifetime, which makes the presented algorithm suitable for energy-constrained wireless sensor networks.
Data aggregation in important issue in WSN’s. Because with the help of data aggregation; we are
reduce energy consumption in the network. In the Ad-hoc sensor network have the most challenging task
is to maintain a life time of the node. due to efficient data aggregation increase the life of the network. In
this paper, we are going to provide the information about the type of the network and which data
aggregation algorithm is best. In big scale sensor network, energy economical, data collection and query
distribution in most important.
Keywords — data aggregation; wireless sensor network
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
Sensor networks consist of randomly deployed nodes that are powered by smaller batteries. The quantum and quality of information sensed by these nodes is of vital importance. Battery saving techniques or algorithms are need of the hour. One such technique is clustering of the nodes. This paper presents modification to existing DEEHC algorithm that builds multiple vertex disjoint paths from nodes to base station via cluster heads. The proposed modification (MDEEHC) improves the performance of the network as equated to DEEHC and FLDEEC by relaying the data of the child cluster heads using relay nodes. MDEEHC shows improvement in terms of throughput, packet delivery ratio, number of packet drops and remaining energy. Pragati Dikshit | Rajveer Kaur Hyher | Goldendeep Kaur"An Improved DEEHC to Extend Lifetime of WSN" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018, URL: http://www.ijtsrd.com/papers/ijtsrd15905.pdf http://www.ijtsrd.com/engineering/computer-engineering/15905/an-improved-deehc-to-extend-lifetime-of-wsn/pragati-dikshit
Wireless sensor networks, clustering, Energy efficient protocols, Particles S...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality.
The most important issue in this type of networks is energy constraints. In this area several researches have
been done from which clustering is one of the most effective solutions. The goal of clustering is to divide
network into sections each of which has a cluster head (CH). The task of cluster heads collection, data
aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach
for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal
fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual
energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation
results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF,
PSO-MV) in terms of network lifetime and energy consumption.
AN OPTIMUM ENERGY CONSUMPTION HYBRID ALGORITHM FOR XLN STRATEGIC DESIGN IN WSN’SIJCNCJournal
In this paper, X-Layer protocol is originated which executes mobility error prediction (MEP) algorithm to calculate the remaining energy level of each node. This X-Layer protocol structure employs the mobility aware protocol that senses the mobility concerned to each node with the utilization of Ad-hoc On-Demand Distance Vector (AODV), which shares the information or data specific to the distance among individual nodes. With the help of this theory, the neighbour list will be updated only to those nodes which are mobile resulting in less energy consumption when compared to all (static/mobile) other nodes in the network. Apart from the MEP algorithm, clustering head (CH) election algorithm has also been specified to identify the relevant clusters whether they exists within the network region or not. Also clustering multi-hop routing (CMHR) algorithm was implemented in which the node can identify the cluster to which it belongs depending upon the distance from each cluster surrounding the node. Finally comprising the AODV routing protocol with the Two-Ray Ground method, we implement X-Layer protocol structure by considering MAC protocol in accordance to IEEE 802.15.4 to obtain the best results in energy consumption and also by reducing the energy wastage with respect to each node. The effective results had been illustrated through Network Simulator-II platform.
An Integrated Distributed Clustering Algorithm for Large Scale WSN...................................................1
S. R. Boselin Prabhu, S. Sophia, S. Arthi and K. Vetriselvi
An Efficient Connection between Statistical Software and Database Management System ................... 1
Sunghae Jun
Pragmatic Approach to Component Based Software Metrics Based on Static Methods ......................... 1
S. Sagayaraj and M. Poovizhi
SDI System with Scalable Filtering of XML Documents for Mobile Clients ............................................... 1
Yi Yi Myint and Hninn Aye Thant
An Easy yet Effective Method for Detecting Spatial Domain LSB Steganography .................................... 1
Minati Mishra and Flt. Lt. Dr. M. C. Adhikary
Minimizing the Time of Detection of Large (Probably) Prime Numbers ................................................... 1
Dragan Vidakovic, Dusko Parezanovic and Zoran Vucetic
Design of ATL Rules for TransformingUML 2 Sequence Diagrams into Petri Nets..................................... 1
Elkamel Merah, Nabil Messaoudi, Dalal Bardou and Allaoua Chaoui
GREEDY CLUSTER BASED ROUTING FOR WIRELESS SENSOR NETWORKSijcsit
In recent years, applications of wireless sensor networks have evolved in many areas such as target tracking, environmental monitoring, military and medical applications. Wireless sensor network continuously collect and send data through sensor nodes from a specific region to a base station. But, data redundancy due to neighbouring sensors consumes energy, compromising the network lifetime. In order to improve the network lifetime, a novel cluster based local route search method, called, Greedy Clusterbased Routing (GCR) technique in wireless sensor network. The proposed GCR method uses arbitrary timer in order to participate cluster head selection process with maximum neighbour nodes and minimum distance between the source and base station. GCR constructs dynamic routing improving the rate of network lifetime through Mass Proportion value. Also, GCR uses a greedy route finding strategy for
balancing energy consumption. Experimental results show that GCR achieves significant energy savings and prolong network lifetime.
