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.
Data Dissemination in Wireless Sensor Networks: A State-of-the Art SurveyCSCJournals
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.
Review on Clustering and Data Aggregation in Wireless Sensor NetworkEditor IJCATR
This document provides a review of clustering and data aggregation techniques in wireless sensor networks. It begins with an introduction to wireless sensor networks and their characteristics. It then discusses clustering, which involves grouping sensor nodes into clusters headed by cluster heads. Different clustering models are described, including hierarchical clustering. The document also reviews data aggregation techniques, which aim to reduce data redundancy and save energy. It outlines common data aggregation protocols for flat and hierarchical network architectures, such as cluster-based, chain-based, tree-based and grid-based approaches. Finally, it summarizes key clustering routing protocols and data aggregation algorithms.
Energy Consumption Reduction in Wireless Sensor Network Based on ClusteringIJCNCJournal
ABSTRACT
One of the important issues in the routing protocol design in Wireless Sensor Networks (WSNs) is minimizing energy consumption and maximizing network lift time. Nowadays networks and information systems are one of the main parts of modern life that without them, people cannot live. On the hand, the impairment of these networks leads to great and incalculable costs. In this paper, a new method based on clustering has presented that problem of energy consumption is solved. The proposed algorithm is that energy-based clustering can create clusters of the same energy level and distribute energy efficiency across the WNS nodes. This proposed clustering protocol classify network nodes based on energy and neighbourhood criteria and attempts to better balance energy in clusters and ultimately increase network lifetime and maintain network coverage. Results are shown that the proposed algorithm is on average 40% better than LEACH algorithm and 14% better than IBLEACH algorithm.
KEYWORDS
Wireless Sensor Network, Clustering, LEACH Algorithm, IBLEACH Algorithm
Abstract Link : http://aircconline.com/abstract/ijcnc/v11n2/11219cnc03.html
Full Details : http://aircconline.com/ijcnc/V11N2/11219cnc03.pdf
HERF: A Hybrid Energy Efficient Routing using a Fuzzy Method in Wireless Sens...ijdpsjournal
Wireless Sensor Network (WSN) is one of the major research areas in computer network field today.Data
dissemination is an important task performed by wireless sensor networks. The routing algorithms of this
network depend on a number of factors such as application areas, usage condition, power, aggregation
parameters. With respect to these factors, different algorithms are recommended. One of the most
important features of routing algorithms is their flexibility and ability to self-organize themselves
according to such parameters. The existence of flexibility in routing protocols can satisfy calls for on
demand and table driven methods. Switching between these two methods would be impossible except by
compatibility between nodes' and switcher. Energy is another significant factor in wireless sensor
networks due to limited battery power and their exchangeability. To arrive at a network with mentioned
features, we have proposed an algorithm for hybrid energy efficient routing in wireless sensor networks
which uses two algorithms, i.e. EF-Tree (Earliest-First Tree) and SID (Source-Initiated Dissemination) to
disseminate data, and employs a fuzzy method to choose cluster head, and to switch between two
methods, i.e. SID and EF-Tree. In this routing, the whole network is clustered and the appropriate clusterhead
is selected according to fuzzy variables. Then, analyzing the changes in fuzzy variables and If fuzzy,
then rule, one routing in EF-Tree or SID is chosen for information transmission. The results of
simulations indicate that HERF has improved energy efficiency.
ENERGY-EFFICIENT MULTI-HOP ROUTING WITH UNEQUAL CLUSTERING APPROACH FOR WIREL...IJCNCJournal
This document summarizes a research paper that proposes a new routing protocol called Energy-efficient Multi-hop routing with Unequal Clustering (EMUC) for wireless sensor networks. EMUC aims to balance energy consumption between nodes and extend network lifetime by using unequal clustering and multi-hop communication. It creates clusters of different sizes based on distance from the base station. Data is transmitted from cluster members to heads, and between heads to the base station, using multiple hops to reduce transmission costs. Simulation results show EMUC balances energy usage, mitigates hotspot issues, and significantly prolongs network lifetime compared to other clustering routing protocols.
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.
Hierarchical Coordination for Data Gathering (HCDG) in Wireless Sensor NetworksCSCJournals
A wireless sensor network (WSN) consists of large number of sensor nodes where each node operates by a finite battery for sensing, computing, and performing wireless communication tasks. Energy aware routing and MAC protocols were proposed to prolong the lifetime of WSNs. MAC protocols reduce energy consumption by putting the nodes into sleep mode for a relatively longer period of time; thereby minimizing collisions and idle listening time. On the other hand, efficient energy aware routing is achieved by finding the best path from the sensor nodes to the Base Sta-tion (BS) where energy consumption is minimal. In almost all solutions there is always a tradeoff between power consumption and delay reduction. This paper presents an improved hierarchical coordination for data gathering (HCDG) routing schema for WSNs based on multi-level chains formation with data aggregation. Also, this paper provides an analytical model for energy consumption in WSN to compare the performance of our proposed HCDG schema with the near optimal energy reduction methodology, PEGASIS. Our results demonstrate that the proposed routing schema provides relatively lower energy consumption with minimum delay for large scale WSNs.
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.
Data Dissemination in Wireless Sensor Networks: A State-of-the Art SurveyCSCJournals
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.
Review on Clustering and Data Aggregation in Wireless Sensor NetworkEditor IJCATR
This document provides a review of clustering and data aggregation techniques in wireless sensor networks. It begins with an introduction to wireless sensor networks and their characteristics. It then discusses clustering, which involves grouping sensor nodes into clusters headed by cluster heads. Different clustering models are described, including hierarchical clustering. The document also reviews data aggregation techniques, which aim to reduce data redundancy and save energy. It outlines common data aggregation protocols for flat and hierarchical network architectures, such as cluster-based, chain-based, tree-based and grid-based approaches. Finally, it summarizes key clustering routing protocols and data aggregation algorithms.
Energy Consumption Reduction in Wireless Sensor Network Based on ClusteringIJCNCJournal
ABSTRACT
One of the important issues in the routing protocol design in Wireless Sensor Networks (WSNs) is minimizing energy consumption and maximizing network lift time. Nowadays networks and information systems are one of the main parts of modern life that without them, people cannot live. On the hand, the impairment of these networks leads to great and incalculable costs. In this paper, a new method based on clustering has presented that problem of energy consumption is solved. The proposed algorithm is that energy-based clustering can create clusters of the same energy level and distribute energy efficiency across the WNS nodes. This proposed clustering protocol classify network nodes based on energy and neighbourhood criteria and attempts to better balance energy in clusters and ultimately increase network lifetime and maintain network coverage. Results are shown that the proposed algorithm is on average 40% better than LEACH algorithm and 14% better than IBLEACH algorithm.
KEYWORDS
Wireless Sensor Network, Clustering, LEACH Algorithm, IBLEACH Algorithm
Abstract Link : http://aircconline.com/abstract/ijcnc/v11n2/11219cnc03.html
Full Details : http://aircconline.com/ijcnc/V11N2/11219cnc03.pdf
HERF: A Hybrid Energy Efficient Routing using a Fuzzy Method in Wireless Sens...ijdpsjournal
Wireless Sensor Network (WSN) is one of the major research areas in computer network field today.Data
dissemination is an important task performed by wireless sensor networks. The routing algorithms of this
network depend on a number of factors such as application areas, usage condition, power, aggregation
parameters. With respect to these factors, different algorithms are recommended. One of the most
important features of routing algorithms is their flexibility and ability to self-organize themselves
according to such parameters. The existence of flexibility in routing protocols can satisfy calls for on
demand and table driven methods. Switching between these two methods would be impossible except by
compatibility between nodes' and switcher. Energy is another significant factor in wireless sensor
networks due to limited battery power and their exchangeability. To arrive at a network with mentioned
features, we have proposed an algorithm for hybrid energy efficient routing in wireless sensor networks
which uses two algorithms, i.e. EF-Tree (Earliest-First Tree) and SID (Source-Initiated Dissemination) to
disseminate data, and employs a fuzzy method to choose cluster head, and to switch between two
methods, i.e. SID and EF-Tree. In this routing, the whole network is clustered and the appropriate clusterhead
is selected according to fuzzy variables. Then, analyzing the changes in fuzzy variables and If fuzzy,
then rule, one routing in EF-Tree or SID is chosen for information transmission. The results of
simulations indicate that HERF has improved energy efficiency.
