A wireless sensor network is a network of tiny nodes with wireless sensing capacity for data collection processing and further communicating with the Base Station this paper discusses the overall mechanism of data dissemination right from data collection at the sensor nodes, clustering of sensor nodes, data aggregation at the cluster heads and disseminating data to the Base Station the overall motive of the paper is to conserve energy so that lifetime of the network is extended this paper highlights the existing algorithms and open research gaps in efficient data dissemination.
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.
Improved LEACH protocol for increasing the lifetime of WSNsIJECEIAES
Recently, wireless sensor network (WSN) is taking a high place in several applications: military, industry, and environment. The importance of WSNs in current applications makes the WSNs the most developed technology at the research level and especially in the field of communication and computing. However, WSN’s performance deals with a number of challenges. Energy consumption is the most considerable for many researchers because nodes use energy to collect, treat, and send data, but they have restricted energy. For this reason, numerous efficient energy routing protocols have been developed to save the consumption of power. Low energy adaptive clustering hierarchy (LEACH) is considered as the most attractive one in WSNs. In the present document, we evaluate the LEACH approach effectiveness in the cluster-head (CH) choosing and in data transmission, then we propose an enhanced protocol. The proposed algorithm aims to improve energy consumption and prolong the lifetime of WSN through selecting CHs depending on the remaining power, balancing the number of nodes in clusters, determining abandoned nodes in order to send their data to the sink. Then CHs choose the optimal path to achieve the sink. Simulation results exhibit that the enhanced method can decrease the consumption of energy and prolong the life-cycle of the network.
Limited energy is the major driving factor for research on wireless sensor networks. Clustering alleviates
this energy shortage problem by reducing data traffic conveyed over the network and therefore several
clustering methods are proposed in the literature. Researchers put forward their methods by making
serious assumptions such as always locating single sink at one side of the topology or making clusters near
to the sink with smaller sizes. However, to the best of our knowledge, there is no comprehensive research
that investigates the effects of various structural alternatives on energy consumption of wireless sensor
networks. In this paper, we thoroughly analyse the impact of various structural approaches such as cluster
size, number of tiers in the topology, node density, position and number of sinks. Extensive simulation
results are provided. The results show that the best performance about lifetime prolongation is achieved by
locating a sufficient number of sinks around the network area.
WEIGHTED DYNAMIC DISTRIBUTED CLUSTERING PROTOCOL FOR HETEROGENEOUS WIRELESS S...ijwmn
In wireless sensor networks (WSN), conserving energy and increasing lifetime of the network are a critical issue that has been addressed by substantial research works. The clustering technique has been proven particularly energy-efficient in WSN. The nodes form groups (clusters) that include one cluster head and member clusters. Cluster heads (CHs) are able to process, filter, gather the data sent by sensors
belonging to their cluster and send it to the base station. Many routing protocols which have been proposed are based on heterogeneity and use the clustering scheme such as SEP and DEEC. In this paper we introduce a new approach called WDDC in which cluster heads are chosen on the basis
of probability of ratio of residual energy and average energy of the network. It also takes into consideration distances between nodes and the base station to favor near nodes with more energy to be cluster heads. Furthermore, WDDC is dynamic; it divides network lifetime in two zones in which it changes its behavior. Simulation results show that our approach performs better than the other distributed clustering protocols such as SEP and DEEC in terms of energy efficiency and lifetime of the network.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
SIMULATION BASED ANALYSIS OF CLUSTER-BASED PROTOCOL IN WIRELESS SENSOR NETWORKijngnjournal
The modern growth in fabricate energy efficient Wireless Sensor Network is liberal a novel way to
systematize WSN in applications like surveillance, industrial monitoring, traffic monitoring, habitat
monitoring, cropping monitoring, crowd including etc. The rising use of these networks is making
engineers evolve novel and efficient ideas in this field. A group of research in data routing, data density
and in network aggregation has been proposed in recent years. The energy consumption is the main
apprehension in the wireless sensor network. There are many protocols in wireless sensor network to
diminish the energy consumption and to put in to the network lifetime. Among a range of types of
techniques, clustering is the most efficient technique to diminish the energy expenditure of network. In
this effort, LEACH protocol has been second-hand for clustering in which cluster heads are nominated on
the basis of distance and energy. The LEACH protocol is been implemented in a simulated environment
and analyze their performance graphically.
Ameliorate Threshold Distributed Energy Efficient Clustering Algorithm for He...chokrio
Ameliorating the lifetime in heterogeneous wireless sensor network is an important task because the sensor nodes are limited in the resource energy. The best way to improve a WSN lifetime is the clustering based algorithms in which each cluster is managed by a leader called Cluster Head. Each other node must communicate with this CH to send the data sensing. The nearest base station nodes must also send their data to their leaders, this causes a loss of energy. In this paper, we propose a new approach to ameliorate a threshold distributed energy efficient clustering protocol for heterogeneous wireless sensor networks by excluding closest nodes to the base station in the clustering process. We show by simulation in MATLAB that the proposed approach increases obviously the number of the received packet messages and prolongs the lifetime of the network compared to TDEEC protocol.
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.
Improved LEACH protocol for increasing the lifetime of WSNsIJECEIAES
Recently, wireless sensor network (WSN) is taking a high place in several applications: military, industry, and environment. The importance of WSNs in current applications makes the WSNs the most developed technology at the research level and especially in the field of communication and computing. However, WSN’s performance deals with a number of challenges. Energy consumption is the most considerable for many researchers because nodes use energy to collect, treat, and send data, but they have restricted energy. For this reason, numerous efficient energy routing protocols have been developed to save the consumption of power. Low energy adaptive clustering hierarchy (LEACH) is considered as the most attractive one in WSNs. In the present document, we evaluate the LEACH approach effectiveness in the cluster-head (CH) choosing and in data transmission, then we propose an enhanced protocol. The proposed algorithm aims to improve energy consumption and prolong the lifetime of WSN through selecting CHs depending on the remaining power, balancing the number of nodes in clusters, determining abandoned nodes in order to send their data to the sink. Then CHs choose the optimal path to achieve the sink. Simulation results exhibit that the enhanced method can decrease the consumption of energy and prolong the life-cycle of the network.
Limited energy is the major driving factor for research on wireless sensor networks. Clustering alleviates
this energy shortage problem by reducing data traffic conveyed over the network and therefore several
clustering methods are proposed in the literature. Researchers put forward their methods by making
serious assumptions such as always locating single sink at one side of the topology or making clusters near
to the sink with smaller sizes. However, to the best of our knowledge, there is no comprehensive research
that investigates the effects of various structural alternatives on energy consumption of wireless sensor
networks. In this paper, we thoroughly analyse the impact of various structural approaches such as cluster
size, number of tiers in the topology, node density, position and number of sinks. Extensive simulation
results are provided. The results show that the best performance about lifetime prolongation is achieved by
locating a sufficient number of sinks around the network area.