A NODE DEPLOYMENT MODEL WITH VARIABLE TRANSMISSION DISTANCE FOR WIRELESS SENS...ijwmn
The deployment of network nodes is essential to ensure the wireless sensor network's regular operation and affects the multiple network performance metrics, such as connectivity, coverage, lifetime, and cost. This paper focuses on the problem of minimizing network costs while meeting network requirements, and proposes a corona-based deployment method by using the variable transmission distance sensor. Based on the analysis of node energy consumption and network cost, an optimization model to minimize Cost Per Unit Area is given. The transmission distances and initial energy of the sensors are obtained by solving the model. The optimization model is improved to ensure the energy consumption balance of nodes in the same corona. Based on these parameters, the process of network node deployment is given. Deploying the
network through this method will greatly reduce network costs.
SIMULATION BASED ANALYSIS OF CLUSTER-BASED PROTOCOL IN WIRELESS SENSOR NETWORKijngnjournal
The modern growth in fabricate energy efficient Wireless Sensor Network is liberal a novel way to
systematize WSN in applications like surveillance, industrial monitoring, traffic monitoring, habitat
monitoring, cropping monitoring, crowd including etc. The rising use of these networks is making
engineers evolve novel and efficient ideas in this field. A group of research in data routing, data density
and in network aggregation has been proposed in recent years. The energy consumption is the main
apprehension in the wireless sensor network. There are many protocols in wireless sensor network to
diminish the energy consumption and to put in to the network lifetime. Among a range of types of
techniques, clustering is the most efficient technique to diminish the energy expenditure of network. In
this effort, LEACH protocol has been second-hand for clustering in which cluster heads are nominated on
the basis of distance and energy. The LEACH protocol is been implemented in a simulated environment
and analyze their performance graphically.
Review on Clustering and Data Aggregation in Wireless Sensor NetworkEditor IJCATR
Wireless Sensor Network is a collection of various sensor nodes with sensing and communication capabilities. Clustering is the
process of grouping the set of objects so that the objects in the same group are similar to each other and different to objects in the other
group. The main goal of Data Aggregation is to collect and aggregate the data by maintaining the energy efficiency so that the network
lifetime can be increased. In this paper, I have presented a comprehensive review of various clustering routing protocols for WSN, their
advantages and limitation of clustering in WSN. A brief survey of Data Aggregation Algorithm is also outlined in this paper. Finally, I
summarize and conclude the paper with some future directions
Congestion Control Clustering a Review PaperEditor IJCATR
Wireless Sensor Networks consists of sensor nodes which are scattered in the environment, gather data and transmit it to a
base station for processing. Energy conservation in the Wireless Sensor Networks (WSN) is a very important task because of their
limited battery power. The related works so far have been done have tried to solve the problem keeping in the mind the constraints of
WSNs. In this paper, a priority based application specific congestion control clustering (PASCCC) protocol has been studied, which
often integrates the range of motion and heterogeneity of the nodes to detect congestion in a very network. Moreover a comparison of
the various clustering techniques has been done. From the survey it has been found that none of the protocol is efficient for energy
conservation. Hence the paper ends with future scope to overcome these issues.
This presentation is all about the wireless sensor networks, how they collect data using aggregation, and how they evaluate or calculate the parameters
A Fast Convergence and Quick Route Updates Based Energy Aware Tree-Based Rout...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
MULTI-CLUSTER MULTI-CHANNEL SCHEDULING (MMS) ALGORITHM FOR MAXIMUM DATA COLLE...IJCNCJournal
Interference during data transmission can cause performance degradation like packet collisions in Wireless Sensor Networks (WSNs). While multi-channels available in IEEE 802.15.4 protocol standard WSN technology can be exploited to reduce interference, allocating channel and channel switching
algorithms can have a major impact on the performance of multi-channel communication. This paper presents an improved Fuzzy Logic based Cluster Formation and Cluster Head (CH) Selection algorithm with enhanced network lifetime for multi-cluster topology. The Multi-Cluster Multi-Channel Scheduling
(MMS) algorithm proposed in this paper improves the data collection by minimizing the maximum interference and collision. The presented work has developed Cluster formation and cluster head (CH) selection algorithm and Interference-free data communication by proper channel scheduled. The extensive
simulation and experimental outcomes prove that the proposed algorithm not only provides an interference-free transmission but also provides delay minimization and longevity of the network lifetime, which makes the presented algorithm suitable for energy-constrained wireless sensor networks.