ENERGY-EFFICIENT MULTI-HOP ROUTING WITH UNEQUAL CLUSTERING APPROACH FOR WIREL...IJCNCJournal
This document summarizes a research paper that proposes a new routing protocol called Energy-efficient Multi-hop routing with Unequal Clustering (EMUC) for wireless sensor networks. EMUC aims to balance energy consumption between nodes and extend network lifetime by using unequal clustering and multi-hop communication. It creates clusters of different sizes based on distance from the base station. Data is transmitted from cluster members to heads, and between heads to the base station, using multiple hops to reduce transmission costs. Simulation results show EMUC balances energy usage, mitigates hotspot issues, and significantly prolongs network lifetime compared to other clustering routing protocols.
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.
Hierarchical Coordination for Data Gathering (HCDG) in Wireless Sensor NetworksCSCJournals
A wireless sensor network (WSN) consists of large number of sensor nodes where each node operates by a finite battery for sensing, computing, and performing wireless communication tasks. Energy aware routing and MAC protocols were proposed to prolong the lifetime of WSNs. MAC protocols reduce energy consumption by putting the nodes into sleep mode for a relatively longer period of time; thereby minimizing collisions and idle listening time. On the other hand, efficient energy aware routing is achieved by finding the best path from the sensor nodes to the Base Sta-tion (BS) where energy consumption is minimal. In almost all solutions there is always a tradeoff between power consumption and delay reduction. This paper presents an improved hierarchical coordination for data gathering (HCDG) routing schema for WSNs based on multi-level chains formation with data aggregation. Also, this paper provides an analytical model for energy consumption in WSN to compare the performance of our proposed HCDG schema with the near optimal energy reduction methodology, PEGASIS. Our results demonstrate that the proposed routing schema provides relatively lower energy consumption with minimum delay for large scale WSNs.
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.
An Integrated Distributed Clustering Algorithm for Large Scale WSN...................................................1
S. R. Boselin Prabhu, S. Sophia, S. Arthi and K. Vetriselvi
An Efficient Connection between Statistical Software and Database Management System ................... 1
Sunghae Jun
Pragmatic Approach to Component Based Software Metrics Based on Static Methods ......................... 1
S. Sagayaraj and M. Poovizhi
SDI System with Scalable Filtering of XML Documents for Mobile Clients ............................................... 1
Yi Yi Myint and Hninn Aye Thant
An Easy yet Effective Method for Detecting Spatial Domain LSB Steganography .................................... 1
Minati Mishra and Flt. Lt. Dr. M. C. Adhikary
Minimizing the Time of Detection of Large (Probably) Prime Numbers ................................................... 1
Dragan Vidakovic, Dusko Parezanovic and Zoran Vucetic
Design of ATL Rules for TransformingUML 2 Sequence Diagrams into Petri Nets..................................... 1
Elkamel Merah, Nabil Messaoudi, Dalal Bardou and Allaoua Chaoui
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
WEIGHTED DYNAMIC DISTRIBUTED CLUSTERING PROTOCOL FOR HETEROGENEOUS WIRELESS S...ijwmn
This document describes a new clustering protocol called WDDC (Weighted Dynamic Distributed Clustering) for heterogeneous wireless sensor networks. WDDC selects cluster heads based on the ratio of a node's residual energy to the average network energy, and also considers the distance between nodes and the base station. WDDC divides the network lifetime into two zones and changes its behavior dynamically between the zones. Simulation results show WDDC outperforms other clustering protocols like SEP and DEEC in terms of energy efficiency and extending network lifetime.
A Cluster-Based Routing Protocol and Fault Detection for Wireless Sensor NetworkIJCNCJournal
The document proposes a new clustering and routing algorithm for wireless sensor networks that aims to extend network lifetime. Key points:
- The algorithm divides nodes into sensing nodes and relay nodes, with relay nodes responsible for forwarding data to reduce cluster head burden.
- It selects cluster heads and relay nodes based on residual energy to distribute load and avoid early node death.
- A routing tree is constructed among relay nodes to transmit data to the base station in a multi-hop manner, selecting next hops based on residual energy and number of child nodes to balance energy usage.
- The goal is to improve energy efficiency, extend network lifetime, and increase data accuracy through mechanisms like clustering, load balancing, and fault detection
Clustering and data aggregation scheme in underwater wireless acoustic sensor...TELKOMNIKA JOURNAL
Underwater Wireless Acoustic Sensor Networks (UWASNs) are creating attentiveness in
researchers due to its wide area of applications. To extract the data from underwater and transmit to
watersurface, numerous clustering and data aggregation schemes are employed. The main objectives of
clustering and data aggregation schemes are to decrease the consumption of energy and prolong the
lifetime of the network. In this paper, we focus on initial clustering of sensor nodes based on their
geographical locations using fuzzy logic. The probability of degree of belongingness of a sensor node to its
cluster, along with number of clusters is analysed and discussed. Based on the energy and distance the
cluster head nodes are determined. Finally using using similarity function data aggregation is analysed and
discussed. The proposed scheme is simulated in MATLAB and compared with LEACH algorithm.
The simulation results indicate that the proposed scheme performs better in maximizing network lifetime
and minimizing energy consumption.
The document presents the outline of a research project on performance evaluation of secure data transmission in wireless sensor networks using IEEE 802.11x standards. The research aims to enhance network lifetime by designing an energy-efficient clustering approach and data aggregation technique. It involves developing a cluster head selection algorithm using genetic algorithms, designing a broadcast tree construction protocol for data transmission, and implementing hash-based authentication. The research will be conducted in phases involving literature review, methodology development, implementation, and performance evaluation. The expected outcomes include reduced data transmission time and improved quality of service through increased network lifetime.
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.
Energy balanced on demand clustering algorithm based on leach-cijwmn
The proposed algorithm aims to improve energy efficiency in wireless sensor networks. It uses a centralized k-means clustering algorithm to form clusters based on minimizing total energy. The base station calculates relevant information for each node, including total network energy, distance to neighbor nodes, and cluster assignment. Nodes then use this information to probabilistically elect cluster heads within each cluster in a distributed manner. The algorithm considers both energy levels and communication distances to select optimal cluster heads. Simulation results show the proposed algorithm outperforms LEACH-C in network lifetime, stability period, and energy efficiency.
This document summarizes research on topology control techniques in wireless sensor networks. It first discusses how topology control aims to reduce energy consumption while maintaining network connectivity by regulating nodes' transmission power. It then reviews several existing topology control algorithms proposed in other papers. These algorithms distribute transmission power control to maximize network lifetime. Finally, the document concludes that many topology control algorithms have been developed to achieve energy efficient routing, but implementing them on real-world testbeds poses challenges.
Mobile Data Gathering with Load Balanced Clustering and Dual Data Uploading i...1crore projects
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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
MULTI-CLUSTER MULTI-CHANNEL SCHEDULING (MMS) ALGORITHM FOR MAXIMUM DATA COLLE...IJCNCJournal
Interference during data transmission can cause performance degradation like packet collisions in Wireless Sensor Networks (WSNs). While multi-channels available in IEEE 802.15.4 protocol standard WSN technology can be exploited to reduce interference, allocating channel and channel switching
algorithms can have a major impact on the performance of multi-channel communication. This paper presents an improved Fuzzy Logic based Cluster Formation and Cluster Head (CH) Selection algorithm with enhanced network lifetime for multi-cluster topology. The Multi-Cluster Multi-Channel Scheduling
(MMS) algorithm proposed in this paper improves the data collection by minimizing the maximum interference and collision. The presented work has developed Cluster formation and cluster head (CH) selection algorithm and Interference-free data communication by proper channel scheduled. The extensive
simulation and experimental outcomes prove that the proposed algorithm not only provides an interference-free transmission but also provides delay minimization and longevity of the network lifetime, which makes the presented algorithm suitable for energy-constrained wireless sensor networks.