WEIGHTED DYNAMIC DISTRIBUTED CLUSTERING PROTOCOL FOR HETEROGENEOUS WIRELESS S...ijwmn
In wireless sensor networks (WSN), conserving energy and increasing lifetime of the network are a critical issue that has been addressed by substantial research works. The clustering technique has been proven particularly energy-efficient in WSN. The nodes form groups (clusters) that include one cluster head and member clusters. Cluster heads (CHs) are able to process, filter, gather the data sent by sensors
belonging to their cluster and send it to the base station. Many routing protocols which have been proposed are based on heterogeneity and use the clustering scheme such as SEP and DEEC. In this paper we introduce a new approach called WDDC in which cluster heads are chosen on the basis
of probability of ratio of residual energy and average energy of the network. It also takes into consideration distances between nodes and the base station to favor near nodes with more energy to be cluster heads. Furthermore, WDDC is dynamic; it divides network lifetime in two zones in which it changes its behavior. Simulation results show that our approach performs better than the other distributed clustering protocols such as SEP and DEEC in terms of energy efficiency and lifetime of the network.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
SIMULATION BASED ANALYSIS OF CLUSTER-BASED PROTOCOL IN WIRELESS SENSOR NETWORKijngnjournal
The modern growth in fabricate energy efficient Wireless Sensor Network is liberal a novel way to
systematize WSN in applications like surveillance, industrial monitoring, traffic monitoring, habitat
monitoring, cropping monitoring, crowd including etc. The rising use of these networks is making
engineers evolve novel and efficient ideas in this field. A group of research in data routing, data density
and in network aggregation has been proposed in recent years. The energy consumption is the main
apprehension in the wireless sensor network. There are many protocols in wireless sensor network to
diminish the energy consumption and to put in to the network lifetime. Among a range of types of
techniques, clustering is the most efficient technique to diminish the energy expenditure of network. In
this effort, LEACH protocol has been second-hand for clustering in which cluster heads are nominated on
the basis of distance and energy. The LEACH protocol is been implemented in a simulated environment
and analyze their performance graphically.
Ameliorate Threshold Distributed Energy Efficient Clustering Algorithm for He...chokrio
Ameliorating the lifetime in heterogeneous wireless sensor network is an important task because the sensor nodes are limited in the resource energy. The best way to improve a WSN lifetime is the clustering based algorithms in which each cluster is managed by a leader called Cluster Head. Each other node must communicate with this CH to send the data sensing. The nearest base station nodes must also send their data to their leaders, this causes a loss of energy. In this paper, we propose a new approach to ameliorate a threshold distributed energy efficient clustering protocol for heterogeneous wireless sensor networks by excluding closest nodes to the base station in the clustering process. We show by simulation in MATLAB that the proposed approach increases obviously the number of the received packet messages and prolongs the lifetime of the network compared to TDEEC protocol.
Energy aware clustering protocol (eacp)IJCNCJournal
Energy saving to prolong the network life is an important design issue while developing a new routing
protocol for wireless sensor network. Clustering is a key technique for this and helps in maximizing the
network lifetime and scalability. Most of the routing and data dissemination protocols of WSN assume a
homogeneous network architecture, in which all sensors have the same capabilities in terms of battery
power, communication, sensing, storage, and processing. Recently, there has been an interest in
heterogeneous sensor networks, especially for real deployments. This research paper has proposed a new
energy aware clustering protocol (EACP) for heterogeneous wireless sensor networks. Heterogeneity is
introduced in EACP by using two types of nodes: normal and advanced. In EACP cluster heads for normal
nodes are elected with the help of a probability scheme based on residual and average energy of the
normal nodes. This will ensure that only the high residual normal nodes can become the cluster head in a
round. Advanced nodes use a separate probability based scheme for cluster head election and they will
further act as a gateway for normal cluster heads and transmit their data load to base station when they
are not doing the duty of a cluster head. Finally a sleep state is suggested for some sensor nodes during
cluster formation phase to save network energy. The performance of EACP is compared with SEP and
simulation result shows the better result for stability period, network life and energy saving than SEP.
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
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.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
FUZZY-CLUSTERING BASED DATA GATHERING IN WIRELESS SENSOR NETWORK ijsc
Wireless Sensor Networks (WSN) is spatially distributed, collection of sensor nodes for the purpose of
monitoring physical or environmental conditions, such as temperature, sound, pressure, etc. and to
cooperatively pass their data through the network to a base station. The critical challenge is to minimize
the energy consumption in data gathering and forwarding from sensor nodes to the sink. Cluster based
data aggregation is one of the most popular communication protocols in this field. Clustering is an
important procedure for extending the network lifetime in wireless sensor networks. Cluster Heads (CH)
aggregate data from relevant cluster nodes and send it to the base station. A main challenge in WSNs is to
select suitable CHs. Another communication protocol is based on a tree construction. In this protocol,
energy consumption is low because there are short paths between the sensors. In this paper, Dynamic
Fuzzy Clustering data aggregation is introduced. This approach is based on clustering and minimum
spanning tree. The proposed method initially uses fuzzy decision making approach for the selection of CHs.
Afterward a minimum spanning tree is constructed based on CHs. CHs are selected efficiently and
accurately. The combining clustering and tree structure is reclaiming the advantages of the previous
structures. Our method is compared to the well-known data aggregation methods, in terms of energy
consumption and the amount of energy residuary in each sensor network lifetime. Our method decreases
energy consumption of each node. When the best CHs selected and the minimum spanning tree is formed by
the best CHs, the remaining energy of the nodes will be preserved. Node lifetime has an important role in
WSN. Using our proposed data aggregation algorithm, survival of the network is improved
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.
MULTI-HOP DISTRIBUTED ENERGY EFFICIENT HIERARCHICAL CLUSTERING SCHEME FOR HET...ijfcstjournal
Wireless sensor network (WSNs) are network of Sensor Nodes (SNs) with inherent sensing, processing and
communicating abilities. One of current concerns in wireless sensor networks is developing a stable
clustered heterogeneous protocol prolonging the network lifetime with minimum consumption of battery
power. In the recent times, many routing protocols have been proposed increasing the network lifetime,
stability in short proposing a reliable and robust routing protocol. In this paper we study the impact of
hierarchical clustered network with sensor nodes of two-level heterogeneity. The main approach in this
research is to develop an enhanced multi-hop DEEC routing protocol unlike DEEC. Simulation results
show the proposed protocol is better than DEEC in terms of FDN (First Dead Node), energy consumption
and Packet transmission.
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.
Extending the longevity, is a significant job to be accomplished by these sensor networks. The traditional routing protocols could not be applied here, due to its nodes powered by batteries. Nodes are often clustered in to non-overlapping clusters, so as to provide energy efficiency. A concise overview on clustering processes, within wireless sensor networks is given in this paper. But it is difficult to replace the deceased batteries of the sensor nodes. A distinctive sensor node consumes much of its energy during wireless communication. This research work suggests the development of a hierarchical distributed clustering mechanism, which gives improved performance over the existing clustering algorithm LEACH. The two hiding concepts behind the proposed scheme are the hierarchical distributed clustering mechanism and the concept of threshold. Energy utilization is significantly reduced, thereby greatly prolonging the lifetime of the sensor nodes.
