Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical issue that degrades the network performance. Recharging and providing security to the sensor devices is very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an important and suitable approach to increase energy efficiency and transmitting secured data which in turn enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC) works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all the cluster heads are formed at a time and selected on rotation based on considering the highest energy of the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access (CSMA), a contention window based protocol is used at the MAC layer for collision detection and to provide channel access prioritization to HWSN of different traffic classes with reduction in End to End delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the cluster head for transmission without depleting the energy. Simulation parameters of the proposed system such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing system.
SLGC: A New Cluster Routing Algorithm in Wireless Sensor Network for Decrease...IJCSEA Journal
Decrease energy consumption and maximizing network lifetime are important parameters in designing and protocols for wireless sensor network (WSN).Clustering is one of the efficient methods in energy consumption by Cluster-Head in WSN. Besides, CH can process and aggregate data sent by cluster members, thus reducing network traffic for sending data to sink. In this paper presents a new cluster routing algorithm by dividing network into grids. In each grid computes the center-gravity and threshold of energy for selecting the node that has the best condition base on these parameters in grid for selecting Cluster-Head in current round, also SLGC selecting Cluster-Heads for next rounds thereby this CHs reduce the volume of controlling messages for next rounds and inform nodes for sending data into CH of respective round. This algorithm prolong network lifetime and decrease energy consumption by selecting CH in grid and sending data of grid to sink by this CH. Result of simulation shows that SLGC algorithm in comparison with the previous clustering algorithm has maximizing network lifetime and decrease energy consumption in network.
Comparative Simulation Study Of LEACH-Like And HEED-Like Protocols Deployed I...IOSRJECE
WSNs represents one of the most interesting research areas with deep impact on technological development because of their potential usage in a wide variety of applications such as fire monitoring, border surveillance medical care, and highway traffic coordination. Therefore, WSNs researchers have defined many routing protocols for this type of network. In this paper, we have implemented and analyzed different clustering protocols, namely LEACH, LEACH-C, LEACH-1R, and HEED using MATLAB environment. These routing protocols are compared in different terms such as residual energy, data delivery to the base station, number of rounds and live nodes
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.
SECTOR TREE-BASED CLUSTERING FOR ENERGY EFFICIENT ROUTING PROTOCOL IN HETEROG...IJCNCJournal
One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.
SLGC: A New Cluster Routing Algorithm in Wireless Sensor Network for Decrease...IJCSEA Journal
Decrease energy consumption and maximizing network lifetime are important parameters in designing and protocols for wireless sensor network (WSN).Clustering is one of the efficient methods in energy consumption by Cluster-Head in WSN. Besides, CH can process and aggregate data sent by cluster members, thus reducing network traffic for sending data to sink. In this paper presents a new cluster routing algorithm by dividing network into grids. In each grid computes the center-gravity and threshold of energy for selecting the node that has the best condition base on these parameters in grid for selecting Cluster-Head in current round, also SLGC selecting Cluster-Heads for next rounds thereby this CHs reduce the volume of controlling messages for next rounds and inform nodes for sending data into CH of respective round. This algorithm prolong network lifetime and decrease energy consumption by selecting CH in grid and sending data of grid to sink by this CH. Result of simulation shows that SLGC algorithm in comparison with the previous clustering algorithm has maximizing network lifetime and decrease energy consumption in network.
Comparative Simulation Study Of LEACH-Like And HEED-Like Protocols Deployed I...IOSRJECE
WSNs represents one of the most interesting research areas with deep impact on technological development because of their potential usage in a wide variety of applications such as fire monitoring, border surveillance medical care, and highway traffic coordination. Therefore, WSNs researchers have defined many routing protocols for this type of network. In this paper, we have implemented and analyzed different clustering protocols, namely LEACH, LEACH-C, LEACH-1R, and HEED using MATLAB environment. These routing protocols are compared in different terms such as residual energy, data delivery to the base station, number of rounds and live nodes
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.
SECTOR TREE-BASED CLUSTERING FOR ENERGY EFFICIENT ROUTING PROTOCOL IN HETEROG...IJCNCJournal
One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.
Energy efficient data communication approach in wireless sensor networksijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based
configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor
node creates challenges for routing in WSNs. The research work presents the organized and detailed
description of energy conservation method for WSNs. In the proposed method reclustering and multihop
data transmission processes are utilized for data reporting to base station by sensor node. The accurate use
of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the
proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the
total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for
longer times inside the cluster. The result shows that the proposed clustering approach has higher stable
region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy
Adaptive Clustering Hierarchy (LEACH) for WSNs.
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.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
An Adaptive Energy Aware Clustering Based Reliable Routing for in-Network Agg...Editor IJCATR
Wireless Sensor Network (WSN) consists of spatially distributed autonomous devices that cooperatively sense physical or
environmental conditions. Due to the non-uniform node deployment, the energy consumption among nodes are more
imbalanced in cluster-based wireless sensor networks this factor will affect the network life time. Cluster-based routing and EADC
algorithm through an efficient energy aware clustering algorithm is employed to avoid imbalance network distribution. Our proposed
protocol EADC aims at minimizing the overall network overhead and energy expenditure associated with the multi hop data retrieval
process while also ensuring balanced energy consumption among SNs and prolonged network life time .A optimal one-hop based
selective node in building cluster structures consisted of member nodes that route their measured data to their assigned cluster head is
identified to ensure efficient communication. The proposed routing algorithm increases forwarding tasks of the nodes in scarcely
covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes and finally, achieves
imbalanced among cluster head and improve the network life time.
CUTTING DOWN ENERGY USAGE IN WIRELESS SENSOR NETWORKS USING DUTY CYCLE TECHNI...ijwmn
A wireless sensor network is composed of many sensor nodes, that have beengiven out in a
specific zoneandeach of them hadanability of collecting information from the environment and
sending collected data to the sink. The most significant issues in wireless sensor networks,
despite the recent progress is the trouble of the severe limitations of energy resources.Since that
in different applications of sensor nets, we could throw a static or mobile sink, then all aspects of
such networks should be planned with an awareness of energy.One of the most significant topics
related to these networks, is routing. One of the most widely used and efficient methods of
routing isa hierarchy (based on clustering) method.
In The present study with the objective of cutting down energy consumption and persistence of
network coverage, we have offered a novel algorithm based on clustering algorithms and multihop routing.To achieve this goal, first, we layer the network environment based on the size of the
network.We will identify the optimal number of cluster heads and every cluster head based on
the mechanism of topology control will start to accept members.Likewise, we set the first layer
as gate layer and subsequently identifying the gate’s nodes, we’d turn away half of the sensors
and then stop using energy and the remaining nodes in this layer will join the gate’s nodes
because they hold a critical part in bettering the functioning of the system. Cluster heads off
following layers send the information to cluster heads in the above layer until sent data will be
sent to gate’s nodes and finally will be sent to sink. We have tested the proposed algorithm in
two situations 1) when the sink is off and 2)when a sink is on and simulation data shows that
proposed algorithm has better performance in terms of the life span of a network than LEACH
and ELEACH protocols.
International Journal of Advanced Smart Sensor Network Systems ( IJASSN )ijassn
With the availability of low cost, short range sensor technology along with advances in wireless networking, sensor networks has become a hot topic of discussion. The International Journal of Advanced Smart Sensor Network Systems is an open access peer-reviewed journal which focuses on applied research and applications of sensor networks. While sensor networks provide ample opportunities to provide various services, its effective deployment in large scale is still challenging due to various factors. This journal provides a forum that impacts the development of high performance computing solutions to problems arising due to the complexities of sensor network systems. It also acts as a path to exchange novel ideas about impacts of sensor networks research.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A LOW-ENERGY DATA AGGREGATION PROTOCOL USING AN EMERGENCY EFFICIENT HYBRID ME...IJCNCJournal
Recent wireless sensor network focused on developing communication networks with minimal power and cost. To achieve this, several techniques have been developed to monitor a completely wireless sensor network. Generally, in the WSN network, communication is established between the source nodes and the destination node with an abundant number of hops, an activity which consumes much energy. The node existing between source and destination nodes consumes energy for transmission of data and maximize network lifetime. To overcome this issue, a new Emergency Efficient Hybrid Medium Access Control (EEHMAC) protocol is presented to reduce consumption of energy among a specific group of WSNs which will increase the network lifetime. The proposed model makes a residual battery is utilized for effective transmission of data with minimal power consumption. Compared with other models, the experimental results strongly showed that our model is not only able to reduce network lifetime but also to increase the overall network performance.