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.
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.
Energy-Efficient Improved Optimal K-Means: Dynamic Cluster Head Selection bas...IJCNCJournal
The document proposes an Energy-Efficient Improved Optimal K-means clustering protocol for mobile wireless sensor networks in IoT applications. The protocol aims to prolong network lifetime by delaying the first node death through dynamic cluster head selection based on remaining energy, distance to cluster center, and node mobility. Simulation results show the proposed protocol improves first node lifetime by 11%, throughput by 43%, and energy efficiency by 44% compared to the previous Improved K-means approach.
Energy-Efficient Improved Optimal K-Means: Dynamic Cluster Head Selection bas...IJCNCJournal
The Internet of Things (IoT), which attaches dynamic devices that can access the Internet to create a smart environment, is a tempting research area. IoT-based mobile wireless sensor networks (WSN-IoT) are one of the major databases from which the IoT collects data for analysis and interpretation. However, one of the critical constraints is network lifetime. Routing-based clustered protocols and cluster head (CH) selection are crucial in load balancing and sensor longevity. Yet, with clustering, sensor node mobility requires more overhead because the nodes close to the center may get far and thus become unsuitable to be a CH, whereas those far from the center may get close and become good CH candidates, influencing energy consumption. This paper suggests an energy-efficient clustering protocol with a dynamic cluster head selection considering the distance to the cluster center, remaining energy, and each node's mobility degree implementing a rotation mechanism that allows cluster members to be equally elected while prioritizing those with the minimum weight. The advised algorithm aims to delay the first node death (FND) and thus prolong the stability period and minimize energy consumption by avoiding re-clustering. The performance of the proposed protocol exceeds that achieved in our previous work, Improved OK-means, by 11%, in first dead node lifetime maximization, 43% in throughput, and 44% in energy efficiency.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
The document proposes a new method to increase the lifetime of wireless sensor networks. It divides the sensor network environment into two virtual layers based on distance from the base station. It then uses residual energy, distance from base station, and position in the layers as factors in selecting cluster heads. Simulations show the proposed method outperforms LEACH and ELEACH algorithms in both homogeneous and heterogeneous sensor energy environments.
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption.
Simulation Based Analysis of Cluster-Based Protocol in Wireless Sensor Networkjosephjonse
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.
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.
This document compares and contrasts several common cluster-based routing algorithms for wireless sensor networks, including LEACH, TEEN, APTEEN, HEED, and PEGASIS. It discusses the advantages and disadvantages of each algorithm, with a focus on their approaches to energy efficiency. LEACH randomly selects cluster heads and uses TDMA, but assumes equal energy levels and that all nodes can reach the base station. TEEN and APTEEN add thresholds to improve energy efficiency for time-critical applications. HEED selects cluster heads based on both residual energy and node degree to balance energy use. The document provides an overview of the key clustering algorithms and issues to consider when choosing an approach.
An Integrated Distributed Clustering Algorithm for Large Scale WSN...................................................1
S. R. Boselin Prabhu, S. Sophia, S. Arthi and K. Vetriselvi
An Efficient Connection between Statistical Software and Database Management System ................... 1
Sunghae Jun
Pragmatic Approach to Component Based Software Metrics Based on Static Methods ......................... 1
S. Sagayaraj and M. Poovizhi
SDI System with Scalable Filtering of XML Documents for Mobile Clients ............................................... 1
Yi Yi Myint and Hninn Aye Thant
An Easy yet Effective Method for Detecting Spatial Domain LSB Steganography .................................... 1
Minati Mishra and Flt. Lt. Dr. M. C. Adhikary
Minimizing the Time of Detection of Large (Probably) Prime Numbers ................................................... 1
Dragan Vidakovic, Dusko Parezanovic and Zoran Vucetic
Design of ATL Rules for TransformingUML 2 Sequence Diagrams into Petri Nets..................................... 1
Elkamel Merah, Nabil Messaoudi, Dalal Bardou and Allaoua Chaoui
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
WEIGHTED DYNAMIC DISTRIBUTED CLUSTERING PROTOCOL FOR HETEROGENEOUS WIRELESS S...ijwmn
This document describes a new clustering protocol called WDDC (Weighted Dynamic Distributed Clustering) for heterogeneous wireless sensor networks. WDDC selects cluster heads based on the ratio of a node's residual energy to the average network energy, and also considers the distance between nodes and the base station. WDDC divides the network lifetime into two zones and changes its behavior dynamically between the zones. Simulation results show WDDC outperforms other clustering protocols like SEP and DEEC in terms of energy efficiency and extending network lifetime.
A Cluster-Based Routing Protocol and Fault Detection for Wireless Sensor NetworkIJCNCJournal
The document proposes a new clustering and routing algorithm for wireless sensor networks that aims to extend network lifetime. Key points:
- The algorithm divides nodes into sensing nodes and relay nodes, with relay nodes responsible for forwarding data to reduce cluster head burden.
- It selects cluster heads and relay nodes based on residual energy to distribute load and avoid early node death.
- A routing tree is constructed among relay nodes to transmit data to the base station in a multi-hop manner, selecting next hops based on residual energy and number of child nodes to balance energy usage.
- The goal is to improve energy efficiency, extend network lifetime, and increase data accuracy through mechanisms like clustering, load balancing, and fault detection
Clustering and data aggregation scheme in underwater wireless acoustic sensor...TELKOMNIKA JOURNAL
Underwater Wireless Acoustic Sensor Networks (UWASNs) are creating attentiveness in
researchers due to its wide area of applications. To extract the data from underwater and transmit to
watersurface, numerous clustering and data aggregation schemes are employed. The main objectives of
clustering and data aggregation schemes are to decrease the consumption of energy and prolong the
lifetime of the network. In this paper, we focus on initial clustering of sensor nodes based on their
geographical locations using fuzzy logic. The probability of degree of belongingness of a sensor node to its
cluster, along with number of clusters is analysed and discussed. Based on the energy and distance the
cluster head nodes are determined. Finally using using similarity function data aggregation is analysed and
discussed. The proposed scheme is simulated in MATLAB and compared with LEACH algorithm.
The simulation results indicate that the proposed scheme performs better in maximizing network lifetime
and minimizing energy consumption.
The document presents the outline of a research project on performance evaluation of secure data transmission in wireless sensor networks using IEEE 802.11x standards. The research aims to enhance network lifetime by designing an energy-efficient clustering approach and data aggregation technique. It involves developing a cluster head selection algorithm using genetic algorithms, designing a broadcast tree construction protocol for data transmission, and implementing hash-based authentication. The research will be conducted in phases involving literature review, methodology development, implementation, and performance evaluation. The expected outcomes include reduced data transmission time and improved quality of service through increased network lifetime.
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.
Energy balanced on demand clustering algorithm based on leach-cijwmn
The proposed algorithm aims to improve energy efficiency in wireless sensor networks. It uses a centralized k-means clustering algorithm to form clusters based on minimizing total energy. The base station calculates relevant information for each node, including total network energy, distance to neighbor nodes, and cluster assignment. Nodes then use this information to probabilistically elect cluster heads within each cluster in a distributed manner. The algorithm considers both energy levels and communication distances to select optimal cluster heads. Simulation results show the proposed algorithm outperforms LEACH-C in network lifetime, stability period, and energy efficiency.
This document summarizes research on topology control techniques in wireless sensor networks. It first discusses how topology control aims to reduce energy consumption while maintaining network connectivity by regulating nodes' transmission power. It then reviews several existing topology control algorithms proposed in other papers. These algorithms distribute transmission power control to maximize network lifetime. Finally, the document concludes that many topology control algorithms have been developed to achieve energy efficient routing, but implementing them on real-world testbeds poses challenges.