Communication synchronization in cluster based wireless sensor network a re...eSAT Journals
Abstract A wireless sensor network is acquiring more popularity in different sectors. A scalable, low latency and energy efficient are desire challenges that should meet by wireless sensor network. Clustering permits sensors to systematically communicate among clusters. Cluster based sensor network satisfies these challenges as it provides flexible, energy saving and QoS. The communication efficiency and network performance degrades if the interaction between inter-cluster and intra-cluster communication are not managed properly. The proposed work uses two approaches to solve this problem. At aiming low packet delay and high throughput first approach uses cycle- based synchronous scheduling. By completely removing necessity of communication synchronization second approach send packets with no synchronization delay. The combined scheme can take benefit of both approaches. Keywords: Wireless sensor network, clustering, communication synchronization, QoS.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Wireless sensor network consists of several distributed sensor nodes. It is used for several environmental applications, military applications and health related applications. To prolong the lifetime of the sensor nodes, designing efficient routing protocols is critical. Most of the research in energy efficient data gathering in data centric applications of wireless sensor networks is motivated by LEACH (Low Energy Adaptive Clustering Hierarchy) scheme. It allows the rotation of cluster head role among the sensor nodes and tries to distribute the energy consumption over the network. Selection of sensor node for such role rotations greatly affects the energy efficiency of the network. Some of the routing protocol has a drawback that the cluster is not evenly distributed due to its randomized rotation of local cluster head. We have surveyed several existing methods for selecting energy efficient cluster head in wireless sensor networks. We have proposed an energy efficient cluster head selection method in which the cluster head selection and replacement cost is reduced and ultimately the network lifetime is increased. Using our proposed method, network life time is increased compared to existing methods. Keywords: WSN, CH, BS, LEACH, LEACH-B, LEACH-F
Clustering provides an effective method for
extending the lifetime of a wireless sensor network. Current
clustering methods selecting cluster heads with more residual
energy, and rotating cluster heads periodically to distribute the
energy consumption among nodes in each cluster. However,
they rarely consider the hot spot problem in multi hop sensor
networks. When cluster heads forward their data to the base
station, the cluster heads closer to the base station are heavily
burdened with traffic and tend to die much faster. To mitigate
the hot spot problem, we propose a Novel Energy Efficient
Unequal Clustering Routing (NEEUC) protocol. It uses residual
energy and groupsthe nodesinto clusters of unequal layers
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.
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 aware clustering protocol (eacp)IJCNCJournal
Energy saving to prolong the network life is an important design issue while developing a new routing
protocol for wireless sensor network. Clustering is a key technique for this and helps in maximizing the
network lifetime and scalability. Most of the routing and data dissemination protocols of WSN assume a
homogeneous network architecture, in which all sensors have the same capabilities in terms of battery
power, communication, sensing, storage, and processing. Recently, there has been an interest in
heterogeneous sensor networks, especially for real deployments. This research paper has proposed a new
energy aware clustering protocol (EACP) for heterogeneous wireless sensor networks. Heterogeneity is
introduced in EACP by using two types of nodes: normal and advanced. In EACP cluster heads for normal
nodes are elected with the help of a probability scheme based on residual and average energy of the
normal nodes. This will ensure that only the high residual normal nodes can become the cluster head in a
round. Advanced nodes use a separate probability based scheme for cluster head election and they will
further act as a gateway for normal cluster heads and transmit their data load to base station when they
are not doing the duty of a cluster head. Finally a sleep state is suggested for some sensor nodes during
cluster formation phase to save network energy. The performance of EACP is compared with SEP and
simulation result shows the better result for stability period, network life and energy saving than SEP.
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
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.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
FUZZY-CLUSTERING BASED DATA GATHERING IN WIRELESS SENSOR NETWORK ijsc
Wireless Sensor Networks (WSN) is spatially distributed, collection of sensor nodes for the purpose of
monitoring physical or environmental conditions, such as temperature, sound, pressure, etc. and to
cooperatively pass their data through the network to a base station. The critical challenge is to minimize
the energy consumption in data gathering and forwarding from sensor nodes to the sink. Cluster based
data aggregation is one of the most popular communication protocols in this field. Clustering is an
important procedure for extending the network lifetime in wireless sensor networks. Cluster Heads (CH)
aggregate data from relevant cluster nodes and send it to the base station. A main challenge in WSNs is to
select suitable CHs. Another communication protocol is based on a tree construction. In this protocol,
energy consumption is low because there are short paths between the sensors. In this paper, Dynamic
Fuzzy Clustering data aggregation is introduced. This approach is based on clustering and minimum
spanning tree. The proposed method initially uses fuzzy decision making approach for the selection of CHs.
Afterward a minimum spanning tree is constructed based on CHs. CHs are selected efficiently and
accurately. The combining clustering and tree structure is reclaiming the advantages of the previous
structures. Our method is compared to the well-known data aggregation methods, in terms of energy
consumption and the amount of energy residuary in each sensor network lifetime. Our method decreases
energy consumption of each node. When the best CHs selected and the minimum spanning tree is formed by
the best CHs, the remaining energy of the nodes will be preserved. Node lifetime has an important role in
WSN. Using our proposed data aggregation algorithm, survival of the network is improved
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.
MULTI-HOP DISTRIBUTED ENERGY EFFICIENT HIERARCHICAL CLUSTERING SCHEME FOR HET...ijfcstjournal
Wireless sensor network (WSNs) are network of Sensor Nodes (SNs) with inherent sensing, processing and
communicating abilities. One of current concerns in wireless sensor networks is developing a stable
clustered heterogeneous protocol prolonging the network lifetime with minimum consumption of battery
power. In the recent times, many routing protocols have been proposed increasing the network lifetime,
stability in short proposing a reliable and robust routing protocol. In this paper we study the impact of
hierarchical clustered network with sensor nodes of two-level heterogeneity. The main approach in this
research is to develop an enhanced multi-hop DEEC routing protocol unlike DEEC. Simulation results
show the proposed protocol is better than DEEC in terms of FDN (First Dead Node), energy consumption
and Packet transmission.
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.
Extending the longevity, is a significant job to be accomplished by these sensor networks. The traditional routing protocols could not be applied here, due to its nodes powered by batteries. Nodes are often clustered in to non-overlapping clusters, so as to provide energy efficiency. A concise overview on clustering processes, within wireless sensor networks is given in this paper. But it is difficult to replace the deceased batteries of the sensor nodes. A distinctive sensor node consumes much of its energy during wireless communication. This research work suggests the development of a hierarchical distributed clustering mechanism, which gives improved performance over the existing clustering algorithm LEACH. The two hiding concepts behind the proposed scheme are the hierarchical distributed clustering mechanism and the concept of threshold. Energy utilization is significantly reduced, thereby greatly prolonging the lifetime of the sensor nodes.
