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.
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.
ENERGY CONSUMPTION IMPROVEMENT OF TRADITIONAL CLUSTERING METHOD IN WIRELESS S...IJCNCJournal
In the traditional clustering routing protocol of wireless sensor network, LEACH protocol (Low Energy
Adaptive Clustering Hierarchy) is considered to have many outstanding advantages in the implementation
of the hierarchy according to low energy adaptive cluster to collect and distribute the data to the base
station. The main objective of LEACH is: To prolong life time of the network, reduce the energy
consumption by each node, using the data concentration to reduce bulletins in the network. However, in the
case of large network, the distance from the nodes to the base station is very different. Therefore, the
energy consumption when becoming the host node is very different but LEACH is not based on the
remaining energy to choose the host node, which is based on the number of times to become the host node
in the previous rounds. This makes the nodes far away from the base station lose power sooner.
In this paper, we give a new routing protocol based on the LEACH protocol in order to improve operating
time of sensor network by considering energy issues and distance in selecting the cluster-head (CH), at that
time the nodes with high energy and near the base station (BS) will have a greater probability of becoming
the cluster-head than the those in far and with lower energy.
WIRELESS SENSOR NETWORK CLUSTERING USING PARTICLES SWARM OPTIMIZATION FOR RED...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality. The most important issue in this type of networks is energy constraints. In this area several researches have been done from which clustering is one of the most effective solutions. The goal of clustering is to divide network into sections each of which has a cluster head (CH). The task of cluster heads collection, data aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF, PSO-MV) in terms of network lifetime and energy consumption.
In network aggregation using efficient routing techniques for event driven se...IJCNCJournal
Sensors used in applications such as agriculture, weather , etc., monitoring physical parameters like soil moisture, temperature, humidity, will have to sustain their battery power for long intervals of time. In order to accomplish this, parameter which assists in reducing the consumption of power from battery need to be attended to. One of the factors affecting the consumption of energy is transmit and receive power. This energy consumption can be reduced by avoiding unnecessary transmission and reception. Efficient routing techniques and incorporating aggregation whenever possible can save considerable amount of energy. Aggregation reduces repeated transmission of relative values and also reduces lot of computation at the base station. In this paper, the benefits of aggregation over direct transmission in saving the amount of energy consumed is discussed. Routing techniques which assist aggregation are incorporated. Aspects like transmission of average value of sensed data around an area of the network, minimum value in the whole of the network, triggering of event when there is low battery are assimilated.
Communication Cost Reduction by Data Aggregation: A SurveyIJMTST Journal
Wireless Sensor Networks have gained wide popularity in the recent years for its high-ranking applications such as remote environment monitoring, target tracking, safety-critical monitoring etc. However Wireless Sensor Networks face many constraints like low computational power, small storage, and limited energy resources. One of the important issues in wireless sensor network is to increase the network lifetime to keep the network operational as long as possible. In this survey paper, we provide a comprehensive review of the existing literature on techniques and protocols for data aggregation to reduce communication cost and increase network lifetime in wireless sensor networks.
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.
ENERGY CONSUMPTION IMPROVEMENT OF TRADITIONAL CLUSTERING METHOD IN WIRELESS S...IJCNCJournal
In the traditional clustering routing protocol of wireless sensor network, LEACH protocol (Low Energy
Adaptive Clustering Hierarchy) is considered to have many outstanding advantages in the implementation
of the hierarchy according to low energy adaptive cluster to collect and distribute the data to the base
station. The main objective of LEACH is: To prolong life time of the network, reduce the energy
consumption by each node, using the data concentration to reduce bulletins in the network. However, in the
case of large network, the distance from the nodes to the base station is very different. Therefore, the
energy consumption when becoming the host node is very different but LEACH is not based on the
remaining energy to choose the host node, which is based on the number of times to become the host node
in the previous rounds. This makes the nodes far away from the base station lose power sooner.
In this paper, we give a new routing protocol based on the LEACH protocol in order to improve operating
time of sensor network by considering energy issues and distance in selecting the cluster-head (CH), at that
time the nodes with high energy and near the base station (BS) will have a greater probability of becoming
the cluster-head than the those in far and with lower energy.
WIRELESS SENSOR NETWORK CLUSTERING USING PARTICLES SWARM OPTIMIZATION FOR RED...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality. The most important issue in this type of networks is energy constraints. In this area several researches have been done from which clustering is one of the most effective solutions. The goal of clustering is to divide network into sections each of which has a cluster head (CH). The task of cluster heads collection, data aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF, PSO-MV) in terms of network lifetime and energy consumption.
In network aggregation using efficient routing techniques for event driven se...IJCNCJournal
Sensors used in applications such as agriculture, weather , etc., monitoring physical parameters like soil moisture, temperature, humidity, will have to sustain their battery power for long intervals of time. In order to accomplish this, parameter which assists in reducing the consumption of power from battery need to be attended to. One of the factors affecting the consumption of energy is transmit and receive power. This energy consumption can be reduced by avoiding unnecessary transmission and reception. Efficient routing techniques and incorporating aggregation whenever possible can save considerable amount of energy. Aggregation reduces repeated transmission of relative values and also reduces lot of computation at the base station. In this paper, the benefits of aggregation over direct transmission in saving the amount of energy consumed is discussed. Routing techniques which assist aggregation are incorporated. Aspects like transmission of average value of sensed data around an area of the network, minimum value in the whole of the network, triggering of event when there is low battery are assimilated.
Communication Cost Reduction by Data Aggregation: A SurveyIJMTST Journal
Wireless Sensor Networks have gained wide popularity in the recent years for its high-ranking applications such as remote environment monitoring, target tracking, safety-critical monitoring etc. However Wireless Sensor Networks face many constraints like low computational power, small storage, and limited energy resources. One of the important issues in wireless sensor network is to increase the network lifetime to keep the network operational as long as possible. In this survey paper, we provide a comprehensive review of the existing literature on techniques and protocols for data aggregation to reduce communication cost and increase network lifetime in wireless sensor networks.