In wireless sensor network energy cutback is considered as a principle intensive challenge which is studied largely in the Wireless Sensor Networks (WSN) literature. Wireless Sensor Networks (WSNs) are pertinent in numerous arenas where WSNs may be used for sensing, ciphering, and communication elements that give a user or administrator the ability to instrument, observe, and retort to events and phenomena in a specific environment. But sensor devices are resource curbed, positioned in an open and unattended environment, different types of attacks and conventional techniques against these attacks are not desirable due to the resource constrained nature of these kinds of networks. An energy-balanced routing method based on forward-aware factor (FAF-EBRM) in which the next-hop node is elected according to the awareness of link weight and forward energy density. FAF-EBRM is compared with Ladder Diffusion Algorithm, which balances the energy utilization, sustain the function era and guarantees high QoS of WSN. The FAF-EBRM is proposed with Secure Routing Layer (SRL) Protocol which ensures that the secure data transmission is achieved without releasing private sensor readings and without introducing significant overhead on the battery-limited sensors.
Advance in the WIRELESS SENSOR NETWORK (WISENET) technology is energy efficient routing protocols that promises a wide range of potential applications in both civilian and military areas. In the WISNET the sensor node have a limited transmission range and their processing and storage capabilities as well as their energy sources are limited. So the Equalized Cluster Head Election Routing Protocol (ECHERP) and PEGASIS with Double Cluster Head (PDCH) pursues energy conservation through balanced clustering for Energy Efficiency. In WSN, energy efficient routing protocol is important to increase the network lifetime. ECHERP and PDCH both protocol claims to be energy efficient.
Mobile Data Gathering with Load Balanced Clustering and Dual Data Uploading i...1crore projects
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A Novel Grid Based Dynamic Energy Efficient Routing Approach for Highly Dense...ijasuc
A research work without considering the power constraint cannot be conceded a fine contribution towards
Mobile Ad Hoc Networks (MANET). As MANET comes into action for some special purpose, but its
fugacity sometimes result degrades in network performance. Although the many prominent features of
MANET like mobility, dynamic change in topology, multi radio relaying, quickly lay down the network
without depending upon fixed infrastructures and many more provides tremendous flexibilities for the end
user but challenges like limited power constraint, reliable data communication, band width utilization ,
network performance and throughput are still needed to be handle very sensibly. As limited battery power
and inefficient routing protocol mechanism are high prone to network partition, in such case the network
needs to be established more than once. Because communication establishment involves many costly
operations like route discovery and route maintenance. The more the network partition the more the packet
drops and packet loss which indeed requires a number of retransmission of packets, consuming network
bandwidth as well as depleting battery power of individual nodes with a higher rate, which are the major
destructive elements in network performance degradation as well as the major cause of reducing individual
node’s life time and network life time. So with all caveat in mind, we have proposed a novel Grid Based
Dynamic Energy Efficient Routing (GBDEER) approach which is aimed to construct an energy efficient
path from source to destination based on grid area, where each grid will have three deferent levels of
transmission power. Every grid will have its own grid supervisor node who will take the responsibility
during data communication, especially when the data is been passed through that specific grid. And
keeping the dynamic nature of MANET in mind, we have also provide the feature of grid subordinate
node, who will take the place of grid supervisor in case the supervisor is moving out of the grid area or
running out of energy from certain threshold level. So we our proposed method not only establishes an
energy efficient path but also concerned a dedicated path which can be used for data communication for a
long period of time without any network partition. Hence this approach will be less prone to all those
problems mentions above by the incorporating an efficient mobility handling mechanism.
Energy Efficient Data Aggregation in Wireless Sensor Networks: A Surveyijsrd.com
The use of Wireless Sensor Networks (WSNs) is anticipated to bring lot of changes in data gathering, processing and dissemination for different environments and applications. However, a WSN is a power constrained system, since nodes run on limited power batteries which shorten its lifespan. Prolonging the network lifetime depends on efficient management of sensing node energy resource. Energy consumption is therefore one of the most crucial design issues in WSN. Hierarchical routing protocols are best known in regard to energy efficiency. By using a clustering technique hierarchical routing protocols greatly minimize energy consumed in collecting and disseminating data. To prolong the lifetime of the sensor nodes, designing efficient routing protocols is critical. In this paper, we have discussed various energy efficient data aggregation protocols for sensor networks.
A QoI Based Energy Efficient Clustering for Dense Wireless Sensor Networkijassn
In a wireless sensor network Quality of Information (QoI), Energy Efficiency, Redundant data avoidance,
congestion control are the important metrics that affect the performance of wireless sensor network. As
many approaches were proposed to increase the performance of a wireless sensor network among them
clustering is one of the efficient approaches in sensor network. Many clustering algorithms concentrate
mainly on power Optimization like FSCH, LEACH, and EELBCRP. There is necessity of the above
metrics in wireless sensor network where nodes are densely deployed in a given network area. As the nodes
are deployed densely there is maximum possibility of nodes appear in the sensing region of other nodes. So
there exists an option that nodes have to send the information that is already reached the base station by its
own cluster members or by members of other clusters. This mechanism will affect the QoI, Energy factor
and congestion control of the wireless sensor networks. Even though clustering uses TDMA (Time Division
Multiple Access) for avoiding congestion control for intra clustering data transmission, but it may fail in
some critical situation. This paper proposed a energy efficient clustering which avoid data redundancy in a
dense sensor network until the network becomes sparse and hence uses the TDMA efficiently during high
density of the nodes.
Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Eff...CSCJournals
The objective of this paper is to develop a mechanism to increase the lifetime of homogeneous wireless sensor networks (WSNs) through minimizing long range communication, efficient data delivery and energy balancing. Energy efficiency is a very important issue for sensor nodes which affects the lifetime of sensor networks. To achieve energy balancing and maximizing network lifetime we divided the whole network into different clusters. In cluster based architecture, the role of aggregator node is very crucial because of extra processing and long range communication. Once the aggregator node becomes non functional, it affects the whole cluster. We introduced a candidate cluster head node on the basis of node density. We proposed a modified cluster based WSN architecture by introducing a server node (SN) that is rich in terms of resources. This server node (SN) takes the responsibility of transmitting data to the base station over longer distances from the cluster head. We proposed cluster head selection algorithm based on residual energy, distance, reliability and degree of mobility. The proposed method can save overall energy consumption and extend the lifetime of the sensor network and also addresses robustness against even/uneven node deployment.
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.
Energy efficient data communication approach in wireless sensor networksijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based
configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor
node creates challenges for routing in WSNs. The research work presents the organized and detailed
description of energy conservation method for WSNs. In the proposed method reclustering and multihop
data transmission processes are utilized for data reporting to base station by sensor node. The accurate use
of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the
proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the
total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for
longer times inside the cluster. The result shows that the proposed clustering approach has higher stable
region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy
Adaptive Clustering Hierarchy (LEACH) for WSNs.
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.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
An Adaptive Energy Aware Clustering Based Reliable Routing for in-Network Agg...Editor IJCATR
Wireless Sensor Network (WSN) consists of spatially distributed autonomous devices that cooperatively sense physical or
environmental conditions. Due to the non-uniform node deployment, the energy consumption among nodes are more
imbalanced in cluster-based wireless sensor networks this factor will affect the network life time. Cluster-based routing and EADC
algorithm through an efficient energy aware clustering algorithm is employed to avoid imbalance network distribution. Our proposed
protocol EADC aims at minimizing the overall network overhead and energy expenditure associated with the multi hop data retrieval
process while also ensuring balanced energy consumption among SNs and prolonged network life time .A optimal one-hop based
selective node in building cluster structures consisted of member nodes that route their measured data to their assigned cluster head is
identified to ensure efficient communication. The proposed routing algorithm increases forwarding tasks of the nodes in scarcely
covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes and finally, achieves
imbalanced among cluster head and improve the network life time.