Communication synchronization in cluster based wireless sensor network a re...eSAT Journals
Abstract A wireless sensor network is acquiring more popularity in different sectors. A scalable, low latency and energy efficient are desire challenges that should meet by wireless sensor network. Clustering permits sensors to systematically communicate among clusters. Cluster based sensor network satisfies these challenges as it provides flexible, energy saving and QoS. The communication efficiency and network performance degrades if the interaction between inter-cluster and intra-cluster communication are not managed properly. The proposed work uses two approaches to solve this problem. At aiming low packet delay and high throughput first approach uses cycle- based synchronous scheduling. By completely removing necessity of communication synchronization second approach send packets with no synchronization delay. The combined scheme can take benefit of both approaches. Keywords: Wireless sensor network, clustering, communication synchronization, QoS.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Wireless sensor network consists of several distributed sensor nodes. It is used for several environmental applications, military applications and health related applications. To prolong the lifetime of the sensor nodes, designing efficient routing protocols is critical. Most of the research in energy efficient data gathering in data centric applications of wireless sensor networks is motivated by LEACH (Low Energy Adaptive Clustering Hierarchy) scheme. It allows the rotation of cluster head role among the sensor nodes and tries to distribute the energy consumption over the network. Selection of sensor node for such role rotations greatly affects the energy efficiency of the network. Some of the routing protocol has a drawback that the cluster is not evenly distributed due to its randomized rotation of local cluster head. We have surveyed several existing methods for selecting energy efficient cluster head in wireless sensor networks. We have proposed an energy efficient cluster head selection method in which the cluster head selection and replacement cost is reduced and ultimately the network lifetime is increased. Using our proposed method, network life time is increased compared to existing methods. Keywords: WSN, CH, BS, LEACH, LEACH-B, LEACH-F
Clustering provides an effective method for
extending the lifetime of a wireless sensor network. Current
clustering methods selecting cluster heads with more residual
energy, and rotating cluster heads periodically to distribute the
energy consumption among nodes in each cluster. However,
they rarely consider the hot spot problem in multi hop sensor
networks. When cluster heads forward their data to the base
station, the cluster heads closer to the base station are heavily
burdened with traffic and tend to die much faster. To mitigate
the hot spot problem, we propose a Novel Energy Efficient
Unequal Clustering Routing (NEEUC) protocol. It uses residual
energy and groupsthe nodesinto clusters of unequal layers
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.
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.
MULTI-HOP DISTRIBUTED ENERGY EFFICIENT HIERARCHICAL CLUSTERING SCHEME FOR H...ijfcstjournal
Wireless sensor network (WSNs) are network of Sensor Nodes (SNs) with inherent sensing, processing and
communicating abilities. One of current concerns in wireless sensor networks is developing a stable
clustered heterogeneous protocol prolonging the network lifetime with minimum consumption of battery
power. In the recent times, many routing protocols have been proposed increasing the network lifetime,
stability in short proposing a reliable and robust routing protocol. In this paper we study the impact of
hierarchical clustered network with sensor nodes of two-level heterogeneity. The main approach in this
research is to develop an enhanced multi-hop DEEC routing protocol unlike DEEC. Simulation results
show the proposed protocol is better than DEEC in terms of FDN (First Dead Node), energy consumption
and Packet transmission.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
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 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.
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 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.
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.
This paper considers a heterogeneous network of energy constrained sensors deployed over a region. Each
Normal sensor node in a network is systematically gathering and transmitting sensed data to the clusterhead,
and then cluster head sending data to a base station (via intermediate cluster- heads). This paper
focuses on reducing the energy consumption and hence improving lifetime of wireless sensor Networks.
Clustering sensor node is an effective topology for the energy constrained networks. So energy saving
algorithm has been developed in which clusters are formed considering a subset of high energy nodes as a
cluster-head and another subset of powerful nodes is ask to go to sleep. When Cluster heads deplete their
energy another subset of nodes becomes active and acts as a cluster head. Proposed approach is
implemented in MATLAB, Simulation results shows that it can prolong the network lifetime than LEACH
protocol, and achieves better performance than the existing clustering algorithms such as LEACH.
Uniform Distribution Technique of Cluster Heads in LEACH Protocolidescitation
A sensor network is composed of a large number of
sensor nodes that are densely deployed either inside the
phenomenon or very close to it. Clustering provides an effective
way for prolonging the lifetime of a wireless sensor network.
Current clustering algorithms usually utilize two techniques,
selecting cluster heads (CHs) with more residual energy and
rotating cluster heads periodically, to distribute the energy
consumption among nodes in each cluster and extend the
network lifetime. LEACH (Low-Energy Adaptive Clustering
Hierarchy), a clustering-based protocol that utilizes
randomized rotation of local cluster base stations (cluster-
heads) to evenly distribute the energy load among the sensors
in the network. But LEACH cannot select the cluster-heads
uniformly throughout the network. Hence, some nodes in the
network have to transmit their data very far to reach the CHs,
causing the energy in the system to be large. Here we have an
approach to address this problem for selecting CHs and their
corresponding clusters. The goal of this paper is to build such
a wireless sensor network in which each sensor node remains
inside the transmission range of CHs and its lifetime is
enlarged.
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.
Analysis of Packet Loss Rate in Wireless Sensor Network using LEACH ProtocolIJTET Journal
Abstract: Wireless sensor network (WSN) is used to collect and send various kinds of messages to a base station (BS). Wireless sensor nodes are deployed randomly and densely in a target region, especially where the physical environment is very harsh that the macro-sensor counterparts cannot be deployed. Low Energy Adaptive Clustering Hierarchical (LEACH) Routing protocol builds a process where it reduces the Packet Loss Rate from 100 % to 55% .Simulations are carried out using NS2 simulator.
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Data Dissemination in Wireless Sensor Networks: A State-of-the Art Survey
1. Nidhi Gautam, Prof. Sanjeev Sofat & Prof. Renu Vig
International Journal of Computer Networks (IJCN), Volume (4) : Issue (1) : 2012 22
Data Dissemination in Wireless Sensor Networks: A State-of-the
Art Survey
Nidhi Gautam nidhig121@gmail.com
Assistant Professor U.I.A.M.S.,
Panjab University, Chandigarh, 160025, India
Prof Sanjeev Sofat sanjeevsofat@pec.ac.in
Prof. & H.O.D. CSE Deptt,
PEC Univ. of Technology, Chandigarh, 160012, India
Prof Renu Vig renuvig@hotmail.com
Prof. & Director, U.I.E.T.
Panjab University, Chandigarh, 160025, India
Abstract
A wireless sensor network is a network of tiny nodes with wireless sensing capacity for data
collection processing and further communicating with the Base Station this paper discusses the
overall mechanism of data dissemination right from data collection at the sensor nodes, clustering
of sensor nodes, data aggregation at the cluster heads and disseminating data to the Base
Station the overall motive of the paper is to conserve energy so that lifetime of the network is
extended this paper highlights the existing algorithms and open research gaps in efficient data
dissemination.
Keywords: Data Dissemination, Clustering, Aggregation, Sensor Nodes, Wireless.