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
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.
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.
A COST EFFECTIVE COMPRESSIVE DATA AGGREGATION TECHNIQUE FOR WIRELESS SENSOR N...ijasuc
In wireless sensor network (WSN) there are two main problems in employing conventional compression
techniques. The compression performance depends on the organization of the routes for a larger extent.
The efficiency of an in-network data compression scheme is not solely determined by the compression
ratio, but also depends on the computational and communication overheads. In Compressive Data
Aggregation technique, data is gathered at some intermediate node where its size is reduced by applying
compression technique without losing any information of complete data. In our previous work, we have
developed an adaptive traffic aware aggregation technique in which the aggregation technique can be
changed into structured and structure-free adaptively, depending on the load status of the traffic. In this
paper, as an extension to our previous work, we provide a cost effective compressive data gathering
technique to enhance the traffic load, by using structured data aggregation scheme. We also design a
technique that effectively reduces the computation and communication costs involved in the compressive
data gathering process. The use of compressive data gathering process provides a compressed sensor
reading to reduce global data traffic and distributes energy consumption evenly to prolong the network
lifetime. By simulation results, we show that our proposed technique improves the delivery ratio while
reducing the energy and delay
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
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.
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.
CONSENSUS BASED DATA AGGREGATION FOR ENERGY CONSERVATION IN WIRELESS SENSOR N...ijdpsjournal
Our planet is abundant with raw data and to monitor the available data properly, processing of the enormous raw data is very vital. One of the key things in development of mankind and the nature is to acquire as much data as possible and to react appropriately in accordance with the studied data. It’s nothing but diagnosis of the physical world by studying the data acquired from them in order to take proper measures that can help in treating them better. Large volume of data incurs high energy consumption for its transmission and thus results in decrease of overall network lifetime.
Wireless Sensor Network (WSN) is a collection of multiple sensor nodes that all together forms a network for transmitting data acquired by each sensor node to sink known as Base Station (BS). In hierarchical routing acquired data are sent via relay agents like Cluster Heads (CH). The Cluster Heads must be customised with computations and formulations, which will help in aggregating the gathered data, in order to reduce energy consumption while transmitting the data further in the network while maintaining the data integrity to withhold the significance of every single value in a data set.
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 EFFICIENT AGGREGATION WITH DIVERGENT SINK PLACEMENT FOR WIRELESS SENSO...ijasuc
In WSN the data aggregation is a means for condensing the energy requirement by reducing number of
transmission by combining the data and sending the final required result to the base station. The lifetime
of the WSN can be improved by employing the aggregation techniques. During the process of aggregation
the numbers of transmission are reduced by combining the similar data from the nearby areas. By using
the clustering technique and aggregating the correlated data greatly minimize the energy consumed in
collecting and disseminating the data. In this work, we evaluate the performance of a novel energy
efficient cluster based aggregation protocol (EECAP) for WSN. The main focus in this proposed work is
to study the performance of our proposed aggregation protocol with divergent sink placements such as
when sink is at the centre of the sensing field, corner of the sensing field or at a location selected
randomly in the sensor field. We present experimental results by calculating the lifetime of network in
terms of number of sensing rounds using various parameters such as – average remaining energy of
nodes, number of dead nodes after the specified number of sensing rounds. Finally the performance of
various aggregation algorithms such as LEACH, SEP and our proposed aggregation protocol (EECAP)
are compared with divergent sink placements. The simulation results demonstrates that EECAP exhibits
good performance in terms of lifetime and the energy consumption of the wireless sensor networks and
which can be as equally compared with existing clustering protocols.
Smart parking is common in contemporary cities. These smart parking lots are outfitted mostly with wireless sensor networks (WSNs), which are used to detect, monitor, and collect data on the availability status of all existing parking spaces in a given area. Sensors make up WSN, which may gather, process, and transmit informations to the sink. However, the power and
communication limitations of the sensors have an effect on the performance and quality of the WSNs. The decrease in the battery and the energy of the
nodes causes a decrease in the life of the nodes and also of the entire WSN network. In this article, we present a routing protocol that implements an
efficient and robust algorithm allowing the creation of clusters so that the base station can receive data from the entire WSN network. This protocol
adopts a reliable and efficient algorithm allowing to minimize the energy dissipation of the sensors and to increase the lifetime of the WSN. In
comparison to alternative parking lot management protocols already in use,
the simulation results of the proposed protocol are effective and robust in terms of power consumption, data transmission reliability, and WSN network longevity.
Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Net...IJCNCJournal
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.
DESIGNING AN ENERGY EFFICIENT CLUSTERING IN HETEROGENEOUS WIRELESS SENSOR NET...IJCNCJournal
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.
Clustering and data aggregation scheme in underwater wireless acoustic sensor...TELKOMNIKA JOURNAL
Underwater Wireless Acoustic Sensor Networks (UWASNs) are creating attentiveness in
researchers due to its wide area of applications. To extract the data from underwater and transmit to
watersurface, numerous clustering and data aggregation schemes are employed. The main objectives of
clustering and data aggregation schemes are to decrease the consumption of energy and prolong the
lifetime of the network. In this paper, we focus on initial clustering of sensor nodes based on their
geographical locations using fuzzy logic. The probability of degree of belongingness of a sensor node to its
cluster, along with number of clusters is analysed and discussed. Based on the energy and distance the
cluster head nodes are determined. Finally using using similarity function data aggregation is analysed and
discussed. The proposed scheme is simulated in MATLAB and compared with LEACH algorithm.
The simulation results indicate that the proposed scheme performs better in maximizing network lifetime
and minimizing energy consumption.