CUTTING DOWN ENERGY USAGE IN WIRELESS SENSOR NETWORKS USING DUTY CYCLE TECHNI...ijwmn
A wireless sensor network is composed of many sensor nodes, that have beengiven out in a
specific zoneandeach of them hadanability of collecting information from the environment and
sending collected data to the sink. The most significant issues in wireless sensor networks,
despite the recent progress is the trouble of the severe limitations of energy resources.Since that
in different applications of sensor nets, we could throw a static or mobile sink, then all aspects of
such networks should be planned with an awareness of energy.One of the most significant topics
related to these networks, is routing. One of the most widely used and efficient methods of
routing isa hierarchy (based on clustering) method.
In The present study with the objective of cutting down energy consumption and persistence of
network coverage, we have offered a novel algorithm based on clustering algorithms and multihop routing.To achieve this goal, first, we layer the network environment based on the size of the
network.We will identify the optimal number of cluster heads and every cluster head based on
the mechanism of topology control will start to accept members.Likewise, we set the first layer
as gate layer and subsequently identifying the gate’s nodes, we’d turn away half of the sensors
and then stop using energy and the remaining nodes in this layer will join the gate’s nodes
because they hold a critical part in bettering the functioning of the system. Cluster heads off
following layers send the information to cluster heads in the above layer until sent data will be
sent to gate’s nodes and finally will be sent to sink. We have tested the proposed algorithm in
two situations 1) when the sink is off and 2)when a sink is on and simulation data shows that
proposed algorithm has better performance in terms of the life span of a network than LEACH
and ELEACH protocols.
International Journal of Advanced Smart Sensor Network Systems ( IJASSN )ijassn
With the availability of low cost, short range sensor technology along with advances in wireless networking, sensor networks has become a hot topic of discussion. The International Journal of Advanced Smart Sensor Network Systems is an open access peer-reviewed journal which focuses on applied research and applications of sensor networks. While sensor networks provide ample opportunities to provide various services, its effective deployment in large scale is still challenging due to various factors. This journal provides a forum that impacts the development of high performance computing solutions to problems arising due to the complexities of sensor network systems. It also acts as a path to exchange novel ideas about impacts of sensor networks research.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A LOW-ENERGY DATA AGGREGATION PROTOCOL USING AN EMERGENCY EFFICIENT HYBRID ME...IJCNCJournal
Recent wireless sensor network focused on developing communication networks with minimal power and cost. To achieve this, several techniques have been developed to monitor a completely wireless sensor network. Generally, in the WSN network, communication is established between the source nodes and the destination node with an abundant number of hops, an activity which consumes much energy. The node existing between source and destination nodes consumes energy for transmission of data and maximize network lifetime. To overcome this issue, a new Emergency Efficient Hybrid Medium Access Control (EEHMAC) protocol is presented to reduce consumption of energy among a specific group of WSNs which will increase the network lifetime. The proposed model makes a residual battery is utilized for effective transmission of data with minimal power consumption. Compared with other models, the experimental results strongly showed that our model is not only able to reduce network lifetime but also to increase the overall network performance.
In wireless sensor network energy cutback is considered as a principle intensive challenge which is studied largely in the Wireless Sensor Networks (WSN) literature. Wireless Sensor Networks (WSNs) are pertinent in numerous arenas where WSNs may be used for sensing, ciphering, and communication elements that give a user or administrator the ability to instrument, observe, and retort to events and phenomena in a specific environment. But sensor devices are resource curbed, positioned in an open and unattended environment, different types of attacks and conventional techniques against these attacks are not desirable due to the resource constrained nature of these kinds of networks. An energy-balanced routing method based on forward-aware factor (FAF-EBRM) in which the next-hop node is elected according to the awareness of link weight and forward energy density. FAF-EBRM is compared with Ladder Diffusion Algorithm, which balances the energy utilization, sustain the function era and guarantees high QoS of WSN. The FAF-EBRM is proposed with Secure Routing Layer (SRL) Protocol which ensures that the secure data transmission is achieved without releasing private sensor readings and without introducing significant overhead on the battery-limited sensors.
Advance in the WIRELESS SENSOR NETWORK (WISENET) technology is energy efficient routing protocols that promises a wide range of potential applications in both civilian and military areas. In the WISNET the sensor node have a limited transmission range and their processing and storage capabilities as well as their energy sources are limited. So the Equalized Cluster Head Election Routing Protocol (ECHERP) and PEGASIS with Double Cluster Head (PDCH) pursues energy conservation through balanced clustering for Energy Efficiency. In WSN, energy efficient routing protocol is important to increase the network lifetime. ECHERP and PDCH both protocol claims to be energy efficient.
Mobile Data Gathering with Load Balanced Clustering and Dual Data Uploading i...1crore projects
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A Novel Grid Based Dynamic Energy Efficient Routing Approach for Highly Dense...ijasuc
A research work without considering the power constraint cannot be conceded a fine contribution towards
Mobile Ad Hoc Networks (MANET). As MANET comes into action for some special purpose, but its
fugacity sometimes result degrades in network performance. Although the many prominent features of
MANET like mobility, dynamic change in topology, multi radio relaying, quickly lay down the network
without depending upon fixed infrastructures and many more provides tremendous flexibilities for the end
user but challenges like limited power constraint, reliable data communication, band width utilization ,
network performance and throughput are still needed to be handle very sensibly. As limited battery power
and inefficient routing protocol mechanism are high prone to network partition, in such case the network
needs to be established more than once. Because communication establishment involves many costly
operations like route discovery and route maintenance. The more the network partition the more the packet
drops and packet loss which indeed requires a number of retransmission of packets, consuming network
bandwidth as well as depleting battery power of individual nodes with a higher rate, which are the major
destructive elements in network performance degradation as well as the major cause of reducing individual
node’s life time and network life time. So with all caveat in mind, we have proposed a novel Grid Based
Dynamic Energy Efficient Routing (GBDEER) approach which is aimed to construct an energy efficient
path from source to destination based on grid area, where each grid will have three deferent levels of
transmission power. Every grid will have its own grid supervisor node who will take the responsibility
during data communication, especially when the data is been passed through that specific grid. And
keeping the dynamic nature of MANET in mind, we have also provide the feature of grid subordinate
node, who will take the place of grid supervisor in case the supervisor is moving out of the grid area or
running out of energy from certain threshold level. So we our proposed method not only establishes an
energy efficient path but also concerned a dedicated path which can be used for data communication for a
long period of time without any network partition. Hence this approach will be less prone to all those
problems mentions above by the incorporating an efficient mobility handling mechanism.
Energy Efficient Data Aggregation in Wireless Sensor Networks: A Surveyijsrd.com
The use of Wireless Sensor Networks (WSNs) is anticipated to bring lot of changes in data gathering, processing and dissemination for different environments and applications. However, a WSN is a power constrained system, since nodes run on limited power batteries which shorten its lifespan. Prolonging the network lifetime depends on efficient management of sensing node energy resource. Energy consumption is therefore one of the most crucial design issues in WSN. Hierarchical routing protocols are best known in regard to energy efficiency. By using a clustering technique hierarchical routing protocols greatly minimize energy consumed in collecting and disseminating data. To prolong the lifetime of the sensor nodes, designing efficient routing protocols is critical. In this paper, we have discussed various energy efficient data aggregation protocols for sensor networks.