Mobile Data Gathering with Load Balanced Clustering and Dual Data Uploading i...1crore projects
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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
MULTI-CLUSTER MULTI-CHANNEL SCHEDULING (MMS) ALGORITHM FOR MAXIMUM DATA COLLE...IJCNCJournal
Interference during data transmission can cause performance degradation like packet collisions in Wireless Sensor Networks (WSNs). While multi-channels available in IEEE 802.15.4 protocol standard WSN technology can be exploited to reduce interference, allocating channel and channel switching
algorithms can have a major impact on the performance of multi-channel communication. This paper presents an improved Fuzzy Logic based Cluster Formation and Cluster Head (CH) Selection algorithm with enhanced network lifetime for multi-cluster topology. The Multi-Cluster Multi-Channel Scheduling
(MMS) algorithm proposed in this paper improves the data collection by minimizing the maximum interference and collision. The presented work has developed Cluster formation and cluster head (CH) selection algorithm and Interference-free data communication by proper channel scheduled. The extensive
simulation and experimental outcomes prove that the proposed algorithm not only provides an interference-free transmission but also provides delay minimization and longevity of the network lifetime, which makes the presented algorithm suitable for energy-constrained wireless sensor networks.
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.
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.
Energy-Efficient Improved Optimal K-Means: Dynamic Cluster Head Selection bas...IJCNCJournal
The document proposes an Energy-Efficient Improved Optimal K-means clustering protocol for mobile wireless sensor networks in IoT applications. The protocol aims to prolong network lifetime by delaying the first node death through dynamic cluster head selection based on remaining energy, distance to cluster center, and node mobility. Simulation results show the proposed protocol improves first node lifetime by 11%, throughput by 43%, and energy efficiency by 44% compared to the previous Improved K-means approach.
Energy-Efficient Improved Optimal K-Means: Dynamic Cluster Head Selection bas...IJCNCJournal
The Internet of Things (IoT), which attaches dynamic devices that can access the Internet to create a smart environment, is a tempting research area. IoT-based mobile wireless sensor networks (WSN-IoT) are one of the major databases from which the IoT collects data for analysis and interpretation. However, one of the critical constraints is network lifetime. Routing-based clustered protocols and cluster head (CH) selection are crucial in load balancing and sensor longevity. Yet, with clustering, sensor node mobility requires more overhead because the nodes close to the center may get far and thus become unsuitable to be a CH, whereas those far from the center may get close and become good CH candidates, influencing energy consumption. This paper suggests an energy-efficient clustering protocol with a dynamic cluster head selection considering the distance to the cluster center, remaining energy, and each node's mobility degree implementing a rotation mechanism that allows cluster members to be equally elected while prioritizing those with the minimum weight. The advised algorithm aims to delay the first node death (FND) and thus prolong the stability period and minimize energy consumption by avoiding re-clustering. The performance of the proposed protocol exceeds that achieved in our previous work, Improved OK-means, by 11%, in first dead node lifetime maximization, 43% in throughput, and 44% in energy efficiency.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
The document proposes a new method to increase the lifetime of wireless sensor networks. It divides the sensor network environment into two virtual layers based on distance from the base station. It then uses residual energy, distance from base station, and position in the layers as factors in selecting cluster heads. Simulations show the proposed method outperforms LEACH and ELEACH algorithms in both homogeneous and heterogeneous sensor energy environments.
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption
CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS ...IJCSES Journal
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network.
Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes,
and this has significant effects on the network's energy consumption. The objective of this paper is to
analyze existing cluster head selection algorithms and the parameters they implement to enhance energy
efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers
were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library,
Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster
Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These
algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more
parameters that can be used to elect cluster heads to improve on energy consumption.
Simulation Based Analysis of Cluster-Based Protocol in Wireless Sensor Networkjosephjonse
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.
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.
This document compares and contrasts several common cluster-based routing algorithms for wireless sensor networks, including LEACH, TEEN, APTEEN, HEED, and PEGASIS. It discusses the advantages and disadvantages of each algorithm, with a focus on their approaches to energy efficiency. LEACH randomly selects cluster heads and uses TDMA, but assumes equal energy levels and that all nodes can reach the base station. TEEN and APTEEN add thresholds to improve energy efficiency for time-critical applications. HEED selects cluster heads based on both residual energy and node degree to balance energy use. The document provides an overview of the key clustering algorithms and issues to consider when choosing an approach.
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
Energy Efficient Data Mining in Multi-Feature Sensor Networks Using Improved...IOSR Journals
This document proposes an improved LEACH (Low-Energy Adaptive Clustering Hierarchy) communication protocol for energy efficient data mining in multi-feature sensor networks. The original LEACH protocol has drawbacks like random cluster head selection and uneven energy consumption. The improved protocol designates both a cluster head and sub-cluster head to take over if the head dies. This addresses the issues with the cluster head dying and the cluster becoming useless. The improved LEACH protocol is proposed to cluster sensor nodes in multi-feature networks to enhance energy efficiency and reliability of data transfer compared to the original LEACH protocol.
ENERGY EFFICIENT HIERARCHICAL CLUSTER HEAD ELECTION USING EXPONENTIAL DECAY F...ijwmn
This document summarizes an article that proposes an improved algorithm for selecting cluster heads in wireless sensor networks. The algorithm uses an exponential decay function to predict the average energy of sensor nodes and selects cluster heads based on both the probabilistic LEACH algorithm and predicted energy levels. The algorithm was tested in MATLAB simulations of a homogeneous sensor network and showed improvements in stability, average energy dissipation per round, and lifespan over the baseline LEACH protocol.
Routing in Wireless Sensor Networks: Improved Energy Efficiency and Coverage ...CSCJournals
This paper proposes a new method for collecting distributed data in Wireless Sensor Networks (WSNs) that can improve the energy efficiency and network coverage; especially in remote areas. In multi-hop communication, sink nodes are responsible for collecting and forwarding data to base stations. The nodes that are located near a sink node usually deplete their battery faster than other nodes because they are responsible for aggregating the data from other sensor nodes. Several studies have proved the advantages of using mobile sink nodes to reduce energy consumption. Nonetheless, the need for compatible and efficient routing algorithms cannot be understated. Accordingly, a hybrid routing algorithm based on the Dijkstra�s and Rendezvous algorithms is proposed. To improve the energy efficiency and coverage, Energy Efficient Hybrid Unmanned Vehicle Based Routing Algorithm (E2HUV) is proposed to create a routing path for Unmanned Aerial Vehicles (UAVs) that can be used as mobile sinks in WSNs. Performance results show that the E2HUV algorithm offers better efficiency as compared to currently existing algorithms.
Data gathering in wireless sensor networks using intermediate nodesIJCNCJournal
Energy consumption is an essential concern to Wireless Sensor Networks (WSNs).The major cause of the energy consumption in WSNs is due to the data aggregation. A data aggregation is a process of collecting data from sensor nodes and transmitting these data to the sink node or base station. An effective way to perform such a task is accomplished by using clustering. In clustering, nodes are grouped into clusters where a number of nodes, called cluster heads, are responsible for gathering data from other nodes, aggregate them and transmit them to the Base Station (BS).
In this paper we produce a new algorithm which focused on reducing the transmission bath between sensor nodes and cluster heads. A proper utilization and reserving of the available power resources is achieved with this technique compared to the well-known LEACH_C algorithm.
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.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
CLUSTERING-BASED ROUTING FOR WIRELESS SENSOR NETWORKS IN SMART GRID ENVIRONMENTijassn
Wireless Sensor Networks (WSN) is widely deployed in different fields of applications of smart grid to provide reliable monitoring and controlling of the electric power grid. The objective of this paper is simulate and analyze impact of various smart grid environments on performance of four different WSN
routing protocols namely the Low Energy Adaptive Clustering Hierarchy (LEACH) and Centralized LEACH (LEACT-C) as well as other two conventional protocols namely Minimum Transmission Energy (MTE) and Static Clustering. This analysis would be beneficial in making the correct choice of WSN
routing protocols for various smart grid applications. The performance of the four protocols is simulated using NS-2 network simulation on Ubuntu. The results are analyzed and compared using number of data signals received at base station, energy consumption, and network lifetime as performance metrics. The results show that the performance of various protocols in the smart grid environments have deteriorated due log normal channel characteristics and consequently network lifetime have decreased significantly.