CBHRP: A Cluster Based Routing Protocol for Wireless Sensor NetworkCSEIJJournal
A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol
(CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster
head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to
collect information from target field. On rotation basis, a head-set member receives data from the neighbor
nodes and transmits the aggregated results to the distance base station. This protocol reduces energy
consumption quite significantly and prolongs the life time of sensor network. It is found that CBHRP
performs better than other well accepted hierarchical routing protocols like LEACH in term of energy
consumption and time requirement.
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
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.
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.
A COST EFFECTIVE COMPRESSIVE DATA AGGREGATION TECHNIQUE FOR WIRELESS SENSOR N...ijasuc
In wireless sensor network (WSN) there are two main problems in employing conventional compression
techniques. The compression performance depends on the organization of the routes for a larger extent.
The efficiency of an in-network data compression scheme is not solely determined by the compression
ratio, but also depends on the computational and communication overheads. In Compressive Data
Aggregation technique, data is gathered at some intermediate node where its size is reduced by applying
compression technique without losing any information of complete data. In our previous work, we have
developed an adaptive traffic aware aggregation technique in which the aggregation technique can be
changed into structured and structure-free adaptively, depending on the load status of the traffic. In this
paper, as an extension to our previous work, we provide a cost effective compressive data gathering
technique to enhance the traffic load, by using structured data aggregation scheme. We also design a
technique that effectively reduces the computation and communication costs involved in the compressive
data gathering process. The use of compressive data gathering process provides a compressed sensor
reading to reduce global data traffic and distributes energy consumption evenly to prolong the network
lifetime. By simulation results, we show that our proposed technique improves the delivery ratio while
reducing the energy and delay
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
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.
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.
CONSENSUS BASED DATA AGGREGATION FOR ENERGY CONSERVATION IN WIRELESS SENSOR N...ijdpsjournal
Our planet is abundant with raw data and to monitor the available data properly, processing of the enormous raw data is very vital. One of the key things in development of mankind and the nature is to acquire as much data as possible and to react appropriately in accordance with the studied data. It’s nothing but diagnosis of the physical world by studying the data acquired from them in order to take proper measures that can help in treating them better. Large volume of data incurs high energy consumption for its transmission and thus results in decrease of overall network lifetime.
Wireless Sensor Network (WSN) is a collection of multiple sensor nodes that all together forms a network for transmitting data acquired by each sensor node to sink known as Base Station (BS). In hierarchical routing acquired data are sent via relay agents like Cluster Heads (CH). The Cluster Heads must be customised with computations and formulations, which will help in aggregating the gathered data, in order to reduce energy consumption while transmitting the data further in the network while maintaining the data integrity to withhold the significance of every single value in a data set.
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 EFFICIENT AGGREGATION WITH DIVERGENT SINK PLACEMENT FOR WIRELESS SENSO...ijasuc
In WSN the data aggregation is a means for condensing the energy requirement by reducing number of
transmission by combining the data and sending the final required result to the base station. The lifetime
of the WSN can be improved by employing the aggregation techniques. During the process of aggregation
the numbers of transmission are reduced by combining the similar data from the nearby areas. By using
the clustering technique and aggregating the correlated data greatly minimize the energy consumed in
collecting and disseminating the data. In this work, we evaluate the performance of a novel energy
efficient cluster based aggregation protocol (EECAP) for WSN. The main focus in this proposed work is
to study the performance of our proposed aggregation protocol with divergent sink placements such as
when sink is at the centre of the sensing field, corner of the sensing field or at a location selected
randomly in the sensor field. We present experimental results by calculating the lifetime of network in
terms of number of sensing rounds using various parameters such as – average remaining energy of
nodes, number of dead nodes after the specified number of sensing rounds. Finally the performance of
various aggregation algorithms such as LEACH, SEP and our proposed aggregation protocol (EECAP)
are compared with divergent sink placements. The simulation results demonstrates that EECAP exhibits
good performance in terms of lifetime and the energy consumption of the wireless sensor networks and
which can be as equally compared with existing clustering protocols.
Smart parking is common in contemporary cities. These smart parking lots are outfitted mostly with wireless sensor networks (WSNs), which are used to detect, monitor, and collect data on the availability status of all existing parking spaces in a given area. Sensors make up WSN, which may gather, process, and transmit informations to the sink. However, the power and
communication limitations of the sensors have an effect on the performance and quality of the WSNs. The decrease in the battery and the energy of the
nodes causes a decrease in the life of the nodes and also of the entire WSN network. In this article, we present a routing protocol that implements an
efficient and robust algorithm allowing the creation of clusters so that the base station can receive data from the entire WSN network. This protocol
adopts a reliable and efficient algorithm allowing to minimize the energy dissipation of the sensors and to increase the lifetime of the WSN. In
comparison to alternative parking lot management protocols already in use,
the simulation results of the proposed protocol are effective and robust in terms of power consumption, data transmission reliability, and WSN network longevity.
Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Net...IJCNCJournal
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.
DESIGNING AN ENERGY EFFICIENT CLUSTERING IN HETEROGENEOUS WIRELESS SENSOR NET...IJCNCJournal
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.
Clustering and data aggregation scheme in underwater wireless acoustic sensor...TELKOMNIKA JOURNAL
Underwater Wireless Acoustic Sensor Networks (UWASNs) are creating attentiveness in
researchers due to its wide area of applications. To extract the data from underwater and transmit to
watersurface, numerous clustering and data aggregation schemes are employed. The main objectives of
clustering and data aggregation schemes are to decrease the consumption of energy and prolong the
lifetime of the network. In this paper, we focus on initial clustering of sensor nodes based on their
geographical locations using fuzzy logic. The probability of degree of belongingness of a sensor node to its
cluster, along with number of clusters is analysed and discussed. Based on the energy and distance the
cluster head nodes are determined. Finally using using similarity function data aggregation is analysed and
discussed. The proposed scheme is simulated in MATLAB and compared with LEACH algorithm.