1. INTRODUCTION
Wireless Sensor Networks (WSNs) is the fast growing research area from more than a decade
and the pace is still increasing. The latest trend in Micro-electromechanical systems (MEMS)-
based sensor technology has enabled the development of relatively inexpensive and low power
wireless sensor nodes. Wireless Sensor Networks (WSNs) are applicable in various areas
including vehicle tracking, habitat monitoring, forest surveillance, earthquake observation,
biomedical or health care applications, and building surveillance. In these applications sensors
are usually densely deployed remotely and are made to operate autonomously. The conditions
are generally harsh and the sensors are unattended, hence sensors cannot be charged, so
energy constraints is the most critical problem that must be considered. Much of the work is being
done on number of issues but still there is lot of gaps present in this area. Deployment of tiny
nodes in any type of conditions is not an easy task when there is no source of power backup
once the battery is drained out. These tiny nodes have to collect data in extreme conditions,
process the data and further send it to the Base Station through intermediate cluster heads or
neighboring nodes with single-hop or multi-hop communication. During communication there are
many mile-stones i.e. how to collect data, which data needs to be discarded, how clusters are to
be formed, how to set cluster boundaries, how data is aggregated at the cluster head, how data is
transferred to the Base Station for further processing, how to secure this data at every step[1].
Network lifetime i.e. the time till network is alive and able to provide all the services to the
application is the most dominant parameters considered in designing the protocols for WSNs.
The considerable improvement in network lifetime can be achieved either by reducing the number
of hops travelled by a packet to reach its destination (i.e., a BS) or by reducing the amount of
energy consumed across all the nodes in the network [2].
2. Nidhi Gautam, Prof. Sanjeev Sofat & Prof. Renu Vig
International Journal of Computer Networks (IJCN), Volume (4) : Issue (1) : 2012 23
The rest of the paper is organized as follows: In Section 2, we discuss about the clustering
process, various clustering algorithms and open issues in the existing literature. Section 3 lists
the various in-network data aggregation strategies and research gaps in the present literature. In
Section 4 we discuss various Mobility models and research gaps. Finally, we conclude the paper
in Section 5.
2. CLUSTERING
Heinzelman et al. [3] proposed LEACH algorithm i.e. Low-Energy Adaptive Clustering Hierarchy.
It uses a distributed algorithm to form clusters and nodes make autonomous decisions without
any centralized control. In this algorithm, a node decides to be a CH with a probability p initially
and broadcasts its decision. Each non- CH node determines its cluster by choosing the CH that
can be reached using the least communication energy. The algorithm provides a balancing of
energy usage by random rotation of CHs. It forms clusters based on the received signal strength
and uses the CH nodes as routers to the base-station. No overhead is wasted making the
decision of which node becomes cluster-head. CDMA allows clusters to operate independently,
as each cluster is assigned a different code. Each node calculates the minimum transmission
energy to communicate with its cluster-head and only transmits with that power level. Changing
the CH is probabilistic in LEACH; there is a good chance that a node with very low energy gets
selected as a CH. When this node dies, the whole cluster becomes non functional. LEACH is not
applicable if the CHs are far from the base station. Therefore, a large number of algorithms have
been proposed to improve LEACH, such as PEGASIS [4], TEEN [5], APTEEN [6], MECH [7],
LEACH-C [8], EEPSC [9].
Loscri et al. [10] proposed Two-Level LEACH (TL-LEACH) algorithm which is an extension of the
LEACH algorithm. It utilizes two levels of cluster-heads (primary and secondary) in addition to the
other simple sensing nodes. In this algorithm, the primary cluster-head in each cluster
communicates with the secondary, and the corresponding secondary communicate with the
nodes in their sub-cluster. Data-fusion can also be performed as in LEACH. In addition,
communication within a cluster is still scheduled using TDMA time-slots. The organization of a
round will consist of first selecting the primary and secondary cluster-heads using the same
mechanism as LEACH, with the a priori probability of being elevated to a primary cluster-head
less than that of a secondary node. The two-level structure of TL-LEACH reduces the number of
nodes that need to transmit to the base station, effectively reducing the total energy usage. It
might not be effective if the CH is far from the base station
Ye et al. [11] proposed an Energy Efficient Clustering Scheme (EECS) in which cluster-head
candidates compete for the ability to elevate cluster-head for a given round. This competition
involves candidates broadcasting their residual energy to neighbouring candidates. If a given
node does not find a node with more residual energy, it becomes a cluster-head. Cluster
formation is different than that of LEACH. LEACH forms clusters based on the minimum distance
of nodes to their corresponding cluster-head [4]. EECS extends this algorithm by dynamic sizing
of clusters based on cluster distance from the base station. The result is an algorithm that
addresses the problem that clusters at a greater range from the base station requires more
energy for transmission than those that are closer. Ultimately, this improves the distribution of
energy throughout the network, resulting in better resource usage and extended network lifetime.
However clusters closer to the base station may become congested which may result in early CH
death.
Younis et al. [12] proposed a clustering algorithm i.e. Hybrid Energy Efficient Distributed
Clustering (HEED). It is a multi-hop clustering algorithm for Wireless Sensor Networks. CHs are
chosen based on two important parameters: residual energy and intra-cluster communication
cost. Residual energy of each node is used to probabilistically choose the initial set of CHs, as
commonly done in other clustering schemes. HEED is a distributed clustering scheme in which
CH nodes are picked from the deployed sensors. HEED considers both energy and
communication cost while selecting CHs. Unlike LEACH, it does not select cluster -head nodes
randomly. Only sensors that have a high residual energy can become cluster-head nodes. HEED
3. Nidhi Gautam, Prof. Sanjeev Sofat & Prof. Renu Vig
International Journal of Computer Networks (IJCN), Volume (4) : Issue (1) : 2012 24
has three main characteristics: For a given sensor’s transmission range, the probability of CH
selection can be adjusted to ensure inter-CH connectivity. In HEED, each node is mapped to
exactly one cluster and can directly communicate with its CH. The algorithm is divided into three
phases: Initialization, repetition and finalization.
Li et al. [13] proposed Energy-Efficient Unequal Clustering (EEUC) algorithm. In multi-hop WSNs,
there exists a hot-spot problem that CHs closer to the base station tend to die faster, because
they relay much more traffic than remote nodes. EEUC (Energy- Efficient Unequal Clustering)
proposed to balance the energy consumption among clusters, in which the cluster sizes near the
sink node are much smaller than the clusters far away from the sink node in order to save more
energy in intra-cluster communications and inter-cluster communications. Actually, EEUC is a
distance based scheme similar to EECS and it also requires every node to have global
knowledge such as its locations and distances to the sink node. It tries to prolong the network
lifetime and to balance the load among the nodes. It solves the hot spot problems; cluster size is
proportional to the distance to base-Station. However, the extra global data aggregation adds
overheads to all sensors and degrades the network performance, especially for a multi-hop
network.
Bandyopadhyay et al. [14] proposed a distributed, randomized clustering algorithm for WSNs i.e.
Energy Efficient Hierarchical Clustering (EEHC). CHs collect data from the non cluster-head node
in different clusters and send an aggregated report to the base-station. This technique is divided
into two phases; initial and extended. In the first stage i.e. single-level clustering; each sensor
node announces itself as a CH within its communication range with probability p to the
neighbouring nodes. These CHs are named as the volunteer CHs. All nodes that are within k
hops range of a CH receive this announcement either by direct communication or by forwarding.