The results also indicate that clustering based routing protocols have more advantageous over conventional protocols; MTE and static clustering. Also, centralized clustering approach is more effective as it distributes energy dissipation evenly throughout the sensor nodes which reduce energy consumption
and prolong the networks’ lifetime. This approach is more effective in delivering data to base station because it has global knowledge of the location and energy of all the nodes in the network.
This document summarizes a research paper on developing an improved LEACH (Low-Energy Adaptive Clustering Hierarchy) communication protocol for energy efficient data mining in multi-feature sensor networks. It begins with background on wireless sensor networks and issues like energy efficiency. It then discusses the existing LEACH protocol and its drawbacks. The proposed improved LEACH protocol includes cluster heads, sub-cluster heads, and cluster nodes to address LEACH's limitations. This new version aims to minimize energy consumption during cluster formation and data aggregation in multi-feature sensor networks.
Performance evaluation of data filtering approach in wireless sensor networks...ijmnct
Wireless Sensor Network is a field of research which is viable in every application area like security
services, patient care, traffic regulations, habitat monitoring and so on. The resource limitation of small
sized tiny nodes has always been an issue in wireless sensor networks. Various techniques for improving
network lifetime have been proposed in the past. Now the attention has been shifted towards heterogeneous
networks rather than having homogeneous sensor nodes in a network. The concept of partial mobility has
also been suggested for network longevity. In all the major proposals; clustering and data aggregation in
heterogeneous networks has played an integral role. This paper contributes towards a new concept of
clustering and data filtering in wireless sensor networks. In this paper we have compared voronoi based
ant systems with standard LEACH-C algorithm and MTWSW with TWSW algorithm. Both the techniques
have been applied in heterogeneous wireless sensor networks. This approach is applicable both for critical
as well as for non-critical applications in wireless sensor networks. Both the approaches presented in this
paper outperform LEACH-C and TWSW in terms of energy efficiency and shows promising results for
future work.
INCREASE THE LIFETIME OF WIRELESS SENSOR NETWORKS USING HIERARCHICAL CLUSTERI...ijwmn
Wireless sensor networks consist of hundreds or thousands of nodes with limited energy. Since the life time
of each sensor is equivalent to the battery life, the energy issue is considered as a major challenge.
Clustering has been proposed as a strategy to extend the lifetime of wireless sensor networks. Cluster size,
number of Cluster head per cluster and the selection of cluster head are considered as important factors in
clustering. In this research by studying LEACH algorithm and optimized algorithms of this protocol and by
evaluating the strengths and weaknesses, a new algorithm based on hierarchical clustering to increase the
lifetime of the sensor network is proposed. In this study, with a special mechanism the environment of
network is layered and the optimal number of cluster head in each layer is selected and then recruit for the
formation of clusters in the same layer by controlling the topology of the clusters is done independently.
Then the data is sent through the by cluster heads through the multi- stage to the main station. Simulation
results show that the above mentioned method increases the life time about 70% compared to the LEACH.
INCREASE THE LIFETIME OF WIRELESS SENSOR NETWORKS USING HIERARCHICAL CLUSTERI...ijwmn
Wireless sensor networks consist of hundreds or thousands of nodes with limited energy. Since the life time
of each sensor is equivalent to the battery life, the energy issue is considered as a major challenge.
Clustering has been proposed as a strategy to extend the lifetime of wireless sensor networks. Cluster size,
number of Cluster head per cluster and the selection of cluster head are considered as important factors in
clustering. In this research by studying LEACH algorithm and optimized algorithms of this protocol and by
evaluating the strengths and weaknesses, a new algorithm based on hierarchical clustering to increase the
lifetime of the sensor network is proposed. In this study, with a special mechanism the environment of
network is layered and the optimal number of cluster head in each layer is selected and then recruit for the
formation of clusters in the same layer by controlling the topology of the clusters is done independently.
Then the data is sent through the by cluster heads through the multi- stage to the main station. Simulation
results show that the above mentioned method increases the life time about 70% compared to the LEACH.
Similar to IMPACTS OF STRUCTURAL FACTORS ON ENERGY CONSUMPTION IN CLUSTER-BASED WIRELESS SENSOR NETWORKS: A COMPREHENSIVE ANALYSIS (20)
CYBER SECURITY ENHANCEMENT IN NIGERIA. A CASE STUDY OF SIX STATES IN THE NORT...AJHSSR Journal
ABSTRACT: Security plays an important role in human life and endeavors. Securing information and
disseminating are critical challenges in the present day. This study aimed at identifying innovative technologies
that aid cybercrimes and can constitute threats to cybersecurity in North Central (Middle Belt) Nigeria covering
its six States and the FCT Abuja. A survey research design was adopted. The researchers employed the use of
Google form in administering the structured questionnaire. The instruments were faced validated by one expert
each from ICT and security. Cronbach Alpha reliability Coefficient was employed and achieved 0.83 level of
coefficient. The population of the study was 200, comprising 100 undergraduate students from computer science
and Computer/Robotics Education, 80 ICT instructors, technologists and lecturers in the University and
Technical Colleges in the Middle Belt Nigeria using innovative technologies for their daily jobs and 20 officers
of the crime agency such as: Independent Corrupt Practices Commission (ICPC) andEconomic and Financial
Crimes Commission (EFCC). Three research purposes and questions as well as the hypothesis guided the study
on Five (5) point Likert scale. Data collected were analyzed using mean and standard deviation for the three
research questions while three hypotheses were tested using t-test at 0.05 level of significance. Major findings
revealed that serious steps are needed to better secure the cybers against cybercrimes. Motivation, types, threats
and strategies for the prevention of cybercrimes were identified. The study recommends that government,
organizations and individuals should place emphasis on moral development, regular training of its employees,
regular update of software, use strong password, back up data and information, produce strong cybersecurity
policy, install antivirus soft and security surveillance (CCTV) in offices in order to safeguard its employees and
properties from being hacked and vandalized.
KEYWORDS: Cybersecurity, cybercrime, cyberattack, cybercriminal, computer virus, Virtual Private Networks
(VPN).
STUDY ON THE DEVELOPMENT STRATEGY OF HUZHOU TOURISMAJHSSR Journal
ABSTRACT: Huzhou has rich tourism resources, as early as a considerable development since the reform and
opening up, especially in recent years, Huzhou tourism has ushered in a new period of development
opportunities. At present, Huzhou tourism has become one of the most characteristic tourist cities on the East
China tourism line. With the development of Huzhou City, the tourism industry has been further improved, and
the tourism degree of the whole city has further increased the transformation and upgrading of the tourism
industry. However, the development of tourism in Huzhou City still lags far behind the tourism development of
major cities in East China. This round of research mainly analyzes the current development of tourism in
Huzhou City, on the basis of analyzing the specific situation, pointed out that the current development of
Huzhou tourism problems, and then analyzes these problems one by one, and put forward some specific
solutions, so as to promote the further rapid development of tourism in Huzhou City.
KEYWORDS:Huzhou; Travel; Development
SCHOOL CULTURE ADAPTATION AMONG INDIGENOUS PEOPLES COLLEGE STUDENTS AT A PRIV...AJHSSR Journal
ABSTRACT: This qualitative study investigates the adaption experiences of indigenous college students at the
University of Mindanao, Matina-main campus. Eight major themes emerged, including difficulties with language
proficiency, online learning, classroom interaction, examination systems, grading procedures, school regulations,
resource accessibility, coping mechanisms, and future goals. Implications include the requirement for targeted
language proficiency and technology use support, an understanding of adaption processes, interventions to
improve resource accessibility, and equitable public administration policies. The study underlines the importance
of adaptation in various educational contexts, as well as the role of educators and legislators in creating inclusive
learning environments.