The simulation results indicate that the proposed scheme performs better in maximizing network lifetime
and minimizing energy consumption.
CBHRP: A Cluster Based Routing Protocol for Wireless Sensor NetworkCSEIJJournal
A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol
(CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster
head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to
collect information from target field. On rotation basis, a head-set member receives data from the neighbor
nodes and transmits the aggregated results to the distance base station. This protocol reduces energy
consumption quite significantly and prolongs the life time of sensor network. It is found that CBHRP
performs better than other well accepted hierarchical routing protocols like LEACH in term of energy
consumption and time requirement.
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.
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.
Energy efficient clustering in heterogeneousIJCNCJournal
Cluster head election is a key technique used to reduce energy consumption and enhancing the throughput
of wireless sensor networks. In this paper, a new energy efficient clustering (E2C) protocol for
heterogeneous wireless sensor networks is proposed. Cluster head is elected based on the predicted
residual energy of sensors, optimal probability of a sensor to become a cluster head, and its degree of
connectivity as the parameters. The probability threshold to compete for the role of cluster head is derived.
The probability threshold has been extended for multi-levels energy heterogeneity in the network. The
proposed E2C protocol is simulated in MATLAB. Results obtained in the simulationshowthat performance
of the proposed E2Cprotocol is betterthan stable election protocol (SEP), and distributed energy efficient
clustering (DEEC) protocol in terms of energy consumption, throughput, and network lifetime.
Wireless sensor networks, clustering, Energy efficient protocols, Particles S...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality.
The most important issue in this type of networks is energy constraints. In this area several researches have
been done from which clustering is one of the most effective solutions. The goal of clustering is to divide
network into sections each of which has a cluster head (CH). The task of cluster heads collection, data
aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach
for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal
fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual
energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation
results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF,
PSO-MV) in terms of network lifetime and energy consumption.
Energy Efficient Techniques for Data aggregation and collection in WSNIJCSEA Journal
A multidisciplinary research area such as wireless sensor networks (WSN) have been invoked the monitoring of remote physical environment and are used for a wide range of applications ranging from defense personnel to many scientific research, statistical application, disaster area and War Zone. These networks are constraint with energy, memory and computing power enhance efficient techniques are needed for data aggregation, data collection, query processing, decision making and routing in sensor networks. The problem encountered in the recent past was of the more battery power consumption as activity increases, need more efficient data aggregation and collection techniques with right decision making capabilities. Therefore, this paper proposed the efficient and effective architecture and mechanism of energy efficient techniques for data aggregation and collection in WSN using principles like global weight calculation of nodes, data collection for cluster head and data aggregation techniques using data cube aggregation.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In recent years, applications of wireless sensor networks have evolved in many areas such as target
tracking, environmental monitoring, military and medical applications. Wireless sensor network
continuously collect and send data through sensor nodes from a specific region to a base station. But, data
redundancy due to neighbouring sensors consumes energy, compromising the network lifetime. In order to
improve the network lifetime, a novel cluster based local route search method, called, Greedy Cluster-
based Routing (GCR) technique in wireless sensor network. The proposed GCR method uses arbitrary
timer in order to participate cluster head selection process with maximum neighbour nodes and minimum
distance between the source and base station. GCR constructs dynamic routing improving the rate of
network lifetime through Mass Proportion value. Also, GCR uses a greedy route finding strategy for
balancing energy consumption. Experimental results show that GCR achieves significant energy savings
and prolong network lifetime
A Review Paper on Power Consumption Improvements in WSNIJERA Editor
Wireless Sensor network (WSN) is a network of low-cost, low-power, multifunctional, small
size sensor nodes which are densely deployed inside a physical environment to collect, process and transmit the
information to sink node. As Sensor nodes are generally battery-powered, it is necessary to balance between
power consumption and energy storage capacity to sustain sensor node's operational life. Therefore one of the
important challenge in WSN is to improve power consumption efficiently to prolong network lifetime by
minimizing the amount of data transmissions throughout the network and maximizing node's low power
residence time. In this paper, two energy optimization techniques, Cluster-Based energy efficient routing
(CBER) scheme and extension to IEEE 802.15.4 standard by dynamic rate adaption and control for energy
reduction (DRACER) protocol for wireless sensor networks has been reviewed. CBER technique increases
network lifetime by reducing Hot Spot problem and end-to-end energy consumption using multi-hop wireless
routing whereas DRACER protocol reduces network latency and average power consumption by minimizing
network overhead using automatic data rate selection process. So, both of these techniques, if utilized in
combination, it is possible to achieve very high energy efficiency in WSN
GREEDY CLUSTER BASED ROUTING FOR WIRELESS SENSOR NETWORKSijcsit
In recent years, applications of wireless sensor networks have evolved in many areas such as target tracking, environmental monitoring, military and medical applications. Wireless sensor network continuously collect and send data through sensor nodes from a specific region to a base station. But, data redundancy due to neighbouring sensors consumes energy, compromising the network lifetime. In order to improve the network lifetime, a novel cluster based local route search method, called, Greedy Clusterbased Routing (GCR) technique in wireless sensor network. The proposed GCR method uses arbitrary timer in order to participate cluster head selection process with maximum neighbour nodes and minimum distance between the source and base station. GCR constructs dynamic routing improving the rate of network lifetime through Mass Proportion value. Also, GCR uses a greedy route finding strategy for
balancing energy consumption. Experimental results show that GCR achieves significant energy savings and prolong network lifetime.