A QoI Based Energy Efficient Clustering for Dense Wireless Sensor Networkijassn
In a wireless sensor network Quality of Information (QoI), Energy Efficiency, Redundant data avoidance,
congestion control are the important metrics that affect the performance of wireless sensor network. As
many approaches were proposed to increase the performance of a wireless sensor network among them
clustering is one of the efficient approaches in sensor network. Many clustering algorithms concentrate
mainly on power Optimization like FSCH, LEACH, and EELBCRP. There is necessity of the above
metrics in wireless sensor network where nodes are densely deployed in a given network area. As the nodes
are deployed densely there is maximum possibility of nodes appear in the sensing region of other nodes. So
there exists an option that nodes have to send the information that is already reached the base station by its
own cluster members or by members of other clusters. This mechanism will affect the QoI, Energy factor
and congestion control of the wireless sensor networks. Even though clustering uses TDMA (Time Division
Multiple Access) for avoiding congestion control for intra clustering data transmission, but it may fail in
some critical situation. This paper proposed a energy efficient clustering which avoid data redundancy in a
dense sensor network until the network becomes sparse and hence uses the TDMA efficiently during high
density of the nodes.
Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Eff...CSCJournals
The objective of this paper is to develop a mechanism to increase the lifetime of homogeneous wireless sensor networks (WSNs) through minimizing long range communication, efficient data delivery and energy balancing. Energy efficiency is a very important issue for sensor nodes which affects the lifetime of sensor networks. To achieve energy balancing and maximizing network lifetime we divided the whole network into different clusters. In cluster based architecture, the role of aggregator node is very crucial because of extra processing and long range communication. Once the aggregator node becomes non functional, it affects the whole cluster. We introduced a candidate cluster head node on the basis of node density. We proposed a modified cluster based WSN architecture by introducing a server node (SN) that is rich in terms of resources. This server node (SN) takes the responsibility of transmitting data to the base station over longer distances from the cluster head. We proposed cluster head selection algorithm based on residual energy, distance, reliability and degree of mobility. The proposed method can save overall energy consumption and extend the lifetime of the sensor network and also addresses robustness against even/uneven node deployment.
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.
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.
Cluster Head Selection Techniques for Energy Efficient Wireless Sensor Networ...ijsrd.com
Wireless sensor networks are widely considered as one of the most important technologies. The Wireless Sensor Network (WSN) is a wireless network consisting of ten to thousand small nodes with sensing, computing and wireless communication capabilities. They have been applied to numerous fields such as healthcare, monitoring system, military, and so forth. Recent advances in wireless sensor networks have led to many new protocols specifically designed for sensor networks where energy awareness is an essential consideration. Energy efficiency is thus a primary issue in maintaining the network. Innovative techniques that improve energy efficiency to prolong the network lifetime are highly required. Clustering is an effective topology control approach in wireless sensor networks. This paper elaborates several techniques like LEACH, HEED, LEACH-B, PEACH, EEUC of cluster head selection for energy efficient in wireless sensor networks.
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.
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.
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.
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.
ENERGY SAVINGS IN APPLICATIONS FOR WIRELESS SENSOR NETWORKS TIME CRITICAL REQ...IJCNCJournal
Along with handling and poor storage capacity, each sensor in wireless sensor network (WSN) is equipped
with a limited power source and very difficult to be replaced in most application environments. Improving
the energy savings in applications for wireless sensor networks is necessary. In this paper, we mainly focus
on energy consumption savings in applications for wireless sensor networks time critical requirements. Our
Paper accompanying analysis of advanced technologies for energy saving techniques for the optimization
of energy efficiency together with the data transmission is optimal. Moreover, we propose improvements to
increase energy savings in applications for wireless sensor networks require time critical (LEACH
improvements). Simulation results show that our proposed protocol significantly better than LEACH about
the formation of clusters in each round, the average power, the number of nodes alive and average total
received data in base stations.
Energy Efficient LEACH protocol for Wireless Sensor Network (I-LEACH)ijsrd.com
In the wireless sensor networks (WSNs), the sensor nodes (called motes) are usually scattered in a sensor field an area in which the sensor nodes are deployed. These motes are small in size and have limited processing power, memory and battery life. In WSNs, conservation of energy, which is directly related to network life time, is considered relatively more important souse of energy efficient routing algorithms is one of the ways to reduce the energy conservation. In general, routing algorithms in WSNs can be divided into flat, hierarchical and location based routing. There are two reasons behind the hierarchical routing Low Energy Adaptive Clustering Hierarchy (LEACH) protocol be in explored. One, the sensor networks are dense and a lot of redundancy is involved in communication. Second, in order to increase the scalability of the sensor network keeping in mind the security aspects of communication. Cluster based routing holds great promise for many to one and one to many communication paradigms that are pre valentines or networks.
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption.
DATA GATHERING ALGORITHMS FOR WIRELESS SENSOR NETWORKS: A SURVEYijasuc
Recent developments in processor, memory and radio technology have enabled wireless sensor networks
which are deployed to collect useful information from an area of interest. The sensed data must be
gathered and transmitted to a base station where it is further processed for end-user queries. Since the
network consists of low-cost nodes with limited battery power, power efficient methods must be employed
for data gathering and aggregation in order to achieve long network lifetimes. In an environment where in
a round of communication each of the sensor nodes has data to send to a base station, it is important to
minimize the total energy consumed by the system in a round so that the system lifetime is maximized. With
the use of data fusion and aggregation techniques, while minimizing the total energy per round, if power
consumption per node can be balanced as well, a near optimal data gathering and routing scheme can be
achieved in terms of network lifetime. Several application specific sensor network data gathering protocols
have been proposed in research literatures. However, most of the proposed algorithms have been some
attention to the related network lifetime and saving energy are two critical issues for wireless sensor
networks. In this paper we have explored general network lifetime in wireless sensor networks and made an
extensive study to categorize available data gathering techniques and analyze possible network lifetime on
them.
CUTTING DOWN ENERGY USAGE IN WIRELESS SENSOR NETWORKS USING DUTY CYCLE TECHNI...ijwmn
A wireless sensor network is composed of many sensor nodes, that have beengiven out in a
specific zoneandeach of them hadanability of collecting information from the environment and
sending collected data to the sink. The most significant issues in wireless sensor networks,
despite the recent progress is the trouble of the severe limitations of energy resources.Since that
in different applications of sensor nets, we could throw a static or mobile sink, then all aspects of
such networks should be planned with an awareness of energy.One of the most significant topics
related to these networks, is routing. One of the most widely used and efficient methods of
routing isa hierarchy (based on clustering) method.
Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR's performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
May_2024 Top 10 Read Articles in Computer Networks & Communications.pdfIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
April 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF Based Intrusion Detection System for Big Data IOT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF based Intrusion Detection System for Big Data IoT TrafficIJCNCJournal
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IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
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Hierarchical Digital Twin of a Naval Power SystemKerry Sado
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Design and Analysis of Algorithms-DP,Backtracking,Graphs,B&B
Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Network
1. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.1, January 2021
DOI: 10.5121/ijcnc.2021.13105 75
DESIGNING AN ENERGY EFFICIENT
CLUSTERING IN HETEROGENEOUS
WIRELESS SENSOR NETWORK
Lakshmi M and Prashanth C R
Department of Telecommunication Engineering,
Dr. Ambedkar Institute of Technology, Bangalore, India
ABSTRACT
Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical
issue that degrades the network performance. Recharging and providing security to the sensor devices is
very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an
important and suitable approach to increase energy efficiency and transmitting secured data which in turn
enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC)
works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the
rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the
network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on
the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all
the cluster heads are formed at a time and selected on rotation based on considering the highest energy of
the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum
flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access
(CSMA), a contention window based protocol is used at the MAC layer for collision detection and to
provide channel access prioritization to HWSN of different traffic classes with reduction in End to End
delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the
cluster head for transmission without depleting the energy. Simulation parameters of the proposed system
such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing
system.
KEYWORDS
HWSN, Clustering, EEC, CSMA, MAC, PDR.
1. INTRODUCTION
Wireless sensor network (WSN)[1] is the group of sensor nodes that are deployed randomly in a
focused area over actively changing environments. These wireless sensor nodes are used for
sensing, processing, and forwarding the data to the intermediate nodes or neighboring nodes and
to the Base Station (BS) [2]. Since these nodes are small devices and are limited with memory,
low processing, low computation, and small power unit that are battery-powered.