Data aggregation in important issue in WSN’s. Because with the help of data aggregation; we are
reduce energy consumption in the network. In the Ad-hoc sensor network have the most challenging task
is to maintain a life time of the node. due to efficient data aggregation increase the life of the network. In
this paper, we are going to provide the information about the type of the network and which data
aggregation algorithm is best. In big scale sensor network, energy economical, data collection and query
distribution in most important.
Keywords — data aggregation; wireless sensor network
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
Sensor networks consist of randomly deployed nodes that are powered by smaller batteries. The quantum and quality of information sensed by these nodes is of vital importance. Battery saving techniques or algorithms are need of the hour. One such technique is clustering of the nodes. This paper presents modification to existing DEEHC algorithm that builds multiple vertex disjoint paths from nodes to base station via cluster heads. The proposed modification (MDEEHC) improves the performance of the network as equated to DEEHC and FLDEEC by relaying the data of the child cluster heads using relay nodes. MDEEHC shows improvement in terms of throughput, packet delivery ratio, number of packet drops and remaining energy. Pragati Dikshit | Rajveer Kaur Hyher | Goldendeep Kaur"An Improved DEEHC to Extend Lifetime of WSN" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018, URL: http://www.ijtsrd.com/papers/ijtsrd15905.pdf http://www.ijtsrd.com/engineering/computer-engineering/15905/an-improved-deehc-to-extend-lifetime-of-wsn/pragati-dikshit
Wireless sensor networks, clustering, Energy efficient protocols, Particles S...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality.
The most important issue in this type of networks is energy constraints. In this area several researches have
been done from which clustering is one of the most effective solutions. The goal of clustering is to divide
network into sections each of which has a cluster head (CH). The task of cluster heads collection, data
aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach
for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal
fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual
energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation
results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF,
PSO-MV) in terms of network lifetime and energy consumption.
AN OPTIMUM ENERGY CONSUMPTION HYBRID ALGORITHM FOR XLN STRATEGIC DESIGN IN WSN’SIJCNCJournal
In this paper, X-Layer protocol is originated which executes mobility error prediction (MEP) algorithm to calculate the remaining energy level of each node. This X-Layer protocol structure employs the mobility aware protocol that senses the mobility concerned to each node with the utilization of Ad-hoc On-Demand Distance Vector (AODV), which shares the information or data specific to the distance among individual nodes. With the help of this theory, the neighbour list will be updated only to those nodes which are mobile resulting in less energy consumption when compared to all (static/mobile) other nodes in the network. Apart from the MEP algorithm, clustering head (CH) election algorithm has also been specified to identify the relevant clusters whether they exists within the network region or not. Also clustering multi-hop routing (CMHR) algorithm was implemented in which the node can identify the cluster to which it belongs depending upon the distance from each cluster surrounding the node. Finally comprising the AODV routing protocol with the Two-Ray Ground method, we implement X-Layer protocol structure by considering MAC protocol in accordance to IEEE 802.15.4 to obtain the best results in energy consumption and also by reducing the energy wastage with respect to each node. The effective results had been illustrated through Network Simulator-II platform.
An Integrated Distributed Clustering Algorithm for Large Scale WSN...................................................1
S. R. Boselin Prabhu, S. Sophia, S. Arthi and K. Vetriselvi
An Efficient Connection between Statistical Software and Database Management System ................... 1
Sunghae Jun
Pragmatic Approach to Component Based Software Metrics Based on Static Methods ......................... 1
S. Sagayaraj and M. Poovizhi
SDI System with Scalable Filtering of XML Documents for Mobile Clients ............................................... 1
Yi Yi Myint and Hninn Aye Thant
An Easy yet Effective Method for Detecting Spatial Domain LSB Steganography .................................... 1
Minati Mishra and Flt. Lt. Dr. M. C. Adhikary
Minimizing the Time of Detection of Large (Probably) Prime Numbers ................................................... 1
Dragan Vidakovic, Dusko Parezanovic and Zoran Vucetic
Design of ATL Rules for TransformingUML 2 Sequence Diagrams into Petri Nets..................................... 1
Elkamel Merah, Nabil Messaoudi, Dalal Bardou and Allaoua Chaoui
GREEDY CLUSTER BASED ROUTING FOR WIRELESS SENSOR NETWORKSijcsit
In recent years, applications of wireless sensor networks have evolved in many areas such as target tracking, environmental monitoring, military and medical applications. Wireless sensor network continuously collect and send data through sensor nodes from a specific region to a base station. But, data redundancy due to neighbouring sensors consumes energy, compromising the network lifetime. In order to improve the network lifetime, a novel cluster based local route search method, called, Greedy Clusterbased Routing (GCR) technique in wireless sensor network. The proposed GCR method uses arbitrary timer in order to participate cluster head selection process with maximum neighbour nodes and minimum distance between the source and base station. GCR constructs dynamic routing improving the rate of network lifetime through Mass Proportion value. Also, GCR uses a greedy route finding strategy for
balancing energy consumption. Experimental results show that GCR achieves significant energy savings and prolong network lifetime.