In recent years, applications of wireless sensor networks have evolved in many areas such as target tracking, environmental monitoring, military and medical applications. Wireless sensor network continuously collect and send data through sensor nodes from a specific region to a base station. But, data redundancy due to neighbouring sensors consumes energy, compromising the network lifetime. In order to improve the network lifetime, a novel cluster based local route search method, called, Greedy Clusterbased Routing (GCR) technique in wireless sensor network. The proposed GCR method uses arbitrary timer in order to participate cluster head selection process with maximum neighbour nodes and minimum distance between the source and base station. GCR constructs dynamic routing improving the rate of network lifetime through Mass Proportion value. Also, GCR uses a greedy route finding strategy for balancing energy consumption. Experimental results show that GCR achieves significant energy savings and prolong network lifetime.
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.
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.
Mobile Agents based Energy Efficient Routing for Wireless Sensor NetworksEswar Publications
Energy Efficiency and prolonged network lifetime are few of the major concern areas. Energy consumption rated of sensor nodes can be reduced in various ways. Data aggregation, result sharing and filtration of aggregated data among sensor nodes deployed in the unattended regions have been few of the most researched areas in the field of wireless sensor networks. While data aggregation is concerned with minimizing the information transfer from source to sink to reduce network traffic and removing congestion in network, result sharing focuses on sharing of information among agents pertinent to the tasks at hand and filtration of aggregated data so as to remove redundant information. There exist various algorithms for data aggregation and filtration using different mobile agents. In this proposed work same mobile agent is used to perform both tasks data aggregation and data filtration. This approach advocates the sharing of resources and reducing the energy consumption level of sensor nodes.
Similar to DATA GATHERING ALGORITHMS FOR WIRELESS SENSOR NETWORKS: A SURVEY (20)
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DATA GATHERING ALGORITHMS FOR WIRELESS SENSOR NETWORKS: A SURVEY
1. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.1, No.4, December 2010
DOI : 10.5121/ijasuc.2010.1410 102
DATA GATHERING ALGORITHMS FOR
WIRELESS SENSOR NETWORKS: A SURVEY
K.Ramanan1
and E.Baburaj2
1
Lecturer, Sun college of Engineering and Technology, Nagercoil.
ramana3483@gmail.com
2
Professor, Sun college of Engineering and Technology, Nagercoil.
alanchybabu@gmail.com
ABSTRACT
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.
KEYWORDS
Data gathering, power aware, energy, life time,
1. INTRODUCTION
With the introduction of low-cost processor, memory, and radio technologies, it becomes
possible to build inexpensive wireless micro-sensor nodes. Although these sensors are not so
powerful compared to their expensive macro-sensor counterparts, by using hundreds or
thousands of them it is possible to build a high quality, fault-tolerant sensor network. These
networks can be used to collect useful information from an area of interest, especially where the
physical environment is so harsh that the macro-sensor counterparts cannot be deployed. They
have a wide range of applications[18], from military to civil, that may be realized by using
different type of sensor devices with different capabilities for different kinds of environments
[12]. The main constraint of sensor nodes is their very low finite battery energy, which limits
the lifetime and the quality of the network [16]. For that reason, the protocols running on sensor
networks must consume the resources of the nodes efficiently in order to achieve a longer
network lifetime. There is an ongoing research on power management issues in order to reduce
2. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.1, No.4, December 2010
103
the power consumption[2][21] when the nodes become idle. When power efficient
communication is considered, it is important to maximize the nodes’ lifetimes, reduce
bandwidth requirements by using local collaboration among the nodes, and tolerate node
failures, besides delivering the data efficiently.
Data gathering protocols are formulated for configuring the network and collecting information
from the desired environment [20]. In each round of the data gathering protocol, data from the
nodes need to be collected and transmitted to (BS)[13], where from the end user can access the
data. A simple way of doing that is aggregating (sum, average, min, max, count) the data
originating from different nodes[18]. A more elegant solution is data fusion which can be
defined as combination of several unreliable data measurements to produce a more accurate
signal by enhancing the common signal and reducing the uncorrelated noise. Sensor nodes use
different data aggregation techniques to achieve energy efficiency. The aim is efficient
transmission of all the data to the base station so that the lifetime of the network is maximized
in terms of rounds, where a round is defined as the process of gathering all the data from sensor
nodes to the base station, regardless of how much time it takes. Existing data gathering
protocol[21] can be classified in to different categories based on the network structure and
protocol operation based on routing protocols[13][17] that aim at power-saving and prolonging
network lifetime are intensively studied in research community[14][19].
2. PRELIMINARIES
This section presents the assumptions and radio model of the network under consideration [10].
2.1 Assumptions
A Fixed network which includes in mobile sensor nodes[4] and base station is considered in our
study with the following assumptions [9].
• The network is considered homogeneous and all of the sensor nodes have the same
initial energy.
• Each sensor node knows its own geographical position.
• All nodes measure the environmental parameters at a fixed rate and send it periodically
to the receiver nodes[18].
• The radio channel is symmetric such that energy consumption of data transmission from
node A to node B is the same as that of transmission from node B to node A.
Each sensor nodes can operate either in sensing mode to monitor the environment parameters
and transmit to the base station or cluster head mode to gather data, compress it and forward to
the BS[13].
2.2 scheme for Radio energy
Sensor node main components and associated energy consumption are shown in Fig.1. Both
the free space and multipath fading channel models[24] mentioned in to compute energy
dissipated during the process of transmitting and receiving information[10] are used. The
energy consumption for transmitting an l bit message over a distance d is
0
2
,
*
*
* d
d
d
l
E
l
E
E fs
elec
Tx <
+
=
3. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.1, No.4, December 2010
104
0
4
,
*
*
* d
d
d
l
Emp
l
E
E elec
Tx ≥
+
=
and for receiving this message respectively is:
l
E
E elec
RX *
=
Where Eelec is the energy spent to operate the transceiver circuit, Efs and Emp are the
energy expenditure of transmitting one bit data to achieve an acceptable bit error rate and is
dependent on the distance of transmission in the case of free space model and multipath fading
model[17]. If the transmission distance is less than a threshold d0, the free space model is
applied; otherwise, the multipath model is used. The threshold d0 is calculated as
mp
fs E
E
d /
0 =
Figure 1. Sensor node peripherals and Energy Consumption for Data Aggregation
.