The sensor nodes are scattered in a sensor field which are transceivers having the capability of
collecting, routing the data to the sink using multihop infrastructure-less architecture. The devices
carry computations using their processing capabilities to transmit the processed and required data.
WSNs are used mainly in civilian applications such as detecting, monitoring enemy movements,
nuclear and health care applications, chemical, biological, automation, tracking, and others.
2. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.1, January 2021
76
1.1. Sensor Node
There are five components in a sensor node; a microcontroller unit, a transceiver unit, a memory
unit, a power unit, and a sensor unit as shown in Figure 1. The microcontroller unit is responsible
for handling different tasks such as data processing and controlling other components in the
sensor node.
Figure 1: Components of a sensor node
The controller unit is having a small storage unit that is integrated into the embedded board or
onboard memory. This unit also takes the risk of managing the procedures that make the sensor
node for sensing, processing using algorithms, and collaborating with the other nodes using
wireless communication. The transceiver unit is the most power-consuming unit where a sensor
node communicates with other nodes and other parts of the WSN. Random Access Memory,
Read-Only Memory and other memory types are used as temporary storage of sensed data. The
power unit is a critical component for supplying node energy. Batteries are used for storing
power. The sensor unit is the main component in a wireless sensor node which provides
information-gathering capabilities from the physical phenomenon. This unit is responsible for
gathering information from the outside world like light, sound, temperature, and others. There are
two subunits i.e. a sensor and an analogue to digital converter (ADC).
It is known that Energy efficiency is the ratio of the total amount of data delivered to the total
energy consumed. The energy efficiency [3] increases as more data is transmitted from the source
to destination in a given amount of energy consumption. In turn, it is the one which provides the
same service by using less energy. The focus of these techniques is to achieve energy efficiency
and maximization of network lifetime. Clustering is the most widely used technique in
hierarchical routing to achieve these parameters. Redundant messages are eliminated while
forming efficient clusters and selecting or reselecting the Cluster Head (CH). It is required to
construct the topology for distributing the nodes uniformly in the clusters which makes the
network efficient. Poor network performance is due to the excessive energy consumption while
forming the clusters periodically and reselecting the CH [4, 5, and 6].
1.2. Routing Protocols
An algorithm for defining the exact route for a packet from source to destination is nothing but
the routing protocol. Due to resource constraints in WSN, routing is more challenging compared
to mobile ad-hoc networks or vehicular ad-hoc networks [7]. So new routing mechanisms are
very important in keeping in view the network architecture and application requirements. High
energy consumption results due to negligence in route maintenance and frequent topological
changes. Researchers have found various routing techniques for minimizing energy consumption
and maximizing the network lifetime. The categories of routing protocols are shown in Figure 2.
3. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.1, January 2021
77
Figure 2: Classification of routing protocols
Nodes in the network are grouped into clusters by using some algorithms and the cluster head is
elected on some criteria and held responsible for routing the packets. Two-layer approaches are
used in hierarchical routing and one layer is for sensing the physical phenomenon and other
layers for routing. Higher energy nodes are used for collecting, aggregating, and forwarding the
data sensed by lower energy nodes [8]. Scalability and effective communication can be achieved
through clustering approaches. These approaches have many advantages such as Data
aggregation efficiency, efficient usage of channel bandwidth, and increase in scalability.
Some of the clustering techniques are compared such as Low Energy Adaptive Clustering
Hierarchy(LEACH), Hybrid Energy Efficient Distributed Protocol(HEED), Extended HEED,
Distributed Weight-based Energy-efficient Hierarchical Clustering protocol (DWEHC),
Algorithm for Cluster Establishment (ACE).
1.3. Energy Efficiency in Mac Protocols in WSN
A significant amount of energy is saved in a multi-hop network by the occurrence of routing
using an efficient routing algorithm. Transmission power is dependent based on distance and
range, and energy is a major factor while route discovery. Sensor node has a component called
Radio which is a major power-consuming and it is controlled by Medium Access Control (MAC)
Protocol. Network lifetime increases to a great extent by an efficient MAC Protocol. Besides, the
sharing of the wireless mediums is also controlled by the MAC protocol [9]. Less power is
consumed by a sensor node when it is in sleep mode.
There are three types of traffic in IEEE 802.15.4 standard such as periodic, intermittent, and low
latency data. Guaranteed access of the medium is required for allocating the time slots. One of
the critical application securities monitoring which defines the repetitive low data. There are two
modes in which the MAC protocol provides for three types of traffic such as beacon-enabled and
non-beacon-enabled modes. Beacon enabled mode is for stat topology that defines the
Guaranteed Time Slot(GTS) in a superframe. Peer to peer network is used for non beaconed
enabled mode which is self-organized but does not acknowledge where the data is delivered or
not. CSMA/CA is compared for the analysis of this contention free allocation of GTS. The MAC
layer uses the medium in two different modes. The modes allow the frame transmission through a
physical channel. A beacon-enabled mode uses CSMA/CA mechanism and offers GTS in a
superframe used mostly for time-critical applications. MAC layer provides guaranteed services,
controlling of frame validation, and security services.
One of the adaptive protocols called Sensor Protocols for Information via Negotiation (SPIN)
[10] assumes all the nodes as potential base stations and disseminates all the information at each
Network
Structure
Topology
Based
Reliable
routing
Communication
model scheme
Flat
Network
Hierarchial
approach
Grid
based
Cluster
based
Routing
Protocol
s
4. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.1, January 2021
78
node to all other nodes. This protocol having variants are proposed to enhance the performance of
the network. In Gradient Based Routing (GBR)[11], the difference between the height of a node
and its neighbor node is calculated named as gradient value. Transmission of packet takes place
on a link having the largest gradient value.GBR working is based on memorizing hops count
while diffusing the entire network. Some authors have proposed a hierarchial routing algorithm
which is energy-aware routing for cluster-based networks [12]. This method is based on the
architecture of three tiers. Here the clusters are formed by grouping the sensors and Time-
division multiple access (TDMA) MAC scheme is used to operate the network.
Medium Access control protocols are very important in wireless communication for accessing the
channel. Designing MAC protocols have many issues such as collision, overhearing, and terminal
problems. Since sensors are battery-powered, energy is very important for sensor nodes. Energy
consumption is more in the case of collision, data duplication, delay, and quality of service in
MAC protocol design. Contention based protocol is a communication protocol used to operate
telecommunication equipment in a wireless environment where many users use the same radio
channel without coordination. MAC protocols are divided into TDMA protocols, CSMA based
protocols, and Hybrid protocols. Sensor nodes wake up periodically in CSMA based protocols,
listen to WSN, and again back to sleep. Using CSMA, throughput can be achieved at a lower
traffic load.
The network flow approach [13] is introduced to overcome the problem of routing in sensor
networks. The approach is better in maximizing the network lifetime by considering the link cost
as a function remaining energy of the nodes and the transmission energy using the link.
1.4. Motivation
Some issues are found in the clustering protocols such as a selection of faithful CH, Formation of
energy-efficient clusters, and management of the network. The probabilistic approach is
considered and linked to the criteria while selecting the CH. A node can be selected as CH by
varying the selection of CH which in turn increases the internal overhead. Energy consumption in
the network is increased when the node is selected as CH in the region and hence the
performance of the network reduces. All the nodes connected in the network should have better
internal parameters and connectivity. So the performance parameters are enhanced by selecting
the better CH approach and transmitting secured data.
The work is contributed to overcoming the issues of energy consumption and secured data
transmission. MAC layer has a scheduling mechanism for designing a network that makes
collision-free and more energy conserving. Many MAC protocols have been designed to avoid
collision on a medium and contention window based protocol CSMA plays an important role
during data transmission which occurs while carrier sensing. In the network, clusters are formed
and CHs of all the clusters are selected at a time based on highest energy. The main idea is to
select the CH for data transmission and other CH with less transmission and make them sleep.
This methodology helps in achieving network lifetime by less consumption of node energy.
2. LITERATURE SURVEY
A.Razaque et al., [14] have introduced an energy-efficient medium access control (EE-MAC)
protocol for WSNs. Idle listening and congestion problem is handled for energy preservation.