A NODE DEPLOYMENT MODEL WITH VARIABLE TRANSMISSION DISTANCE FOR WIRELESS SENS...ijwmn
The deployment of network nodes is essential to ensure the wireless sensor network's regular operation and affects the multiple network performance metrics, such as connectivity, coverage, lifetime, and cost. This paper focuses on the problem of minimizing network costs while meeting network requirements, and proposes a corona-based deployment method by using the variable transmission distance sensor. Based on the analysis of node energy consumption and network cost, an optimization model to minimize Cost Per Unit Area is given. The transmission distances and initial energy of the sensors are obtained by solving the model. The optimization model is improved to ensure the energy consumption balance of nodes in the same corona. Based on these parameters, the process of network node deployment is given. Deploying the
network through this method will greatly reduce network costs.
SIMULATION BASED ANALYSIS OF CLUSTER-BASED PROTOCOL IN WIRELESS SENSOR NETWORKijngnjournal
The modern growth in fabricate energy efficient Wireless Sensor Network is liberal a novel way to
systematize WSN in applications like surveillance, industrial monitoring, traffic monitoring, habitat
monitoring, cropping monitoring, crowd including etc. The rising use of these networks is making
engineers evolve novel and efficient ideas in this field. A group of research in data routing, data density
and in network aggregation has been proposed in recent years. The energy consumption is the main
apprehension in the wireless sensor network. There are many protocols in wireless sensor network to
diminish the energy consumption and to put in to the network lifetime. Among a range of types of
techniques, clustering is the most efficient technique to diminish the energy expenditure of network. In
this effort, LEACH protocol has been second-hand for clustering in which cluster heads are nominated on
the basis of distance and energy. The LEACH protocol is been implemented in a simulated environment
and analyze their performance graphically.
Review on Clustering and Data Aggregation in Wireless Sensor NetworkEditor IJCATR
Wireless Sensor Network is a collection of various sensor nodes with sensing and communication capabilities. Clustering is the
process of grouping the set of objects so that the objects in the same group are similar to each other and different to objects in the other
group. The main goal of Data Aggregation is to collect and aggregate the data by maintaining the energy efficiency so that the network
lifetime can be increased. In this paper, I have presented a comprehensive review of various clustering routing protocols for WSN, their
advantages and limitation of clustering in WSN. A brief survey of Data Aggregation Algorithm is also outlined in this paper. Finally, I
summarize and conclude the paper with some future directions
Congestion Control Clustering a Review PaperEditor IJCATR
Wireless Sensor Networks consists of sensor nodes which are scattered in the environment, gather data and transmit it to a
base station for processing. Energy conservation in the Wireless Sensor Networks (WSN) is a very important task because of their
limited battery power. The related works so far have been done have tried to solve the problem keeping in the mind the constraints of
WSNs. In this paper, a priority based application specific congestion control clustering (PASCCC) protocol has been studied, which
often integrates the range of motion and heterogeneity of the nodes to detect congestion in a very network. Moreover a comparison of
the various clustering techniques has been done. From the survey it has been found that none of the protocol is efficient for energy
conservation. Hence the paper ends with future scope to overcome these issues.
This presentation is all about the wireless sensor networks, how they collect data using aggregation, and how they evaluate or calculate the parameters
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Data gathering in wireless sensor networks using intermediate nodesIJCNCJournal
Energy consumption is an essential concern to Wireless Sensor Networks (WSNs).The major cause of the energy consumption in WSNs is due to the data aggregation. A data aggregation is a process of collecting data from sensor nodes and transmitting these data to the sink node or base station. An effective way to perform such a task is accomplished by using clustering. In clustering, nodes are grouped into clusters where a number of nodes, called cluster heads, are responsible for gathering data from other nodes, aggregate them and transmit them to the Base Station (BS).
In this paper we produce a new algorithm which focused on reducing the transmission bath between sensor nodes and cluster heads. A proper utilization and reserving of the available power resources is achieved with this technique compared to the well-known LEACH_C algorithm.
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.
Data Collection Method to Improve Energy Efficiency in Wireless Sensor NetworkKhushbooGupta145
Wireless Sensor Networks (WSNs) are generally self-organized wireless ad hoc networks which incorporate a huge number of sensor nodes which are resource constraint. Among the tasks of WSN, one most essential task is to collect the data
and transmits the gathered data to a distant base station (BS). The effectiveness of WSNs can be calculated in terms of network lifetime. Data collection is a frequent operation but analytical and critical operation in many WSN’s
application. To prolong network lifetime innovative technique that can improve
energy efficiency are highly required. This paper presents a survey for
designing Energy Efficient Data Collection Methods used for prolonging network lifetime in Wireless Sensor Network (WSN). The study highlights the importance of different Data conditions for various purposes like emergency response, medical monitoring, military applications, surveillance in volcanic or
remote regions, etc. Different Data Collection methods like data aggregation clusters, data aggregation trees, network coding, correlation dominating set etc. are considered in detail in this study. Furthermore, a comparison of different Data Collection Method based on the network lifetime, energy efficiency,
complexity of the algorithm, transmission cost and fusion cost is done.