3. REVIEW OF DATA GATHERING TECHNIQUES
The powerful underlying and enabling concept is data gathering in wireless sensor networks –
delivery of data by an integrated and orchestrated suit of algorithms [8][11][22][29].
3.1 Energy-efficient Routing Algorithm to Prolong Lifetime
Energy-efficient Routing Algorithm to Prolong Lifetime (ERAPL) was proposed by Yi-hua
Zhu, et al [27], in which able to dramatically prolong network lifetime while efficiently
expends energy[3]. In the ERAPL, a data gathering sequence (DGS), used to avoid mutual
transmission and loop transmission among nodes, is constructed, and each node proportionally
transmits traffic to the links confined in the DGS. In addition, a mathematical programming
model, in which minimal remaining energy of nodes and total energy consumption are
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105
included, and is presented to optimize network lifetime. Moreover, genetic algorithms are used
to find the optimal solution of the proposed programming problem. Results show the ERAPL
outperforms them in terms of network lifetime.
3.2 Harmony Search Algorithm (HSA)
Harmony Search Algorithm was proposed by D.C. Hoang, and R. Kumar, [10], Clustering
technique is one of the methods utilized to extend lifetime of the network by applying data
aggregation and balancing energy consumption among sensor nodes of the network. Harmony
Search Algorithm (HSA) for minimizing the intra-cluster distance and optimizing the energy
consumption of the network. HSA is music based meta heuristic optimization method which is
analogous with the music improvisation process where musician continue to polish the pitches
in order to obtain better harmony. Results demonstrate that the proposed protocol using HSA
can reduce energy consumption and improve the network lifetime.
3.3 Novel clustering algorithm OCABTR
Novel clustering algorithm OCABTR was Proposed, Ying Liang, Hongwei Gao [28], a novel
clustering algorithm OCABTR which fully consider the characteristic of target occurrence in
monitor area. In OCABTR, the authors adopted the strategy of forming cluster first and
selecting cluster-head afterward. The cluster is formed by genetic algorithm to optimize and
partition the adjacent nodes which will sense similar target into one cluster. Since improving
the rate of data aggregation in clusters, this approach can effectively reduce redundant data
transmission and the whole energy consumed in the network. The operation of OCABTR is
divided into rounds. Each round begins with a set-up phase when the clusters are organized,
followed by a steady-state phase when data are transferred from the nodes to the cluster head
and on to the BS. The experimental results demonstrate that the proposed algorithms
significantly outperform previous methods, in terms of system lifetime.
3.4 Multi-Layer Energy-Efficient And Delay-Reducing Chain-Based Data
Gathering Protocol
Multi-Layer Energy-Efficient And Delay-Reducing Chain-Based Data Gathering Protocol
proposed by[15], Lingyun Yuan, et al. The protocol puts forward the idea of multi-layer chain,
and uses the minimum total energy algorithm to construct the chain. Moreover, the maximum
residual energy of nodes is the standard for selection of leaders. The experimental results
show that MEDC works for WSTMN better than LEACH and PEGASIS, which can not only
prolong the network lifetime, but also reduce the network delay remarkably.
3.5 Steiner Points Grid Routing
Steiner Points Grid Routing was proposed by, Chiu-Kuo Liang, et al.[5] In order to reduce the
total energy consumption for data transmission between the source node and the sink node, a
different virtual grid structure instead of virtual grid in GGR is constructed. The idea is to
construct the virtual grid structure based on the square Steiner trees [19].Once the sensor nodes
are deployed in the sensor field, the sink node starts to construct the grid structure. The sink
divides the plane into a grid of cells. Cross-points of the grid are the Dissemination Points (DPs).
5. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.1, No.4, December 2010
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The size of the cells, denoted as α, is determined by the sink such that DPs are not within direct
transmission range. The sink is the first DP. Knowing its own position and the size of each cell,
the sink is able to send a data request (in the form of a data-announcement message) to each
adjacent Dissemination Point in the grid. Any node that is within the target region of a received
QUERY message stores the appropriate routing information and starts to send the sensed data
(in the form of DATA message) to the sink. The routing information contains the appropriate
upstream DNs through which DATA messages will be forwarded. DN will find the appropriate
path to transmit DATA message depending on which DP or SP it belongs to. If DN belongs to
SP, then it will choose the upstream path along the hexagonal structure.
3.6 Data Gathering Algorithm Based on Energy Level( DGEL)
The DGEL [25] algorithm was proposed Zheng Wang and Yunsheng Liu. The algorithm is
executed in a manner very similar to FLSPT algorithm. The proposed definitions to the
algorithm are applied, and the pseudo code for DGEL is presented. First, two sets namely the
sink node set S and the sensor nodes set V-{S}, both of which was given different initial values
at the beginning is constructed. To further reduce computational cost, the max-priority queue
which contains all nodes sorted in the descending order of ELPD [25] was introduced into the
algorithm. Next, DGEL periodically selects a new node with the highest priority in Q outside the
computed routing tree until the queue is empty.
Steps illustrate how the auxiliary vectors are updated when the current node which is about to
join in the routing tree interferes with its neighbors. To refresh a node’s estimate vectors, a
comparison is first done in terms of ELPD[25] In case of equality, the second-level estimates
(referred to energy level and bandwidth consumption) is used to break the ties here á is an
adjustment coefficient which allows energy level to fluctuate in an appropriate boundary.