Semi synchronous low duty cycle is used in the protocol which uses less time for channel access.
Authors have shown that higher throughput can be achieved using this. They have compared with
existing protocols and achieved by saving 2% to 4.5% energy.
5. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.1, January 2021
79
Mohamed et al.,[15] have proposed a cluster-based routing protocol that has a two-tier structure.
This has the benefit of combining cluster head distribution and chain based routing for
minimizing the CH loss which occurs during data aggregation and transmission from Region of
interest to base station. Adaptive length of time has been used reconstruct to the network for
maintaining the adaptability with minimal network overhead. Authors have compared the work
with other existing routing protocols and achieved a 100% increase in the network stability
period. Accha et al.,[16] have studied the characteristics of MAC protocols for wireless sensor
networks and observed one of the Sensor MAC’s energy efficiency over CSMA/CA and
simulated using ns-2 over an ad-hoc wireless network. The authors analyzed the performance of
different MAC protocols and selected a specific MAC protocol for application need.
Gangbam et al.,[17] have studied that the energy consumption by the CH during transmission
with a base station is higher compared to the energy depleted by cluster members to transmit the
data to the respective CHs. Authors proposed a protocol that organizes the selection of CH
efficiently for providing the network lifetime and also balancing the CH selection. They have
achieved better performance compared to other protocols. Liu et al., [18] proposed an algorithm
called a novel Quorum Time Slot Adaptive Condensing (QTSAC) based medium access control
for minimizing the delay and energy efficiency of a wireless sensor networks. A duty cycle of the
system is prolonged by condensing the Quorum time slot to the data transmission period based on
WSN characteristics and also this innovation reduced the network latency. Utilization of energy
remaining in the area which is far from the sink increases the QTS for achieving the above-
mentioned parameters. S A Sert et al., [19] proposed a two-tier distributed fuzzy logic-based
protocol (TTDFP) for the data aggregation efficiency improvement in multihop wireless sensor
networks. Clustering is considered for efficient aggregation requirements like consumed energy.
A network is divided into clusters and data is transmitted from member nodes to the CHs, then
packets are received at the base stations from CHs. This proposed TTDFP for extending the
lifespan of multihop WSNs by considering the clustering efficiency and routing phases. Also,
tuning of parameters is done by using the optimization framework used in fuzzy clustering.
Alsaafin et al., [20] designed a system by Heterogeneous Aware Distributed Clustering (HADC)
algorithm. They presented node heterogeneity in terms of energy for enhancing the network
lifetime. CHs in the proposed system are selected based on the cost function by considering the
residual energy and node load. By making the trade-off between the distance and node degree
towards CHs, the authors reduced the energy consumption and balancing the load in the network.
Proposed system performance is compared with HEED and LEACH in terms of efficiency. An S
Toor et al.,[21] proposed a routing protocol named Energy Aware Cluster Based Multi-
hop(EACBM) which reduces the energy consumption of sensor nodes by considering the concept
of clustering and multihop communication. Additionally, the sub clustering concept is considered
in the proposed system for the sensor nodes which are not reachable and are not included in any
of the clusters. This protocol is compared with the existing protocols LEACH, CEEC, and SEP).
Authors improved the network lifetime, stability and energy efficiency in heterogeneous WSNs.
R Lakshminarayanan et al.,[22] introduced a heterogeneous networking model based on two
parameters that are primary and secondary. Primary is the one in which heterogeneity level is
decided and secondary decides based on heterogeneity level. These are used in finding the
residual energy of the cluster heads. In this model, the node in the heterogeneous network has a
finite energy level based on the value of parameters. Evaluation of HEED protocol is done and
Multi-level HEED is also tested. The proposed system reduces the energy dissipation and
increases the network lifetime. C U Kumari et al., [23] have investigated a protocol for
minimizing energy consumption in enhancing the stability period and network lifetime. For
different scenarios in a heterogeneous network, Distributed Energy Efficient Clustering (DEEC)
and Threshold Distributed Energy Efficient Clustering (TDEEC) are considered. Comparison of
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the above protocols is done by varying the advanced nodes, super nodes, and fraction of both to
achieve network lifetime and stability period. Table I consists of some of the existing systems
with achievements and drawbacks.
S A Almogahed et al.,[24] have proposed a scheme in heterogeneous WSNs for prolonging the
network lifetime and stability period namely Optimized Distributed Energy Efficient Clustering
(ODEEC). This protocol modifies the probability function of heterogeneity and the cluster head
selection is optimized. In the proposed system, the network has two regions, the inner region, and
outer region, also cluster head selection is not based on the position of BS distance nor the
probabilities of heterogeneity. Authors achieved better performance in throughput, stability
period and network lifetime. B El Bhiri et al., [25] have proposed the Efficient Routing Protocol
for HWSN namely ERP-HWSN. In the proposed system, the cluster in the network has the
highest inter correlated sensors through which the spectral graph theory is considered in an
unbalanced graph. The result is to show the enhancement in network lifetime and compared with
DEEC.
2.1. Energy Consumption Model
Transmitter and Receiver are the main sections of communication. Energy is required for both the
sections, a sensor node having a transmitter section needs energy to run some circuits such as radio
electronics and amplifier. Whereas energy consumed by the receiver section in the packet over a
distance at radio electronics. The calculation of energy consumed is based on the free space energy
consumption model as the distance between the communication entities is less than the threshold
distance. If the distance is more than the threshold distance, then the multipath model is used. Data
aggregation is a feature for the consumption of energy which is implemented to CH and the data
collected by the cluster members is delivered to BS [26]. Energy consumed in the system is
calculating by the parameters Lp, a packet of length (number of bits), and distance ds as shown in
(1).
There are many significant parameters for processing the information. Eel is the consumed energy
by transmitting or receiving electronics circuitry. Two energies abbreviated as ET and ER, are the
transmitting and receiving energies consumed for processing a data packet LP. A scheme of digital
coding and modulation is used on which the parameters depend. Other parameters considered in
the system are Efsm and Empm, the energy needed for the free space model, and multipath model.
For calculating energy, the free space power loss model is considered if the distance d between
the source and destination is less than d0 controlled by the power amplifier with the information.
Transmitter with free space model need energy which is given as
ET(Lp, ds) = LpEel+ LpEfsmds
2
ds <<d0 (1)
Energy calculation using multipath model is given below in which distance ds is greater than the
threshold distance.
ET(Lp, ds) = LpEel+ LpEmpm ds
4
ds >>d0 (2)
Consumption of energy by the Receiver is,
ER(Lp, ds) = LpEel (3)
d0 can be calculated as,
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d0= √Efsm /√Empm (4)
3. EEC NETWORK MODEL
EEC is an energy-efficient clustering in the proposed network model which has sensor nodes
deployed randomly on NxN sensing layout and uses heterogeneity with three-level node energy.
After deployment, all the nodes and BS become static which is predefined. Links between each
node for communication is considered to be static. CH is responsible in the sensing network for
forwarding the data collected to BS directly. Data messages that are supervised or unsupervised
transacted through wireless links. The assumptions made in the network include, the similar
capabilities possessed by the nodes have unique id and different energy levels. The network is
divided into clusters based on the node population and has BS is stationary and located at the
middle of the network field. BS has a stable power supply without any memory restraints, energy,
or computation.
In the network, every node is capable of sensing, aggregating, and forwarding the data. It is
considered primarily that all the nodes have data to transfer always. Data aggregation is done by
the nodes which compress the multiple data packets into a single packet. Energy transmission is
regulated by the nodes with the receiving node distance and node failure is considered during the
node deletion.
3.1. Cluster Formation and Cluster Head Election
Clustering is a grouping of nodes having similar capabilities. The process of clustering and
information transmission consists of three stages such as Cluster arrangement and cluster head
selection, accumulating information, collecting and transmitting the information. Based on
residual energy of all the nodes, cluster head is selected and node density as per the protocol.