Any node that receives such announcements and is not itself a CH becomes the member of the
closest cluster. Forced CHs are nodes that are neither CH nor belong to a cluster. If the
announcement does not reach to a node within a preset time interval t that is calculated based on
the duration for a packet to reach a node that is k hops away, the node will become a forced CH
assuming that it is not within k hops of all volunteer CHs. The second phase, called multi-level
clustering builds h levels of cluster hierarchy. The CHs closest to the base station are at a
disadvantage because they are relays for other CHs.
Gong et al. [15] proposed distributed clustering scheme i.e. Multihop routing protocol with
unequal clustering (MRPUC). It operates in rounds, and each round is separated into three
phases: cluster setup, inter-cluster multihop routing formation and data transmission. Each node
gathers the correlative information of its neighbour nodes and elects a node with maximum
residual energy as the cluster-head. The cluster-heads closer to BS have smaller cluster sizes to
save the energy for heavy inter-cluster forwarding task. The regular nodes join clusters where the
cluster-heads have more residual energy and are closer to them. An inter-cluster routing tree is
constructed as network backbone, and data is transmitted to BS via multi-hop communication.
This algorithm prevents early CHs death because the inter cluster communication also depends
on the residual energy. CHs route to the neighbouring CH having the highest residual energy.
The Inter-cluster multihop routing formation may cause an additional overhead.
To solve the problem of existing clustering algorithms of energy consumption due to cluster
formation overhead and fixed level clustering for densely deployed wireless sensor nodes; Yi et
al. [16] proposed Power-efficient and adaptive clustering hierarchy (PEACH). PEACH minimizes
the energy consumption of each node, and maximize the network lifetime. In PEACH, cluster
formation is performed by using overhearing characteristics of wireless communication to support
adaptive multilevel clustering and avoid additional overheads. In WSNs, overhearing a node can
recognize the source and the destination of packets transmitted by the neighbour nodes. PEACH
is applicable in both location-unaware and location-aware sensor networks. Based on its
overhearing characteristics, PEACH saves energy consumption of each node and hence prolong
network lifetime.
4. Nidhi Gautam, Prof. Sanjeev Sofat & Prof. Renu Vig
International Journal of Computer Networks (IJCN), Volume (4) : Issue (1) : 2012 25
Hanh et al. [17] proposed Sensor Web or S-WEB which divide the sensing field into clusters
bordered by two arcs of two adjacent concentric circles and two adjacent radii originating at the
BS. Each cluster is identified by angle order (β) and the order of Signal Strength threshold (δ). To
do so, the BS in S-WEB will send beacon signals for every α degree angle, one at a time.
Sensors that receive the beacons at time slot i will measure their signal strength to determine
their relative distances to the BS. Let T be a predefined distance (which is inversely proportional
to the received signal strength). All sensors which receive beacon signals at angle order βi (=i*α)
with signal strength of δj*T (within sector j) will be in the same group/cluster, denoted as (βi, δj).
Nodes with the same (β, δ) or in the same cluster can select a CH based on its residual energy.
Since nodes in the same cluster know about each other, the role of being a CH can be rotated to
prolong the lifespan of CH. S-WEB is a hybrid technique since most tasks are performed by the
nodes, except the beacons are generated from the BS.
2.1 Open Research Issues
For large scale wireless sensor networks, clustering is most convenient and a useful topology
management approach to reduce the communication overhead and exploit data aggregation in
sensor networks. Large number of clustering algorithms is present but energy consumption
during cluster formation and maintenance is still high. There are lot of compelling challenges for
clustering algorithms i.e. to schedule concurrent intra-cluster and inter-cluster transmissions, to
compute the optimal cluster size, and to determine the optimal frequency for cluster head rotation
in order to maximize the network lifetime, to handle heterogeneous network, to set boundaries of
the cluster, rotation of the cluster head if mobility is applied, reorganizing clusters when some of
the sensor nodes are dying.
3. DATA PROCESSING WITHIN THE NETWROK
In WSNs, aggregation techniques and routing protocols are not independent, rather
interdependent. Routing protocol design takes into consideration the targeted data aggregation at
some network nodes and accordingly decides packet routing mechanism. Similarly, while
designing aggregation technique the routing protocol used underneath plays a vital role.
3.1 Data Aggregation within the network
In WSNs, data generated by different sensors can be jointly processed while being forwarded
toward the sink. Data aggregation is the simplest type of in-network processing which combines
data from different sources or nodes into a single entity. Data aggregation techniques are closely
related to the way data is gathered at SNs as well as how packets are routed through the
network. Data Aggregation has significant impact on energy consumption and overall network
efficiency. However, data size reduction through in-network processing should not diminish
required granularity of information about the monitored event. Also, apart from reducing many
network overheads, it should be useful in enhancing network lifetime. According to [18], “in-
network aggregation is the global process of gathering and routing information through a multi-
hop network, processing data at intermediate nodes with the objective of reducing energy
consumption, thereby increasing network lifetime”.
3.2 Types of Data Aggregation in WSN
Data aggregation can be classified as in-network aggregation with data size reduction and in-
network aggregation without data size reduction.
Aggregation With Data Size Reduction: This is a process of combining data from different
sources to a data unit which is much smaller than the total size of individual data from different
sources. The aim is to reduce the size of information to be sent over the network.
Aggregation Without Data Size Reduction: If data packets from different sources or nodes are
combined into one packet without any processing like, average, min, max, median etc. For
example, suppose SNs are programmed to measure two different event parameters namely
temperature and pressure. A cluster-head node receives a packet comprising temperature
reading from one node and pressure reading from another. These two readings cannot be
5. Nidhi Gautam, Prof. Sanjeev Sofat & Prof. Renu Vig
International Journal of Computer Networks (IJCN), Volume (4) : Issue (1) : 2012 26
averaged but surely can be put into one larger packet as such and instead of two separate
packets cluster-head transmits single packet.
3.3 Data Aggregation Strategies
Though most data-aggregation protocols can be classified according to the network architecture,
some protocols pursue a different approach where sensor network is represented as a graph.
Such protocols where data aggregation is modeled as a network flow problem are classified as
network-flow-based protocols. The main goal of network-flow-based protocols is optimization of
network lifetime considering energy constraints on sensor nodes and flow constraints on
information routed in the network[19].
Kalpakis et al. [20] studied the maximum lifetime data gathering with aggregation (MLDA)
problem employing efficient data-aggregation algorithms. The goal of the MLDA problem is to
obtain a data-gathering schedule with maximum lifetime where sensors aggregate incoming data
packets. The sensor network is modeled as a directed graph. The edges of G have an associated
capacity which indicates the number of packets transmitted from node i to node j. An optimal
admissible flow network is obtained using integer programming with linear constraints. The
integer program computes the maximum system lifetime T subject to energy constraints of the
sensors and capacity constraints on the edges. To alleviate this problem, a clustering-based
approach called greedy CMLDA has been proposed to obtain efficient data gathering schedules
in large networks. Each cluster is referred to as a super-sensor. A maximum lifetime schedule is
first obtained for the super-sensors which is then used to construct aggregation trees for the
sensors. The initial energy of each super-sensor is equal to the sum of the initial energies of all
the sensors within it. The time complexity of the approach is polynomial in the number of sensors,
which involves solving a linear program with O(m
3
) variables where m is the number of clusters
[21].