3.7 Energy-efficient and Delay-aware Data Gathering Protocol
Energy-efficient and Delay-aware Data Gathering Protocol[14] was proposed by Zuzhi Fan and
GuangZhou, which is efficient in the ways that it prolongs the lifetime of network, as well as
takes less time to finish a transmission round. The simulation results show that it improves the
average EnergyxDelay metric compared to other protocols. A distributed topology construction
algorithm each node locally exchanges its state information, including energy level, location at
the fixed power level to discovery neighbor nodes. "Local exchange" here means that
broadcasting at an output power level corresponding to a cluster radius R. According to
discussion, the minimum value of R is given as equation
27
2
)
R
*
(
* 2
Π
=
Π
K
Parea
where , Parea is the size of the network area. After the neighbor discover phase, each node gets
its degree and neighbor nodes within range R, and begins clustering process, which contain a
number of iterations. In each iteration, the ‘uncovered’ node with suitable degree selects itself as
a candidate cluster-head. An ‘uncovered’ node is neither a cluster-head nor a member of cluster.
If more than one candidate cluster-heads are located in the same cluster range, the node with
large degree will be selected as cluster-head. Once a node is selected as a CH, it asks all
neighbor nodes to join the cluster by broadcasting its cluster members list with maximum
transmission power. On receiving the message, any nodes update its own neighbor node list by
getting rid of those nodes which belong to the received list and enter into the next iterations. The
clustering process will end if the expected number of cluster-heads is selected or no suitable
6. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.1, No.4, December 2010
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nodes are available. At the end of process, each cluster-heads broadcast their status to the other
sensors in the network. The rest ‘uncovered’ sensors determine to which cluster it wants to join
by choosing the cluster-head that requires minimum cost. Taking the energy consumption and
transmission delay into consideration, the cost is described as the product of the distance from
the cluster-head and cluster-head degree.
3.8 Energy-Efficient Data Gathering Protocol (EEDGP)
Energy-Efficient Data Gathering Protocol was proposed by Jun Yang, et al.[22],EEDGP
includes a clustering method of balancing energy consumption, a data prediction transmission
strategy and an energy-aware multi hop routing algorithm. In clustering process phase, the initial
probability of node for cluster head election is derived from mathematical relation between
application’s seamless coverage fraction and numbers of required cluster heads. In data
aggregation phase, the spatial correlation of data within a cluster is utilized by cluster head to
aggregate sampling data. According to temporal correlation of sampling data, cluster heads send
data to sink node using prediction transmission strategy while satisfying the transmission
precision in the data transmission phase, and the lifetime of network is greatly prolonged by this
strategy. In order to mitigate the hot spot problem among cluster heads, a greedy geographic and
energy-aware multi hop routing algorithm is presented for inter-cluster communication.
Simulation results show that EEDGP outperforms in terms of network lifetime by balancing
energy consumption and decrease of transmission while meeting desired application-specific
requirements.
3.9 Energy-efficient data gathering algorithm(EDGA)
The EDGA was proposed by Jing Yang et al. [26], to minimize the energy consumption and
maximize the network lifetime. In order to realize the goal, the basic operations of EDGA are
divided into three distinct phases: Cluster Formation, Chain Construction and Data
Transmission. In the first phase, the network will be grouped into clusters. In the second phase,
the CHs use ACO to construct chain in their cluster. In the third phase, data is gathered and
transmitted to the sink.It is assumed that each node can obtain the statuses of all its neighbors
through broadcasting a topology discovery message, which includes the information of
neighbors, such as the residual energy and ID. When a node receives the message, it saves the
received information in Table 1.
Table 1 INFORMATION TABLE
ID Di Ei CH di qi
1 E1 not q1
2 E2 not q2
.
n En not qn
ID is the identification index of neighbors. Di is the distance between node vi to the sink. Ei is
the residual energy of node vi. qi indicates the probability of node i becoming the CH. After the
CHs receive the data, they use multi-hop method to send data to the sink. In contrast to single-
hop routing algorithms, multi-hop routing algorithms let a node wanting to transmit data to the
sink find one or multiple intermediate nodes, which have focused on load balancing and
7. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.1, No.4, December 2010
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reducing the communication cost. In WSNs, such a scheme can distribute energy usage among
nodes as means to increase the network lifetime.
4. DISCUSSIONS
From the number of papers that we have reviewed for wireless sensor networks in data gathering
techniques have different strong and weak points about network lifetime and energy
consumption. All Data Gathering algorithms have to comply with a few basic requirements. The
most important requirement is that a data gathering algorithm has to be imperceptible. They have
a set of criteria to further define the imperceptibility of an algorithm. These requirements are as
follows [1][3][6] [23][30][31].
4.1 Network density
The network density is the number of nodes per square meter. It varies from one deployment to
another and from one node to another within the same deployment depending on the node
distribution.
4.2 Energy
The energy is an important parameter [3][7] in a resource limited network such as the WSN.
Indeed, the remaining battery level appears to be the most important value in this parameter but
it is not the only one. Consequently, the agent will reject some cooperation requests because it
will consider that there is not enough energy.
4.3 Position within the network
In various works defined so far, three types of node positions normal, edge and critical are used.
The normal position is the position inside the network where the node has multiple neighbors..
The edge node is a node at the border of the network and having a restricted view of the network
limited to only one neighbor. A node is considered in a critical position if it connects two parts
of the network.
4.4 Residual Energy
Residual energy is defined as the remaining power of a sensor node whenever topology changes,
which can be an indicator of the stability of a link and the survival time of a node.
4.5 Energy Level
Energy lever consists of two different ingredients in our work, the first definition is described as
the energy level of a node which represents the amount of packets that a node can transmit to its
neighbors under the constraint of residual energy, while energy level of a path is defined as the
minimum value of energy level among the nodes along the path from a sensor node to the sink.
8. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.1, No.4, December 2010
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4.6 Network Throughput
It is measured by the number of data packets that the sink node can gather before all data routing
path failed due to residual energy shortage. This demonstrates the routing protocol in the ability
of maximizing the network throughput coincided with energy restriction [7].
4.7 Network lifetime
It is the average number of dead nodes, as a result of path failure in terms of different data
collection rounds. It presents the efficiency of rounds. It presents the efficiency of a protocol in
extending the number of living nodes so as to prolong the network lifetime [6].
4.8 Network Topology
A sensor node should be able to make decisions to estimate, for example, the importance of the
sensed information. It should be also able to cooperate with other sensor nodes in order to
eliminate the inter-sensor-nodes redundancy and/or to concatenate data.
4.9 Latency
Latency requirement depends on the applications. In an environment surveillance application,
when an event is detected, sensor nodes should be able to report the local processing result to
sink in real time so that appropriate action can be taken promptly [7]
Table 2.Comparision of different Techniques
paramete
r
Initial
Energ
y
Base
station
Network
size
No of
nodes elec
E fs
E mp
E da
E Thresh
old
distenc
e
simulator
ERAPL (50,10
0)
1000M*
1000M
50
nJ
/bi
t
HSA 1J (50,-
75)
100*100
2
M
100 MatLa
b
OCABT
R
(2J,5J
)
(50,20
0)
100*100
m
100 50
nJ
/bi
t
10p
j/bit
/
2
M
0.00
13pj
/bit/
4
m
75m MatLa
b
MEDC .25j/
.5j/1
j/2j
(500,
250)
50 50
nJ
/bi
t
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4.10 Sensor Node
A sensor node is the core component of a WSN. Sensor nodes can take on multiple roles in a
network, such as simple sensing; data storage; routing; and data processing.
4.11 Base Station
The base station is at the upper level of the hierarchical WSN. It provides the communication
link between the sensor network and the end-user.
4.12Power
The power utilized in a sensor network is consumed as sensors are performing sensing,
processing and communication tasks. Due to the limited energy nature of the sensor nodes,
network lifetime is dependent on the efficient use of this energy[21].
RESEARCH DIRECTIONS
The general data gathering algorithms for wireless sensor networks discussed so far, as well as
the specific implementations of various algorithms of WSN continues a number of research
directions, and opens some new ones.
SPGR 6000j 500
⋅ 500
2
M
3000 C# on
.NET
DGEL
1000
to
2000,
100*1
00
2
M
20-
300.
Matlab.
EDDG
P
1J (50,17
5)
100*100
m
100 50
nJ
/bi
t
10p
j/bit
/
2
M
0.00
13pj
/bit/
4
m
EEDGP 1J (300,5
0)
200*1
00
2
M
800 50
nJ
/bi
t
10p
j/bit
/
2
M
0.00
13pj
/bit/
4
m
75m
EDGA 2j 1 200*200
m
100-
500
50
nJ
/bi
t
10p
j/bit
/
2
M
0.00
13pj
/bit/
4
m
5
nj
/b
it
75m
10. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.1, No.4, December 2010
111
Query processing
To query sensor database, two extensions to traditional SQL query language
have been proposed, including QoS and semantics. QoS extensions allow an application
to express the concerned factors during the planning and execution of a query. Semantic
extensions enable the representation of high-level information on group activities of the
objects in a sensor. Database for wireless sensor networks have been taken into
consideration. The proposals are general and thus enable a database view with query
based interaction applicable to most sensor network applications and tasks. The
proposed extensions are capable of achieving various task goals, but it remains unclear
how difficult it is to implement these extensions in a sensor network query processing
and execution system. This will be the main issue for the future investigation.
Routing Tree
Given an arbitrary communication graph and a routing tree, a wavelet lifting
transform which uses very low number of raw data transmissions have been defined. As
future work, other problems including selecting the tree, transmission schedule and
transform jointly for a given graph can be considered.
Power aware routing
Power-aware routing protocol DGEL, which builds energy-effective path for
data gathering through enhanced link sharing among sensor nodes, is used in small scale
networks. The proposed algorithm, which posses’ simplicity, high throughput and the
prolonged network lifetime may be applied for large-scale communication networks
would be another future research direction.
Optimality in algorithms
In terms of power levels of the sensors considered, the heterogeneous and
adjustable instead of fixed and homogeneous as was considered in the previous work an
upper bound on the lifetime of the optimal data gathering tree has been derived. An
iterative algorithm that progressively reduces the maximum normalized load (hence
increases of the lifetime) of a given initial tree has been developed. The optimality
algorithm can be used to construct new trees periodically or at appropriate time instants
to further prolong the lifetime of a sensor networks.
5.CONCLUSION
Wireless sensor networks are more than just a specific form of ad hoc networks. The
stringent miniaturization and cost requirements make economic usage of energy and
computational power a significantly bigger issue than in normal ad hoc networks.
Moreover, specific applications require a rethinking of some of the basic paradigms with
11. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.1, No.4, December 2010
112
which communication protocols are engineered. As wireless sensor networks are still a
young research field, much activity is still on-going to solve many open issues. As some
of the underlying hardware problems, especially with respect to the energy supply and
miniaturization, are not yet completely solved, wireless sensor networks are at the time
of this writing not yet ready for practical deployment. Nevertheless, these problems
could be resolved in the near future. In a Wireless sensor networks, it is significant to
prolong network lifetime so that more data can be collected by the sink(s).It is well
known that, efficient use of energy is critical for networks lifetime. This paper outlined
different critical issues in wireless sensor network in general and made an extensive
study of different associated with existing data gathering algorithms then we focus on
two key issues .These issues have a network lifetime and saving energy on them.
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