Residual energy is defined as the total remaining energy and its node density which can be
calculated within the sensing range. The highest residual energy node is chosen as a cluster head,
which transmits the data across the cluster head. All the sensor nodes receive a broadcast
messages by their respective cluster heads. Sensor nodes select the cluster head based on the
received signal energy and based on the maximum received energy the decision is sent to CH.
Acknowledgment is sent to all sensor nodes regarding the CHs decision. Generation of TDMA
signal and broadcasting is scheduled once the clusters are determined.
Finally, the energy levels of all the nodes are checked for proceeding to the next round and the
clusters having zero energy are removed from the network. After forming the clusters, the cluster
members in each cluster gather information and send it to their respective CH. Once the data is
collected by the CH, the information transmission stage occurs by sending the aggregated data to
the base station. The individuals in the group spend energies for gathering and sending the
information to their CHs.
3.2. Formation of Cluster Head and Rotation
Energy required for completing one round by CH is estimated as,
E(CHload,R_1)=CH(E1,R1,k)+CH(E1,A1,NCM)+CH(E1,T1,d1BS,k) (5)
In the above equation, E1, R1, T1, A1 and NCM abbreviate energy, receive aggregation and cluster
member nodes in a respective cluster in the first round of transmission. E (CHload, R1) is the
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energy required by CH for completing one round of transmission. CH (E1, R1, k) is the energy
consumed by CH for receiving the k-bits message. CH (E1, A1, NCM) stands for energy needed to
aggregate the data from Cluster members NCM. CH (E1, T1,d1BS, k) indicates the consumption of
energy to transmit the aggregated data to the base station.
CH (E1, R1,NCM)= NCM X (k X Eel) (6)
CH (E1, A1,NCM+1) = (NCM+1)𝑋(kXEA) (7)
CH (E1, T1,d1BS,k)=k X Eel+ kX ∈fsm X d1
2
BS if d1BS < d
kX∈mpm X d1
4
BS otherwise (8)
d has the threshold value.
Pre-requisites:
1. All nodes are updated with neighbor information which is location aware.
2. Deployment of nodes is done randomly.
3. Measure the clusters of sensor nodes in the area, cost of communication such as initial
energy levels and Probabilities of CH.
4. Neighbor sensors are found within the sensing range of clusters.
5. All the neighboring nodes should be updated with some information such as initial
energy level, residual energy of sensor nodes, CH probability and highest energy.
6. Cluster head selection is done by setting the probability.
7. In every round, nodes in each cluster are having data packets for transmission.
8. Attributes of all the nodes from each cluster will be sent to BS.
9. BS receives the information and updates and stores in the database.
10.Number of communication round completed successfully is estimated by CH before it
dies.
The above equations (6), (7), and (8) calculate the energy required for receiving the data from the
members in the cluster, aggregating the data with its data, and sending the aggregated data to the
BS. CH does the estimation of the number of communication rounds before it dies.
The estimation of the number of communication round is done by CH successfully before it dies
and given as,
CHE_R = floor (EiE_CH) / E(CHload,R_1) (9)
In the above equation (9), CHE_R is the number of rounds that CH completes before it dies, and
EiE_CH is the initial energy when the node becomes CH respectively.
Death of the CH is calculated as = ETi/ERi, where ETi is the total energy and ERi is the energy
required to complete one round by CH.
The dynamic threshold for CH-Rot is calculated by using equation (9) by estimating CHE_R. If
CHE_R >1, then CHE_R -1 is completed successfully by CH and again CH-Rot is triggered for
selecting CH. The CH is selected among cluster members based on residual energy. If CHE_R < 1,
then re-clustering is done. Cluster head rotation is given below in equation (10),
CHE_R -1 if CHE_R >1
CH-Rot= Re-clustering Otherwise (10)
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4. PROPOSED PROTOCOL
In this approach, energy-efficient clustering algorithm is introduced which consists of the
following stages: Arrangement of clusters, Decision of group head, Accumulation of information
and collection, and transmission of information It is necessary for selecting CHs based on initial
energy, residual energy, and one hop count. All the nodes of different energy levels are deployed
randomly over a network. Clusters are formed based on single-hop distance and neighbors are
calculated using the Euclidian distance formula. Energy levels of each node are calculated as
explained in the Energy consumption model. Once the energy levels of all the nodes are
calculated, first CH is found using high initial energy. In the next step, all other CHs are
calculated based on the energy and also by giving a condition of not including the CH already
found in other clusters. Totally 6 CHs are found in the network. During transmission, a particular
cluster is considered; CH is transmitting the data packets to the BS. Whereas other CHs remain
static as the transmission is not taking place within those clusters. Once the energy of CH that is
transmitting the data gets depleted, CH rotation takes place.
The scheme improves the utilization of energy and enhancing the remaining energy in the
network. Contention window-based protocol CSMA/CA at the MAC layer enhanced for collision
detection and avoidance for improving the faster transmission. Existing energy-efficient
clustering protocols have issues such as Cluster size inconsistency, and location of selected CH
towards the network boundary, and energy dissipation, affecting the network performance. After
the cluster round, the remaining energy of a node must be high enough to handle the role of CH
in the next upcoming rounds.
5. SIMULATION PARAMETERS
The parameters set for implementation are highlighted below and simulation work having
performance validation is explained.
Throughput: The amount of throughput per cluster round is defined as the number of data sent
towards the base station from the sensor nodes over the cluster round. So it is the total number of
data packets delivered at the destination node per unit time. It is measured in packets/second or
bits/second.
Energy Efficiency: Energy consumed per unit of successful communication is referred to as
Energy efficiency. It is defined as the ratio of throughput to the energy consumed.
Packet Delivery Ratio (PDR): PDR is the ratio of data packets delivered successfully to a
destination to the total number of data packets sent by the sender. It can be calculated by
considering the number of data packets sent and the number of received data packets.
End to End Delay:
The time taken for a data packet for transmission across a network from source to destination is
referred to as End to end delay. It differs from Round trip time (RTT) and it is common in
Internet Protocol network monitoring. The set of parameters utilized in implementing the
proposed work for the simulation is given in Table 1.
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Table 1: Simulation Parameters
Sl.No. Parameter
symbol
Description Value
1 N×N Network area 1300m* 1300m
2 N Number of nodes 100
3 MAC MAC protocol IEEE 802.11
4 E0 Initial energy of nodes 0.5–1.5 J
5 Lp Data packet size 4000 bits
6 Eel Radio electronics
energy
50 nJ/bit
7 Efsm Free space energy 10 pJ/bit/m2
8 Empm Amplification energy 0.0013 pJ/bit/m4
9 d0 Threshold distance 87–87.7m
10 Traffic Traffic Type CBR
11 Packet Size Packet Size 512 bytes
12 BS Sink node (145,125)
6. DISCUSSION
In this section, the implementation and results of the simulated work and the validation with
protocols like HEED and Rotating Energy Efficient Clustering for Heterogeneous Devices
(REECHD) concerning parameters set shown in Table II are focus on. In a Heterogeneous
Wireless Sensor Network, nodes are deployed randomly and the network is divided into clusters
based on the population of nodes. BS is placed at the center of the network and node 49 with
position (145, 125). A Number of nodes in the network is 100, and all the nodes are assigned with
different energy levels.
6.1. Validation with HEED Protocol
HEED [27] is a clustering protocol that produces equal-sized clusters. This algorithm has two
phases, clustering and network operation. In the clustering phase, CH is selected based on
residual energy, and member nodes that are close to the first CH, join the cluster. Data packets
get delivered from member nodes to BS in the operation phase. These two phrases get repeated
over time. This protocol prevents two nodes from becoming CHs within the same transmission
range. The Energy of sensor node gets depleted which is closest to the BS compared to the node
that is farther away.
6.2. Validation with REECHD Protocol
REECHD [28] is a clustering protocol that uses equal size clustering and rotation. For leader
election, this protocol combines node residual energy and node induced work. Intra traffic
communication is reduced by the strategy of cluster head selection by prolonging the lifetime of
the network. It defines the intra traffic communication limit accompanied by all clusters.