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.
Multi Objective Salp Swarm based Energy Efficient Routing Protocol for Hetero...IJCNCJournal
Routing is a persistent concern in wireless sensor networks (WSNs), as getting data from sources to destinations can be a tricky task. Challenges include safeguarding the data being transferred, ensuring network longevity, and preserving energy in harsh environmental conditions. Consequently, this study delves into the suitability of using multi-objective swarm optimization to route heterogeneous WSNs in the hope of mitigating these issues while boosting the speed and accuracy of data transmission. In order to achieve better performance in terms of load balancing and reducing energy expenditure, the MOSSA-BA algorithm was developed. This algorithm combines the Multi-Objective Salp Swarm Algorithm (MOSSA) with the exploiting strategy of the artificial bee colony (BA) in the neighbourhood of Salps. Inspired by the SEP and EDEEC protocols, the integrated solutions of MOSSA-BA were used to route two and three levels of heterogeneous networks. The embedded solutions provided outstanding performance in regards to FND, HND, LND, percentage of remaining energy, and the number of packages delivered to the base station. Compared to SEP, EDEEC, and other competitors based on MOSSA and a modified multi-objective particle swarm optimization (MOPSO), the MOSSA-BA-based protocols demonstrated energy-saving percentages of more than 34% in medium-sized areas of interest and over 22% in large-sized areas of detection.
Multi Objective Salp Swarm based Energy Efficient Routing Protocol for Hetero...IJCNCJournal
Routing is a persistent concern in wireless sensor networks (WSNs), as getting data from sources to destinations can be a tricky task. Challenges include safeguarding the data being transferred, ensuring network longevity, and preserving energy in harsh environmental conditions. Consequently, this study delves into the suitability of using multi-objective swarm optimization to route heterogeneous WSNs in the hope of mitigating these issues while boosting the speed and accuracy of data transmission. In order to achieve better performance in terms of load balancing and reducing energy expenditure, the MOSSA-BA algorithm was developed. This algorithm combines the Multi-Objective Salp Swarm Algorithm (MOSSA) with the exploiting strategy of the artificial bee colony (BA) in the neighbourhood of Salps. Inspired by the SEP and EDEEC protocols, the integrated solutions of MOSSA-BA were used to route two and three levels of heterogeneous networks. The embedded solutions provided outstanding performance in regards to FND, HND, LND, percentage of remaining energy, and the number of packages delivered to the base station. Compared to SEP, EDEEC, and other competitors based on MOSSA and a modified multi-objective particle swarm optimization (MOPSO), the MOSSA-BA-based protocols demonstrated energy-saving percentages of more than 34% in medium-sized areas of interest and over 22% in large-sized areas of detection.
MODIFIED CCEF FOR ENERGY-EFFICIENCY AND EXTENDED NETWORK LIFETIME IN WSNSijujournal
The widespread application of wireless sensor networks (WNSs) is obstructed by the severely limited
energy constraints and security threat for sensor nodes. Since traditional routing and security schemes are
not suited for these networks, a large part of research focusses on energy efficient routing protocols while
extending the network lifetime. Uneven distribution of communication loads result in network partitioning.
Traditional novel en-route filtering approaches, notably commutative cipher based en-route filtering
(CCEF) saves energy by early filtering of false reports. However this approach main focus is security not
network lifetime is limited by fixed paths and underlying routing not suitable for WSNs. In order to cater
these problems we propose energy efficient routing and pre-deterministic key distribution with dynamic
path selection in CCEF. Modified CCEF (MCCEF) aims at saving energy and extending network lifetime
while maintaining filtering power as in CCEF. Experimental results demonstrate the validity of our
approach with an average of three times network lifetime extension, 5.022% energy savings, and similar
filtering power as the original scheme.
MODIFIED CCEF FOR ENERGY-EFFICIENCY AND EXTENDED NETWORK LIFETIME IN WSNSijujournal
The widespread application of wireless sensor networks (WNSs) is obstructed by the severely limited
energy constraints and security threat for sensor nodes. Since traditional routing and security schemes are
not suited for these networks, a large part of research focusses on energy efficient routing protocols while
extending the network lifetime. Uneven distribution of communication loads result in network partitioning.