KEYWORDS: indigenous college students, adaptation, educational challenges, coping strategies
The Impact of Work Stress and Digital Literacy on Employee Performance at PT ...AJHSSR Journal
ABSTRACT :This research aims to analyze the correlation between employee work stress and digital literacy
with employee performance at PT Telkom Akses Area Cirebon, both concurrently and partially. Employing a
quantitative approach, the study's objectives are descriptive and causal, adopting a positivist paradigm with a
deductive approach to theory development and a survey research strategy. Findings reveal that work stress
negatively and significantly impacts employee performance, while digital literacy positively and significantly
affects it. Simultaneously, work stress and digital literacy have a positive and significant influence on employee
performance. It is anticipated that company management will devise workload management strategies to
alleviate work stress and assess the implementation of more efficient digital technology to enhance employee
performance.
KEYWORDS -digital literacy, employee performance,job stress, multiple regression analysis, workload
management
On Storytelling & Magic Realism in Rushdie’s Midnight’s Children, Shame, and ...AJHSSR Journal
ABSTRACT: Salman Rushdie’s novels are humorous books about serious times. His cosmopolitanism and
hybrid identity allowed him access to multiple cultures, religions, languages, dialects, and various modes of
writing. His style is often classified as magic realism, blending the imaginary with the real. He draws
inspiration from both English literature and Indian classical sources. Throughout his works, there is a lineage of
‘bastards of history’, a carnival of shameful characters scrolling all along his works. Rushdie intertwines fiction
with reality, incorporating intertextual references to Western literature in his texts, and frequently employing
mythology to explore history. This paper focuses on Rushdie’s three novels: Midnight’s Children, Shame, and
Haroun and the Sea of Stories, analyzing his postmodern storytelling techniques that aim to explore human
vices and follies while offering socio-political criticism.
KEYWORDS : Magic Realism, Rushdie, Satire, Storytelling, Transfictional Identities
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Factors affecting undergraduate students’ motivation at a university in Tra VinhAJHSSR Journal
ABSTRACT: Motivation plays an important role in foreign language learning process. This study aimed to
investigate student’s motivation patterns towards English language learning at a University in Tra Vinh, and factors
affecting their motivation change toward English language learning of non-English-major students in the semester.
The researcher used semi-structured interview at the first phase of choosing the participants and writing reflection
through the instrument called “My English Learning Motivation History” adapted from Sawyer (2007) to collect
qualitative data within 15 weeks. The participants consisted of nine first year non-English-major students who learning
General English at pre-intermediate level. They were chosen and divided into three groups of three members each
(high motivation group; average motivation group; and low motivation group). The results of the present study
identified six visual motivation patterns of three groups of students with different motivation fluctuation, through the
use of cluster analysis. The study also indicated a diversity of factors affecting students’ motivation involving internal
factors as influencing factors (cognitive, psychology, and emotion) and external factors as social factors (instructor,
peers, family, and learning environment) during English language learning in a period of 15 weeks. The findings of
the study helped teacher understand relationship of motivation change and its influential factors. Furthermore, the
findings also inspired next research about motivation development in learning English process.
KEY WORDS: language learning motivation, motivation change, motivation patterns, influential factors, students’
motivation.
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IMPACTS OF STRUCTURAL FACTORS ON ENERGY CONSUMPTION IN CLUSTER-BASED WIRELESS SENSOR NETWORKS: A COMPREHENSIVE ANALYSIS
1. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.6, No.1, February 2015
DOI : 10.5121/ijasuc.2015.6101 1
IMPACTS OF STRUCTURAL FACTORS ON
ENERGY CONSUMPTION IN CLUSTER-BASED
WIRELESS SENSOR NETWORKS: A
COMPREHENSIVE ANALYSIS
Taner Cevik1
and Fatih Ozyurt2
1
Department of Computer Engineering, Fatih University, Istanbul, Turkey
2
Department of Software Engineering, Firat University, Elazig, Turkey
ABSTRACT
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.
KEYWORDS
Wireless Sensor Networks, Clustering, Energy Conservation, Network Lifetime.
1. INTRODUCTION
Incredibly small sized sensor nodes have recently become available on the market with affordable
prices facilitating technological improvements in microelectronics, signal processing, etc. which,
in turn allowed application areas of such sensor nodes in our daily lives to expand rapidly [1-2].
These devices constitute mainly three sub-units: the processor, the sensing and the
communication units [3]. Since these nodes can be self-organized without any intervention after
the deployment stage, they form a Wireless Sensor Network (WSN) which is a subclass of ad-hoc
networks [4]. However, there are significant differences between WSNs and their other ad-hoc
counterparts. First, the nodes in traditional ad-hoc networks communicate mostly in a point-to-
point manner. However, since the nodes in WSNs have limited energy sources, they prefer to
communicate in a multi-hop manner. As pointed out by Akyildiz et al. [5], another important
difference is that nodes in WSNs are deployed in a more intensive manner than the nodes
deployed in traditional ad-hoc networks. Therefore, using the protocols and the methods utilized
for ad-hoc networks will not be effective for WSNs.
As well documented in the literature, the most important drawback of these sensor nodes is the
energy expenditure. Thus, in order to use thousands or millions of these devices in a topology,
energy-aware protocols and architectures should be considered [6-8].
2. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.6, No.1, February 2015
2
The major energy consuming unit of a sensor node is the communication unit. Raghunathan et al.
[9], established that sensor nodes consume much more energy during data communication when
compared with data processing. Hence, researchers have dramatically focused on developing
energy-efficient communication protocols and architectures. Most prominent categories are duty-
cycling methods, data-driven approaches, and clustering.
The key point in duty-cycling is defining a sub-tree of nodes in the topology that will remain
awake while the others go to sleep. In this way, communication throughout the network is still
active while only a portion of the nodes stay awake. Another important point is to define suitable
sleep and wake-up schedules for these nodes in order to provide the sustainability of the network.
Two major subcategories constituting the data driven approach are data acquisition and data
aggregation methods which aim to reduce the amount of data to be conveyed. Data acquisition is
performed at signal level. In contrast, data aggregation is performed at application level. Data
acquisition is adding distinct signals and transmitting data as a single aggregate. However, data
aggregation is something like filtering and summarizing the original data coming from all sensor
nodes.
Another very popular category of methods for lifetime prolongation is clustering. The main idea
in clustering is grouping the sensor nodes depending on a number of criteria, in other words,
virtually partitioning the topology into grids. Clustering can provide significant energy savings
especially in high density networks. In 2011, Kumar et al. indicated that, since the plain nodes in
clusters direct their data to their cluster heads, problems often encountered such as multiple
routes, flooding and routing loops are eliminated or alleviated [10].
This paper presents a comprehensive analysis of the effects of the various structural factors in
terms of energy consumption in WSNs. General belief about cluster-based WSNs is that in order
to alleviate the hot-spot problem, clusters located near the sink should be smaller-sized than the
ones further from the sink. Other possible factors that may affect the lifetime of the network are
the number of tiers, the node density, the communication radio coverage radius, the number and
location of the sinks. All these parameters are examined for all possible combinations in detail.
Identifying the significant role of clustering in network lifetime prolongation, the rest of the paper
is organized as follows. In Section 2, we briefly describe the idea of clustering by examining a
rich number of studies conducted on this topic. In Section 3, we provide information about the
methods and architectures utilized during simulations. Section 4 is devoted for graphical
presentation of the simulation results and discussion. Lastly, in Section 5 we provide concluding
remarks.
2. RELATED WORK
Clustering is virtually slicing the network topology into grids (Figure 1) and grouping the sensor
nodes under these grids according to a number of benchmarks.
3. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.6, No.1, February 2015
3
Figure 1. Voronoi based clustering
One of the nodes in each cluster is charged with being cluster head (CH). Other nodes in the
cluster which are called plain nodes gather data from the environment and deliver it to the CH
node. CH is responsible for conveying the overall data gathered in its cluster to the sink. In
traditional non-cluster based sensor networks, each sensor node gathers data from physical
environment and aims to transmit its data to the sink somehow. If it is thought that all the nodes
in the topology try to deliver their data simultaneously by flooding, a huge amount of data
transmission will occur. Besides, due to the fact that all the nodes try to access the common
transmission media at the same time, serious delays will occur as a result of collision prevention
mechanisms. Moreover, in consequence of routing loops and multiple routes, redundant energy
consumptions will result. Therefore, in terms of preventing redundant energy consumption during
data transmission, clustering approach provides very significant gains by means of simplifying
the communication and enhancing the scalability [11]. The objective is to find the optimum
method of organizing the nodes into clusters and electing the most appropriate node as the CH in
each cluster in order to achieve energy efficiency by realizing load balance among the nodes.