Xue et al. [21] have studied the data-aggregation problem in the context of energy efficient
routing for maximizing system lifetime. The problem was modeled as a multicommodity flow
problem, where the data generated by a sensor node is analogous to a commodity. The objective
of the multicommodity flow problem is to maximize the network lifetime T (time until first node
dies), subject to flow conservation and energy constraints. A Maxconcurrent flow (Maxlife)
algorithm was proposed which computes a shortest path for one commodity at each iteration of
the algorithm. This is followed by updating the weight of each sensor Sk which represents the
marginal cost of using an additional unit of the sensor’s energy reserve. Since all data sources
share a common destination, a shortest path tree rooted at the data sink is eventually formed. For
the multi-sink data-aggregation problem, a modification of Dijkstra’s shortest path tree algorithm
has been used. The objective is to compute an aggregation forest which is a unification of M trees
routed at data sinks 1, 2, …, M [19].
Hong et al. [22] have formulated data gathering problem as a restricted flow optimization problem.
The goal of maximal data gathering problem (MDG) is to maximize the number of data gathering
rounds subject to the energy constraints of the sensors. The energy constraints on the nodes are
transformed into edge capacitates. The quota constraint requires each node to generate a fixed
number of packets in a given round. The MDG problem is reduced to a restricted flow problem
with edge capacities (RFEC). The sensor network is modeled as a graph and the RFEC problem
determines whether or not there exists a data flow which satisfies the flow constraints, quota
constraint, and the edge-capacity constraints. The RFEC algorithm finds the shortest augmenting
path P from the source to the sink. The RFEC algorithm obtains an integer valued solution that
specifies the number of data packets to be transferred between two neighboring sensors for each
round. The shortest path heuristic may not obtain the optimal solution because it searches over
possible paths in the original graph instead of the residual graph. Examples have been presented
in [22] where for networks with four or more sensors, the MLDA algorithm [20] achieves only 50
percent of the optimal system lifetime [19].
6. Nidhi Gautam, Prof. Sanjeev Sofat & Prof. Renu Vig
International Journal of Computer Networks (IJCN), Volume (4) : Issue (1) : 2012 27
In sensor networks, the data gathered by spatially close sensors are usually correlated. Cristescu
et al. [23] have studied the problem of network-correlated data gathering. When sensors use
source coding strategies, then there is a joint optimization problem which involves optimizing rate
allocation at the nodes and the transmission structure. Slepian–Wolf coding and joint entropy
coding with explicit communication have been investigated in the context of data gathering. In
Slepian– Wolf coding, optimal coding allocates higher rates to nodes closer to the sink and
smaller rates to the nodes at the extremity of the network. In the explicit communication model,
larger rates are allocated to nodes farther from the sink and smaller rates to nodes closer to the
sink. The sensor network is represented as a weighted graph.
An optimal Slepain–Wolf rate allocation scheme has been proposed in [23]. In this scheme, the
closest node to the sink codes data at a rate equal to its unconditioned entropy. All other nodes
code at a rate equal to their respective entropies conditioned on all nodes which are closer to the
sink than themselves. The main disadvantage of this scheme is that each sensor requires global
knowledge of the network in terms of distances between all nodes. To overcome this problem, a
fully distributed approximation algorithm has been proposed which provides solutions close to the
optimum. In this scheme, data are coded locally at each node, and the conditioning is performed
only on the neighbor nodes which are closer to the sink than the respective node.
3.4 Open Research Issues
Despite of lot of research in In-network data aggregation, there are still open research gaps
present i.e. to build data management frameworks for various application-specific data
aggregation schemes, data naming is another aspect of data management which needs ore
exploration, disparity between the amount of data generated and actual data required for data
transmission, In dense networks, significant correlation is expected which helps in reducing the
size of data.
4. MOBILITY
Mobility can finally be used as a tool for reducing energy consumption. In a static sensor network
packets coming from sensor nodes follow a multi-hop path towards the sink(s). Thus, a few paths
can be more loaded than others, and nodes closer to the sink have to relay more packets so that
they are more subject to premature energy depletion (funneling effect). If some of the nodes
(including, possibly, the sink) are mobile, the traffic flow can be altered if mobile devices are
responsible for data collection directly from static nodes
4.1 Mobile Sensor Nodes
Howard et al. [24] presented an algorithm for robotic sensors to maximize coverage while
maintaining line-of-sight contact among robots. Howard et al. [25] in another paper presented a
theory of potential field to distribute the mobile sensors throughout a given area. It also presents
an algorithm to repel mobile sensors from obstacles and other nodes. Goldenberg et al. [26]
presented an idea to have the sensors move into positions that minimize the energy cost of
reporting streams of data to the sink, which is tactically placed. Wang et al. [27] proposed a
protocol that aims at moving mobile sensors from densely deployed areas to areas with coverage
holes, where for some sensors a limited number of sensors have been deployed. Wang et al. [28]
in another paper suggests that nodes move logically to minimize energy consumption and
maximum area coverage. Rao et al. [29] presented a mobility algorithm to reduce transmission
power needed to send data to static sink. Positions of moving sensors are determined via
“distributed annealing” [29].
4.2 Mobile Relays
The concept of Mobile Relays is proposed by Chatzigiannakis et al. in 2004. Shah et al. [30]
introduced a scheme of MULEs i.e. forwarding agents with single hop networks. An algorithm is
proposed for avoiding sensor nodes buffer overflow while minimizing the speed of mobile relays.
The algorithm is extended by having “urgent” flag with the urgent messages. The investigation of
controlled use of relay nodes for data collection and subsequent report to the sink is proposed by
7. Nidhi Gautam, Prof. Sanjeev Sofat & Prof. Renu Vig
International Journal of Computer Networks (IJCN), Volume (4) : Issue (1) : 2012 28
Kim et al. [31]. It is proved that MULEs are effective for energy conservation in so-called delay
tolerant networks i.e. energy is traded off for latency is explained by Small et al. [32]. It means
that the energy needed to communicate a packet to the sink is decreased at the cost of waiting
for a MULE to pass by and cost of waiting for the MULE to reach sink node. Song et al. [33]
studied a model of sensor-o-sink transmission. Tirta et al. [34] stated that nodes send data to
cluster-heads in a multi-hop fashion. Tirta et al. [35] in another paper states that unmanned
Relays can only visit to cluster-heads. Relays are recharged at sink nodes. Different classes of
nodes and controlled and uncontrolled movement of collectors are considered. Its goal was to
schedule collector’s visit to the nodes to minimize transmission energy consumption, data latency
and nodal buffer requirements. Kansal et al. [36] discussed that how to include mobile relays into
the network. An implementation with one mobile relay (robot) is presented with single-hop
communication and network application priorities.