Traditional novel en-route filtering approaches, notably commutative cipher based en-route filtering
(CCEF) saves energy by early filtering of false reports. However this approach main focus is security not
network lifetime is limited by fixed paths and underlying routing not suitable for WSNs. In order to cater
these problems we propose energy efficient routing and pre-deterministic key distribution with dynamic
path selection in CCEF. Modified CCEF (MCCEF) aims at saving energy and extending network lifetime
while maintaining filtering power as in CCEF. Experimental results demonstrate the validity of our
approach with an average of three times network lifetime extension, 5.022% energy savings, and similar
filtering power as the original scheme.
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.
CONSENSUS BASED DATA AGGREGATION FOR ENERGY CONSERVATION IN WIRELESS SENSOR N...ijdpsjournal
Our planet is abundant with raw data and to monitor the available data properly, processing of the enormous raw data is very vital. One of the key things in development of mankind and the nature is to acquire as much data as possible and to react appropriately in accordance with the studied data. It’s nothing but diagnosis of the physical world by studying the data acquired from them in order to take proper measures that can help in treating them better. Large volume of data incurs high energy consumption for its transmission and thus results in decrease of overall network lifetime.
Wireless Sensor Network (WSN) is a collection of multiple sensor nodes that all together forms a network for transmitting data acquired by each sensor node to sink known as Base Station (BS). In hierarchical routing acquired data are sent via relay agents like Cluster Heads (CH). The Cluster Heads must be customised with computations and formulations, which will help in aggregating the gathered data, in order to reduce energy consumption while transmitting the data further in the network while maintaining the data integrity to withhold the significance of every single value in a data set.
A cross layer protocol based on mac and routing protocols for healthcare appl...ijassn
Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In
much of this research tasks like sensor data processing, health states decision making and emergency
message sending are done by a remote server. Many patients with lots of sensor data consume a great deal
of communication resources, bring a burden to the remote server and delay the decision time and
notification time. A healthcare application for elderly people using WSN has been simulated in this paper.
A WSN designed for the proposed healthcare application needs efficient MAC and routing protocols to
provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based
on these requirements, A cross layer based on the modified versions of APTEEN and GinMAC has been
designed and implemented, with new features, such as a mobility module and routes discovery algorithms
have been added. Simulation results show that the proposed cross layer based protocol can conserve
energy for nodes and provide the required performance such as life time of the network, delay and
reliability for the proposed healthcare application.
Energy Proficient and Security Protocol for WSN: A Reviewtheijes
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.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 3
Performance evaluation of data filtering approach in wireless sensor networks for energy efficiency
1. International Journal of Mobile Network Communications & Telematics ( IJMNCT) Vol. 4, No.3, June 2014
DOI : 10.5121/ijmnct.2014.4302 11
PERFORMANCE EVALUATION OF DATA FILTERING
APPROACH IN WIRELESS SENSOR NETWORKS FOR
ENERGY EFFICIENCY
Nidhi Gautam1
, Sanjeev Sofat2
and Renu Vig3
1
U.I.A.M.S., Panjab University Chandigarh, India
2
PEC University of Technology Chandigarh, India
3
U.I.E.T., Panjab University Chandigarh, India
ABSTRACT
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.
KEYWORDS
Filtering, Clustering, Aggregation, Energy consumed, delay, jitter, overhead
1. INTRODUCTION
Wireless sensor networks were initially developed for applications in severe conditions. But now
they are being deployed in various application areas including patient care in hospitals, traffic
management, pollution monitoring and control etc. Earlier the concern was its resource limited
nature and is still the same despite of many proposed solutions. Due to its resource limitations, the
focus has been shifted towards heterogeneous sensor nodes in the wireless networks. In this type
of network, some homogeneous nodes are placed for sensing and better configured nodes are
placed for data clustering and communication. The better configured nodes can be mobile or
static depending upon the nature of the application [1].
The data communication in wireless sensor networks takes most of the energy of the sensor
nodes. Hence, the focus of the research is to reduce inter-node transmissions for conserving
energy at the sensor node level. Energy efficient clustering and data filtering may help to increase
the network lifetime. Filtering the data at the sensor node level checks the redundant information
and passes only the new entry to the cluster-head. The cluster-head also applies the same data
filtering approach and sends only the required information to the base station. This whole process
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may reduce the inter-node transmissions and further increases the network lifetime. Energy
efficient clustering also adds the benefit and helps in longevity of the network.
Therefore, the process is multilevel that deals with sensing, filtering and aggregating the
correlated data from various sources. Along with clustering, data filtering and fusion appears to
be an effective technique for the reduction of communication overhead by removing the
redundant messages. Therefore, this technique happens to be very important aspect in increasing
energy efficiency and lifetime of wireless sensor networks.
The rest of the paper is organized as follows: Section 2 reviews related work in the clustering and
data filtering in wireless sensor networks. Section 3 represents the approach used in this paper.