Many studies have been proposed about cluster-based WSNs. LEACH [12-13], is one of the first
and fundamental studies conducted on WSNs and has led to many subsequent studies about
clustering. The lifetime of the network is partitioned into rounds in LEACH. Cluster formation is
done in an autonomous and distributed manner by the nodes without centralized supervision.
Each round is divided into two phases: set-up and data transmission states. At set-up phase, each
node in the topology holds a random number and depending on this number is elected to be a
cluster head. Load is evenly distributed by rotating the charge of being CH among all nodes.
Thus, the drainage of the nodes in the battery is delayed. Another impressive solution proposed in
LEACH is the CHs making data aggregation in order to reduce the amount of data to be
transmitted.
Another study of clustering following LEACH is PEGASIS [14]. Although PEGASIS is
perceived as an improvement of LEACH, its basic principle is based on the chain structure rather
than a cluster scheme.
HEED [15], is another work which achieves considerable improvements on energy conservation
in WSNs. As in LEACH, CH selection is done periodically but not at each round. In contrast with
LEACH, CH selection is not done randomly, but is rather made according to a hybrid parameter
which is a combination of the residual energy levels of the nodes and a cost value called the
average minimum reachability power (AMRP). AMRP is the total energy consumed by all the
other nodes in the cluster if the aforementioned node becomes CH.
Clustered routing for selfish sensors (CROSS) [16] and its improved version localized game
theoretical clustering algorithm (LGCA) [17] is based on the game theory for cluster formation
and CH election. CROSS depends on global knowledge about the topology which is neither
4. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.6, No.1, February 2015
4
practical nor realistic. In contrast, LGCA employs localized information which is more suitable
for energy poor WSNs.
Zhu et al. have proposed an architecture [18] in which clustering is basically performed by
utilizing Hausdroff Distance [19]. The first criterion that is considered during CH selection phase
is the residual energy level of the nodes. Secondly, if the residual energy levels are equal, then the
proximity off the nodes is taken into account. Inter-cluster routing is performed by means of
utilizing classical Bellman-Ford’s shortest path approach [20].
In EECS (An Energy Efficient Clustering Scheme in Wireless Sensor Networks) [21], the
residual energy levels of the nodes are again considered. Another factor impacting the CH
selection is the distance between the CH candidates and the sink because inter-cluster
communication is performed directly between the CHs and the sink.
In order to prevent redundant message exchange suffered during CH election phase, Cui et al.,
proposes an efficient idea which is called passive clustering [22]. With passive clustering, each
CH candidate determines a random waiting time inversely proportional with the residual energy
levels of the nodes. That is, a node with low energy level waits a longer time to announce its
leadership. Therefore, the timers of the nodes with higher energy levels expire earlier and
announce their leadership before the others. Thus, other nodes hearing the announcement give up
the competition.
Inter-cluster communication is another challenge to be considered in cluster-based networks. Data
delivered at the end of the intra-communication phase must be conveyed to the sink by the CH.
This can be achieved either by single-hop or multi-hop communication. ANCAEE (A Novel
Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks) offers single-hop
transmission for intra-cluster communication and multi-hop transmission for inter-cluster
communication [23].
In addition to the studies mentioned above there have been several other studies on cluster-based
sensor networks [24-28]. The next section gives details about the methods and architectures
utilized in the system while analyzing the impacts of different structural variations on energy
consumption.
3. EXPERIMENTAL ARCHITECTURE AND DETAILS
This section outlines the methodology and some significant concepts utilized in our analysis. We
performed a large set of simulations with various combinations of node density, tier count, sink
settlement, radio coverage, and cluster sizing. Each simulation was run until the first node death
which defines the network lifetime. For performance measurement, we considered the network
lifetime, since the primary challenge to be accomplished for WSNs is prolonging the working life
of the network.
Instead of considering an event-based system, our simulations are based on the scenario that all
nodes in the topology periodically gather data and try to transmit that data to the sink(s). For
convenience, sensor nodes are assumed to be fixed and randomly distributed in a two-
dimensional plane. Since all nodes potentially participate during inter-cluster communication,
they do not apply any sleep-wake-up schedule.
Details about the main figures utilized during simulations are described in the following
subsections.
5. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.6, No.1, February 2015
5
3.1. Energy Consumption Model
In this paper, the classical energy model as described in LEACH is used. As is known, primary
factors affecting energy consumption are the number of bits transmitted and the distance between
the communicating pairs. If the distance between the communicating nodes is greater than the
threshold value, then the impact of the distance on the energy consumption grows exponentially
as shown in Eq. (1-3).
Esnd(l,d) = Esnd-elec(l) + Esnd-amp(l,d) (1)
Esnd(l,d)=
(l * Eelec) + (l * ℇfs * d2
) , d<do
(2)
(l * Eelec) + (l * ℇmp * d4
) , d≥do
Ercv = l * Eelec (3)
3.2. Network Lifetime
Several network lifetime definitions are proposed in the literature [29-34]. Some of them consider
the time in which a certain amount of the nodes die. Another idea to consider is the time after
which there is a region no longer covered by the network. The one that makes the most sense and
which we applied in this study is the time when the first node fails. When a node dies, it would
neither be accurate nor realistic to assume that the remaining network will work well. Eventually,
the node is dead and no data can be obtained from the area for which the dead node is
responsible. Besides, this can result in a network partition situation which means there are two
nodes which no longer can communicate with each other.
3.3. Cluster Head Election
Cluster Heads (CHs) have the responsibility of relaying the aggregated data of the corresponding
cluster to the sink. Therefore, this heavy mission should be shared among different nodes as much
as possible. Otherwise, the node assigned as CH drains its battery quickly. In this study, three
types of CH election methods are analysed:
CH Election Model 1: Every node in a cluster runs the same algorithm similar to the one
proposed in [22]. The result of the algorithm is a time value that determines the access time of a
node to the common media for announcing its leadership. Other nodes hearing this announcement
give up the election process and assign that node as the master node. Calculated waiting time
(Tw(i)) at each node is reversely proportional with the distance of the node to the centre of the
corresponding cluster and the residual energy level of that node:
Tw(i) = d(node(i), ClsCentre) / EngRes_node(i) (4)
where:
d(node(i), ClsCentre) is the Euclidean distance between node(i) and the centre point of the cluster
to which it belongs;
EngRes_node(i) is the residual energy of node(i).
According to Equation (4), nodes positioned around the cluster centre with higher residual energy
levels wait shorter durations and therefore have a higher probability of being elected as CH than
the others.
CH Election Model 2: This model uses a similar method to the one identified in model 1. This
time, an extra parameter is involved during CH election phase as presented in Eq. (5). Nodes
deployed between the centre of the corresponding cluster and the sink can be a CH. Furthermore,
6. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.6, No.1, February 2015
6
the distance between the node and the target sink is considered rather than the distance from the
node to the centre of the cluster (Eq. (6)).
isCHCnd = (5)
where:
isCHCnd is a value that determines the possibility of a node to be a CH;
node(i)ypos, and ClsCentreypos denote the (y) coordinates of node(i) and the centre point of the
cluster it belongs to respectively.
Obviously, according to Eq. (6), CHs are elected among the nodes that are positioned between the
centre point of the corresponding cluster and the target sink.
Tw(i) = (isCHCnd*d(node(i),TrgSink))/EngRes_node(i) (6)
where:
isCHCnd is a value that determines the possibility of a node to be a CH;
d(node(i), TrgSink) is the Euclidean distance between node(i) and the target sink;
EngRes_node(i) is the residual energy of node(i).