Jea et al. [37] Extended the work of Kansal et al. [36] with multiple controlled mobile elements. It
considers two cases: first was to deploy nodes uniformly and randomly and second was to
distribute nodes differently i.e. non-uniformly. In the first case, criteria is given to chose number of
nodes by number of MULEs and in second case, a load balancing algorithm is introduced for
distributed number of nodes to number of MULEs. MULEs travel in a straight line and gathers
information. They elect a leader and sends whole of the data to the leader. The leader runs the
load-balancing algorithm. It tackled the problem of scheduling visit to the sensor nodes of a single
relay. Somasundara et al. [38] states that the corresponding Mobile Element Scheduling (MES)
problem is proven to be NP – Complete and Centralized analytical model (ILP) and algorithms
are given for solving the problem. Somasundara et al. [39] in another paper discussed on the
advantages and challenges of controlled mobility.
Ekici et al. [40] discussed a new approach to exploit mobility (Morph) and benefits to sensor
network sustainability. Wang et al. [41] in another paper addressed the use of controlled mobility
and defined how mobility introduces improvements in wireless sensor networks performance.
Giuseppe et al. [42] presented a systematic and comprehensive taxonomy of the energy
conservation schemes. It also considered techniques for energy efficient data acquisition.
4.3 Mobile Sinks
Directed diffusion, TTDD, ADMR algorithms with static sink are presented in [43–45] respectively.
Scalable Energy-Efficient Asynchronous Dissemination (SEAD) where a tree-like communication
structure is built and maintained is presented. The sink moves randomly to sensor nodes in the
tree. Communication between sink and the access points can be multi-hop. The trade offs are
that the data latency and energy needed for tree reconfiguration. Tong et al. [46] states that this
algorithm is best for data dissemination with mobile sink. The main contribution is towards energy
efficient transmission to the passing sink [47–50]. Sinks move along the same route repeatedly.
Hwang et al. [50] determines the transmission range needed to collect data from a predefined
percentage of the sensor nodes, given the observer speed, the time required to transmit a packet,
and different traffic patterns. Various methods for building and maintaining routes to a mobile sink
are presented [51–53]. Hu et al. [51] presents local update techniques for detecting
disconnections and performs route repair in “sink-oriented trees”. Akkaya et al. [52] proposed
ERUP protocol for conducting route rediscovery only in the vicinity of the damaged route. Xuan et
al. [53] presents initial route building. Sink moves, if route is invalid, forwarded nodes are
designated to extend the current. Sink moves according to the random waypoint model [46, 48,
54]. Sink (airplanes) are introduced where movement of sink is fully controlled.
Heterogeneous sensor networks with two types of nodes: Type 0 and Type 1. Type 0 does basic
sensing; perform short-range communications partitioned into clusters are presented. Type 1
nodes are the cluster-heads. They do sensing, aggregation and perform long range
communication. Kansal et al. [49] in another paper aims to determine the optimum node
deployment nodal energy needed to achieve a given network lifetime while ensuring sensing
coverage and radio connectivity with high probability. The inherent pattern of the sink movement
for the design of robust and energy-efficient routing is exploited. Baruah at al. [55] states that the
8. Nidhi Gautam, Prof. Sanjeev Sofat & Prof. Renu Vig
International Journal of Computer Networks (IJCN), Volume (4) : Issue (1) : 2012 29
sensor nodes learn about sink whereabouts at given times via statistics techniques as well as
methods from distributed reinforcement learning.
Network controlled sink mobility for reducing energy consumption and for maximizing the lifetime
of a sensor network is presented. An ILP model is presented that determines the locations of
multiple sinks as well as the routes from the sensors to the sinks. Time is divided into rounds.
Each round calculates the next location of sink by considering minimum energy consumption
parameter. ILP is solved at every round [55–58]. The problem of network lifetime maximization
through controlled sink mobility for networks with single sink is addressed. Sink has no limitation
for time spent at each node, no location constraint. The network lifetime is improved by five times.
Sink moves at five positions in a grid. A solution that provides two times more lifetime than [57] is
presented. It solves the problem of determining the sink sojourn times at the given sites. It also
presents routing of the packets to the current position of the sink [59]. The idea of lifetime
maximization as a min-max problem is proposed. Together sink mobility and data routing is
considered. A load balancing solution is presented that, while keeping the sink moving along the
external perimeter of the network, achieves lifetimes 500% higher than when the sink stays still in
the center of the network [24]. Mixed Integer Linear Programming (MILP) considers data
communication cost constraints of sensor network and sink mobility [60–61]. GMRE, heuristic
approach, TTDD and SEAD are explained in [42].
4.4 Open Research Issues
In case of mobile sensor nodes, the cost associated with the sensor movement as well as the
cost of transmitting sensed data is not yet explored. Lot of research is done in controlled mobility
of relay nodes but there is a scope of improvement in case of uncontrolled mobility. Different
network topologies and routing algorithms can be implemented in case of mobile relay nodes. Till
now, static sinks are being deployed and proved to provide better network efficiency but more
than one sink and mobility of sink needs to be explored more with different network topology and
routing algorithms.
5. CONCLUSIONS
Wireless Sensor Networks is the fastest growing area and considered as the revolutionary
concept of the present and future. Lot of work is reported on single-hop and multi-hop clustering.
Due to which cluster-head nodes die faster and cluster-head nodes nearer to sink nodes become
relay nodes for whole of the network. Very less work is reported on increasing the lifetime of
those relay nodes. Lot of work in WSN study exists to reduce energy consumption in a WSN. Few
of them are: to compress data before dissemination; to find optimal paths between source and
sink for data transfer; to find proper aggregation points in the network; aggregate smaller units
into larger units (fusion) for transmission from different sources or generated at different times.
Lot of work is reported in the review about exploiting correlation to decide when to do aggregation
and how to forward highly correlated data as well as unrelated data. However, insignificant work
yet exists to block and isolate undesired/unnecessary data nearer to its source of generation
based on its value. Blocking such data early in its journey towards sink can avoid many
unnecessary inter-node transmissions resulting in energy savings. Lot of work is reported on
sensor nodes movement but cost associated with the sensor movements and cost associated for
transmitting sensed data is not considered. Lot of models have been proposed for Relay node’s
movement by existing protocols but new routing protocols for sensors- relay nodes and relay-sink
nodes need to be developed. Energy conservation is another area, which is not covered
extensively so far. Very less work is reported on timely discovery of mobile elements and
transmission scheduling at sensors. Very less work is reported on the possibility of collision,
corresponding energy cost, cost of building and maintaining routes, impact on network lifetime in
case of sink nodes.Our survey covers almost all the areas from data collection at sensor nodes to
data dissemination to the sink nodes and discusses the research gaps at every step.
9. Nidhi Gautam, Prof. Sanjeev Sofat & Prof. Renu Vig
International Journal of Computer Networks (IJCN), Volume (4) : Issue (1) : 2012 30
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