Section 4 describes the simulation results and discussions and Section 5 concludes the paper.
2. LITERATURE REVIEW
A. Clustering
In the recent literature, various clustering algorithms have been proposed. [2] presented the
survey of various clustering algorithms in terms of convergence time, node mobility, cluster
overlapping, location awareness, energy-efficiency, failure recovery, balanced clustering and
cluster stability. [3-7] used voronoi diagrams for the movement of various mobile nodes in the
area of observation for efficient data collection. [8-13] used ant systems and its various
modifications for choosing the optimal path between source and the destination in wireless sensor
networks. Voronoi diagram has been a successful technique for boundary estimation and grid
formation [14]. An ant system has proved itself to be energy efficient in choosing the optimal
paths. VAS [15] presented the combination of voronoi diagrams and ant systems that helps in
improving network performance in terms of energy efficiency.
VAS has been compared with AODV and OSPFv2 which are routing algorithms. To prove its
significance in wireless sensor networks, we intend to compare VAS with traditional LEACH-C
algorithm for energy efficiency.
B. Data Filtering
The algorithms presented in [16-18] are based on hierarchical approach for data aggregation and
do not implement any data fusion process to reduce data size. [19-27] used various fusion
techniques. [28-30] presented data aggregation methods in resource constraint wireless sensor
networks.
[31-32] used Kalman filtering and TWSW filtering for over sighting the redundant data
respectively. Both the papers do not cover the criticality of an application and is majorly suitable
for non-critical applications. The technique presented in [33] is a modification of TWSW filtering
and hence we call it as MTWSW. This approach is suitable both for critical as well as for non
critical applications in wireless sensor networks. MTWSW filtering approach filters out the data
in such a way that spurious and redundant data can be ignored for non-critical applications and
crucial information is disseminated for critical applications.
MTWSW has not been compared with any filtering approach in the literature. Hence we intend to
compare MTWSW with the original TWSW for its significance in the field of wireless sensor
networks.
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3. APPROACH USED
The approach used in this paper is as follows:
1: Network Initialization, Node Initialization, Neighbour Initialization.
2: Cluster formation:
a) Cluster-head nodes run VAS (Voronoi Ant Systems) algorithm.
b) All sensor nodes identify their membership status through VCP (Voronoi Control
Packet).
c) Data dissemination starts from sensor nodes to sink node through respective cluster-head
nodes.
3: An Ant system from VAS is used for route discovery and route maintenance in the network.
4: Comparison of VAS and LEACH-C on the basis of average end-to-end packet delay, energy
consumption and data delivery ratio with varying network size and data send rate.
5: Apply MTWSW to all the sensor nodes as well as to all the cluster-head nodes, so that:
a) Redundant packets are filtered out at sensor node level and intermediate level.
b) Further unimportant/redundant data is filtered out at cluster-head level.
6: Comparison of MTWSW and TWSW on the basis of average end-to-end packet delay,
energy consumption and data delivery ratio with varying network size and data send rate.
ABBREVIATIONS AND ACRONYMS
VAS: Voronoi Ant Systems
VCP: Voronoi Control Packet
TWSW: Two Way Sliding Window
MTWSW: Modified Two Way Sliding Window
AODV: Ad hoc On-Demand Distance Vector Routing
OSPFv2: Open Shortest Path First version 2 Routing
LEACH: Low Energy Adaptive Clustering Hierarchy
4. RESULTS & DISCUSSIONS
The area of observation is (100X100) m2
with 100 homogeneous sensor nodes, 10 cluster-head
nodes having unlimited battery, 1 sink node placed outside the side of observation. The power
parameter used for the experiment are: MicaZ, ZigBee Application with 127 Bytes packet size,
IEEE 802.15.4 standard at the MAC and Physical Layer, Linear Battery model (1200 mAh) for
sensor nodes, two-ray signal propagation model. Simulations have been performed in QualNet
version 6.1. We assume that the temperature of an agriculture land’s surface is to be monitored
continuously.
VAS Clustering versus LEACH-C
VAS has been compared by AODV and OSPFv2 in its previous work, but no comparison has
been made with any clustering approach for wireless sensor network. In this paper, we tend to
compare VAS with LEACH-C algorithm on the basis of average end-to-end packet delay, energy
consumed and data delivery ratio. The varying parameters are network size and data send rate.
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LEACH-C uses base station to make a decision for cluster formation whereas in VAS all the
cluster head nodes makes the decision of cluster formation which in turn saves time and energy.
As shown in Figure 1, with increase in network area, the communication between cluster heads
and base station takes more time and hence VAS shows better results than LEACH-C in-terms of
average end-to-end packet delay.
Hence overall energy consumption of VAS is less as compared to LEACH-C as shown in Figure
1(b). As shown in Figure 1(c), data delivery ratio of VAS is much better than LEACH-C because
of better route planning and implementation by ant systems by VAS.