6.3. Simulation Results
6.3.1. Network Initialization
The proposed work uses the EEC algorithm having two phases, clustering phase, and operation
phase. The network is densely populated with 100 nodes having different energy levels. As
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shown in Figure 3, all the nodes are placed randomly in a network area. In a flat grid. The
parameters such as antenna type, link layer, queue type, routing protocol, and interface type are
set up.
Figure 3: Node deployment
6.3.2. Neighbor discovery
As shown in Figure 4, the neighbor nodes are found out by Euclidian distance by considering the
position of nodes i.e. (x, y) coordinates. The transmission range is set to 200m and the nodes that
fall in those ranges are considered. Each node should send Hello messages to find the position of
nodes.
Figure 4: Neighbor Node Discovery
6.3.3. Cluster Formation and CH selection
The Clusters are formed based on one-hop distance as shown in Figure. 5 which are equally sized
clusters. 100 nodes are deployed and 16 clusters are formed. Based on the high energy of nodes,
CH is selected and other member nodes in the cluster have the feature of BCMF.
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Communication overhead of CH is reduced by these CMs as the maximum flow of data packets
takes place.
Figure 5: Formation of Cluster and CH selection
6.3.4. Energy Calculation
As shown in Figure 6, all the nodes are grouped into clusters. Energy calculation is done for all
the nodes as explained in the above algorithm section. The initial energy is considered between
0.5–1.5 J. Source and destination nodes are fixed by considering the Sink as the destination node.
Figure 6: Energy calculation of nodes
7. PERFORMANCE ANALYSIS
The proposed system is implemented using NS-2.35 and compared with HEED and REECHD to
compare the network performance in terms of parameters such as energy efficiency, throughput,
delay, and PDR. HWSN is considered by deploying 100 nodes on a grid size considered.
Following are the parameters considered in the proposed system with graphs and values.
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7.1. Energy Graph
As shown in the below Figure. 7, the proposed system uses a clustering algorithm that calculates
the CH based on the high energy. CHs of all clusters are calculated subsequently by neglecting
the cluster whose CH is already found. CHs of all clusters in the network are identified.
Figure. 7: Energy Graph
During transmission, the particular cluster is considered; CH is transmitting the data packets to
the BS. Whereas other CHs remain static as the transmission is not taking place within those
clusters. This saves the energy for all other clusters as they are not part of a transmission. CH
rotation takes place when the energy of CH which is transmitting gets depleted. Consumption of
energy reduces during CH selection and transmission. Table 2 shows the values of the proposed
system of energy consumption during transmission and compared with the existing system with
HEED and REECHD. Energy consumption values are taken by considering the number of sensor
nodes on the X-axis and Energy in the joule along the Y-axis. Consumption of energy in the EEC
system is 13.9 joules whereas the energy consumed is more in the existing systems.
Table 2: Energy Values of Proposed and Existing Systems
Sensor
Nodes
Energy Consumption
(in joule)
HEED[29] REECHD[30] EEC(Proposed)
0 0 0 0
10 12.90 11.25 9.4
20 13.38 12.38 9.6
30 14.01 12.95 10.1
40 14.32 13.25 10.8
50 15.24 13.90 11.3
60 15.98 14.20 11.8
70 16.12 14.90 12.3
80 16.67 15.01 12.7
90 16.12 15.29 13.1
100 16.72 15.02 13.9
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7.2. Packet Delivery Ratio
Figure 8 shows the PDR of both existing and proposed systems. It is the ratio of no. of packets
obtained at the receiver to the total no. of packets including the packet drop. In the proposed
system, the PDR is achieved with better value as the MAC layer is tuned up with parameters such
as CSMA for detecting the collision and the contention window is maximized for faster
transmission.
Figure. 8: Packet Delivery Ratio
The physical transmission range is also extended for making the transmission faster. The packet
drop is minimized in the proposed system compared to the existing one. Below Table 3 shows the
values of the proposed and existing systems of PDR. The proposed system achieves a better
packet delivery ratio of about 90%, whereas the existing system has 85% and 86%. The graph is
plotted taking sensor nodes and PDR on X-axis and Y-axis.
Table 3. PDR Values of Proposed and Existing Systems
Sensor
Nodes
PDR
(Ratio in %x10-3
)
HEED[29] REECHD[30] EEC(Proposed)
0 0 0 0
10 0.30 0.40 0.42
20 0.32 0.49 0.49
30 0.43 0.50 0.51
40 0.47 0.58 0.55
50 0.51 0.62 0.61
60 0.56 0.69 0.67
70 0.68 0.72 0.70
80 0.74 0.79 0.76
90 0.80 0.83 0.83
100 0.85 0.86 0.90
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7.3. End to End Delay
This is the parameter that gives the overall delay in time that the data packets suffer during
transmission from source to destination across the network. The overall delay includes queuing
delay, propagation delay, and end system processing delays. Packets are lost when it gets delayed
longer than the threshold value. Figure. 9 shows End to end delay of both proposed and existing
systems. The values of End to End Delay for the proposed and existing system are given in Table
4.
Figure. 9: End to End Delay
Delay in the proposed is minimum compared to the existing system due to the clustering protocol
as it selects the CH at once and using a congestion window based algorithm enhanced at the
MAC layer. Delay is reduced by 50% in the EEC system compared to REECHD which is high
that is 1.060 microseconds.
Table 4. Delay Values of Proposed and Existing Systems
Sensor
Nodes
End to End Delay
(In Micro seconds)
HEED[29] REECHD[30] EEC(Proposed)
0 0 0 0
10 0.567 0.545 0.260
20 0.642 0.615 0.287
30 0.681 0.695 0.312
40 0.723 0.700 0.332
50 0.782 0.740 0.392
60 0.812 0.800 0.456
70 0.876 0.870 0.493
80 0.985 0.900 0.532
90 1.145 1.005 0.567
100 1.253 1.060 0.608
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7.4. Throughput
The no. of data packets delivered from source to destination in a specific period time is the
Throughput. It is affected by many factors such as routers and cables, congestion, and packet
loss. In the proposed system, the number of packets sent is 590. The MAC layer is enhanced
with contention window-based algorithm which tunes some of the parameters like the contention
window size. Figure 10 shows the throughput graph of both proposed and existing systems by
plotting sensor nodes and throughput in kb/s.
Figure. 10: Throughput
Below Table 5 have throughput values with a comparison with HEED and REECHD. In the EEC
system, the decongestion method is incorporated in the MAC layer. Better throughput is achieved
in EEC as the system is initiated with a data rate of 11mbps and frequency of 2.4 GHz. EEC
system achieves by sending 370 data packets to the sink node.
Table 5. Throughput Values of Proposed and Existing Systems
Sensor
Nodes
Throughput
(kbps)
HEED[29] REECHD[30] EEC(Proposed)
0 0 0 0
10 124 135 149
20 138 140 165
30 143 149 187
40 160 169 210
50 182 195 254
60 196 210 273
70 210 245 290
80 233 296 320
90 260 302 350
100 283 355 370
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8. CONCLUSIONS
An important research area is saving energy in communication media. Many existing systems
having energy-efficient mechanims have been surveyed. It is very difficult to employ a particular
type of mechanisms to save energy due to a wide range of network applications. MAC uses many
approaches to improve the performance by saving energy. In the proposed system, Energy
Efficient Clustering (EEC) is presented for HWSNs which is a clustering protocol that uses CH
rotation. EEC operates in electing the leader and rotation by combining the node higher energy
and node induced work. Intra traffic communication is reduced by this CH selection strategy thus
extending the network lifetime. Contention window-based algorithm is enhanced in the MAC
layer for decongestion thereby increasing the throughput and reducing the delay.EEC is more
energy efficient compared to HEED and REECHD. In the future, many strategies to experiment
with various member selections for the formation of cluster by incorporating unequal-sized
clustering can be done.
CONFLICTS OF INTEREST
The authors declare no conflict of interest.
ACKNOWLEDGMENTS
The authors would like to thank all the staff of the Department of Telecommunication
Engineering, Principal, Dr. Ambedkar Institute of Technology for the support given and also
thankful to Technical Education Quality Improvement Programme (TEQIP-III) for providing
financial support.
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