Figure 1(a) Average end-to-end packet delay with varying network area
Figure 1(b) Energy consumption with varying network area
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As the data send rate varies in Figure 2, performance of both the algorithms deteriorates. With
variation in data send rate, more number of data packets is generated in the network and hence
leads to congestion. VAS uses ant systems for route discovery and route maintenance. An ant
system used in VAS is very useful in handling traffic congestion as shown in Figure 2(a). It
handles the redundant packets very well whereas LEACH-C performs poorly in this scenario.
Figure 2(a) Average end-to-end packet delay with varying data send rate
Figure 1(c) Data delivery ratio with varying network area
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Therefore, VAS is more energy efficient as compare to LEACH-C as shown in Figure 2(b)
VAS performs well with 4 data packets per second as shown in Figure 2(c). Though it performs
well as compare to LEACH-C for 10-12 data packets per second but we consider 4 is the
optimum number for VAS. VAS shows good performance as compared to LEACH-C with all the
parameters.
Hence VAS proves to be better than LEACH-C with varying network area and data send rate
in terms of average end-to-end packet delay, energy consumption and data delivery ratio.
MTWSW versus TWSW
After analyzing VAS clustering in wireless sensor network, we implement filtering approach for
improving it further. To check the significance of MTWSW with VAS in wireless sensor
networks, we apply TWSW as well. Here in this section, a comparative analysis is presented
Figure 2(b) Energy consumption with varying data send rate
Figure 2(c) Data delivery ratio with varying data send rate
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between TWSW and MTWSW with varying network size and data send rate. The algorithms
have been compared on the basis of average end-to-end packet delay, energy consumption and
data delivery ratio.
Variation i network size has lot of impact on the network performance. Figure 3(a) and 3(b)
represents average end-to-end packet delay, energy consumed respectively with varying network
size.
Figure 3(a) shows that average end-to-end delay has increased because node density directly
affects the network performance. The sparsely populated sensor nodes in a networks form a very
difficult environment because of poor connectivity. MTWSW shows better performance in terms
of average end-to-end packet delay than TWSW because the sensed data items have been filtered
at the sensor/relay node level and only non redundant information is transmitted to cluster head
nodes which further decreases the average delay.
Figure 3(b) Energy consumption with varying network area
Figure 3(a) Average end-to-end packet delay with varying network area
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Energy consumption as shown in Figure 3(b) has increased with increasing network area because
of sparse networks. But energy consumed by MTWSW is much less than TWSW as well as
without filtering approach
As shown in the Figure 3(c), the data delivery ratio is deteriorating with increasing network area
because the average path length between two communicating nodes is increasing and hence
increasing the chances of link failure and hampers the repair mechanism. Even in the worst case
MTWSW is able to deliver approximately 48 % of the data as compare to 40 % by TWSW in the
worst case
The data send rate i.e. number of packets sent per second has been varied from 1 to 12 packets per
second. By varying the number of packets sent per second, increases the network load and
congestion and interference becomes more likely.
Figure 4(a) Average end-to-end packet delay with varying data send rate
Figure 3(c) Data delivery ratio with varying network area
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Figure 4(a) and 4(b) represents average end-to-end packet delay and energy consumed
respectively with varying data send rate. As shown in the figures, both the parameters suffered
with increase in data send rate from four packets to eight packets per second. But in this case also
MTWSW filtering approach performed better than its counterpart.
Data delivery ratio has been represented by Figure 4(c) with varying data send rate. In this case,
we considered the number of data items sent from the source nodes after filtering redundant data
items rather than the number of data items sensed at the source node. It has been noticed from the
figure that increasing data send rate from four packets to eight packets has a great impact on data
delivery ratio and energy consumption. With four data packets per second MTWSW was able to
deliver approximately 89% of the data accurately whereas TWSW delivered approximately 85%
of the data accurately. Hence TWSW has shown better performance than TWSW.
Figure 4 (b) Energy consumption with varying data send rate
Figure 4(c) Data delivery ratio with varying data send rate
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5. CONCLUSIONS
In this paper, we have compared VAS and TWSW with standard approaches for their validation
in the field of wireless sensor networks. The paper has been divided into two continuous sections.
In first section, VAS has been compared with LEACH-C and in preceding section; MTWSW has
been compared with TWSW. The comparison has been made on the basis of average end-to-end
packet delay, energy consumed and data delivery ratio with varying network size and number of
packets sent per second. In the first section, VAS has been proved better than LEACH-C and
MTWSW has been proved better than TWSW in preceding section. This papers represents the
significance of clustering and filtering in resource limited wireless sensor networks. Further
research in this area will offer promising results. We plan to extend this approach by
implementing mobility in this type of heterogeneous network. We did not take up security aspects
of wireless sensor networks in this work. Wireless sensor network security can also be taken up as
future work.
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