CH Election Model 3: In this method, every node in the cluster can be elected as a CH. There is
no constraint like the one defined in Model 2. Again, the target is the sink(s) and nodes closer to
the sink(s) with more residual energies have a greater chance to be elected as CH (Eq. (7)).
Tw(i)= d(node(i),TrgSink) / EngRes_node(i) (7)
3.4. Routing
Next-hop selection is performed depending on the geographical positions of the nodes. It is
assumed that all nodes are aware of their relative two dimensional coordinates in the topology.
Furthermore, they are assumed to be informed about the coordinates of their neighbours and the
sinks settled in the topology. A number of techniques have been proposed in the literature about
localization and positioning concepts. The first coming to mind is that equipping the sensor node
with a Global Positioning System (GPS) receiver. However, that is not a promising solution
because of deployment and cost limitations. There are other alternative solutions proposed such
as lateration and angulation techniques [35]. Since it is out of scope of this study, no specific
positioning method is studied in the paper.
3.5. Intra-Cluster Communication
Data gathered by each plain node in the cluster is delivered directly to the CH in a single-hop
manner if it is in the coverage area of the sender node. Otherwise, multi-hop transmission is
utilized. The packet emerging from the plain sensor node is forwarded to one of the neighbours
belonging to the same cluster which is closest to the CH. The next-hop selection method for intra-
cluster packet transmission is given below:
Algorithm 1 Intra-Cluster Next-Hop Selection Method
findNextIntraClsHop(){
if (isInCov(this, CH)) then
sendPckDirectlyToCH()
end if
else
distance ← ∞
for (i←1 to numOfNgbs ) do
if (d(this,CH) < dist(ngb(i),CH)) then
if (isInSameCls(this,ngb(i))) then
7. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.6, No.1, February 2015
7
if (dist(ngb(i),CH) < distance) then
distance = dist(ngb(i),CH)
nexthop = ngb[i]
end if
end if
end if
end for
sendIntraClsPckToNxtHop(nexthop)
end if
}
3.6. Inter-Cluster Communication
Data aggregated at each cluster is delivered by the CHs directly to the closest sink if the sink is in
the coverage area. Otherwise, the aggregated packet is forwarded to the node that is closest to the
target sink. If noticed, the next hop candidate of the inter-cluster packet is not required to be in
the same cluster. Next-hop calculation method for Inter-cluster communication is given below:
Algorithm 2 Inter-Cluster Next-Hop Selection Method
findNextInterClsHop(){
TrgSink ← calcTrgSink();
if (isInCov(this, TrgSink)) then
sendPckDirectlyToTrgSink(TrgSink)
end if
else
distance ← ∞
for (i←1 to numOfNgbs ) do
if (d(this,TrgSink) > dist(ngb(i),TrgSink)) then
if (dist(ngb(i),TrgSink) < distance) then
distance = dist(ngb(i), TrgSink)
nexthop = ngb[i]
end if
end if
end for
sendInterClsPckToNxtHop(nexthop)
end if
}
3.7. Packet Structures
Length of an Intra-cluster packet is 52 bytes that takes 1625µs to transmit with the utilized radio
data rate. As is known, WSNs are data-centric applications, not id-based like other traditional
networks. That is, data collection centre does not deal with the ID of the data source. It is only
concerned with the content. ID is only needed during forwarding operations inside the topology.
Thus, there is no need to apply conventional, redundant IP or MAC addresses during in-network
forwarding. It is sufficient to define short in-network unique addresses for forwarding purposes.
Since all nodes are assumed to be aware of their geographical positions of themselves and their
neighbours, and it is also assumed that two distinct nodes do not overlap, these relative two-
dimensional coordinates constitute the ID of the nodes. Intra-cluster packet structure is presented
in Figure 2.
Figure 2. Intra-Cluster packet structure
8. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.6, No.1, February 2015
8
CHs aggregate the data delivered by the plain nodes in its corresponding cluster and generate an
Inter-Cluster packet to be transmitted to the sink. Structure of an Inter-Cluster Packet is depicted
in Figure 3.
Figure 3. Inter-Cluster packet structure
As shown in Figure 3, the first 6 octets of the Inter-Cluster packet are fixed for every Inter-
Cluster packet. ClsID and CHID slots contain the IDs of the owner cluster and the corresponding
CH. In this way, when the aggregated packet arrives at the data collection centre, this information
identifies the region to which that packet belongs. For each round, a new sensor node is elected as
a CH. Therefore, the value of the second octet part changes in each round. Field TrgSinkID
denotes the ID of the target sink. Like the sensor nodes, relative two-dimensional coordinates of
the sinks constitutes their IDs. Topology is virtually divided into clusters uniformly and
permanently and each cluster defines its target sink at the beginning of its lifecycle, that is, the
closest one relative to the centre point of the cluster. Remaining parts of the Inter-cluster packet
comprises of the data delivered by each plane node in the cluster. Since the number of nodes
varies for each cluster, a general formula identifying the total length of an Inter-Cluster packet is
as follows:
LngthInterClsPck = 48 +(LngthIntraClsPck * NumOfNodes) (8)
3.8. Cluster Size
One of the most important challenges encountered in WSNs is the hot-spot problem. As stated
above, since sensor nodes are very tiny devices, their resources have limited capacities. The same
limitation is also valid for the communication coverage radius. Sensor nodes far from the sink
cannot transmit their data directly to the sink. Moreover, conveying the data directly which is
actually single-hop transmission is not preferred because the energy consumed during data
transmission is exponentially proportional by the distance. Therefore, multi-hop communication
is preferred in WSNs. Though multi-hop communication seems to be advantageous, another vital
challenge to be considered is called the hot-spot problem. Nodes closer to the sink act like a relay
and convey the data incoming from the remote nodes to the sink as shown in Figure 4. Hence, all
of the data traffic passes over a limited number of nodes that will cause these nodes to quickly
drain the battery, which is called the hot-spot problem.
Figure 4. Hot-spot problem
One of the promising proposals for solving the hot-spot problem is the unequal clustering method.
Researchers claim that forming the cluster located closer to the sink with smaller sizes and the
remote ones with larger sizes provides considerable gains in terms of energy conservation [36-
42].
In this part, we inspect the effect of cluster sizes on energy consumption for three types of
methods:
9. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.6, No.1, February 2015
9
- Clusters closer to the sink with smaller sizes and remote clusters with larger sizes
(ClsSizeModel1)
- Clusters closer to the sink with larger sizes and remote clusters with smaller sizes
(ClsSizeModel2)
- All clusters with equal size (ClsSizeModel3)
3.9. The Number and Location of the Sinks
Generally, researchers locate a single sink at one side or at the centre of the topology. However,
position and number of the sinks can affect the energy consumed in the topology. Therefore,
another important point examined in this paper is the variation in network lifetime depending on
the position and the number of the sink(s) in the network. Simulations were performed according
to three different sink(s) localization types.
- Sink(s) located at one side of the topology (SinkPositionModel1)
- Sink located at the centre of the topology (SinkPositionModel2)
- Sink(s) positioned around the topology (SinkPositionModel3)
4. EXPERIMENTAL RESULTS
In this section, we analyse the performance and the impact of five structural factors on energy
consumption: the number of tiers, the cluster sizes, the number and the location of the sinks, the
node density and the radio coverage. While analysing the effects of these factors, different types
of CH election methods are utilized and performances are compared. The simulations are
performed on a 500*500 squarely shaped area where the nodes are randomly deployed. Lifetime
is comprised of periodic rounds that each consists of CH election, data aggregation, intra-cluster
data transmission and inter-cluster data communication phases. Topology is virtually divided into
tiers and clusters.
In order to prevent common media access collisions, a MAC protocol similar to 802.11 with
RTS/CTS mechanism is used. As mentioned in the previous section, we employed the classical
energy calculation model that depends primarily on the distance. Parameters utilized during
simulations are given in Table1.
Table 1. Simulation parameters
Radio transmission data rate 250 Kbps
d0 (threshold distance) 85 m
R0 (coverage radius) 100 m
Eelec 50 nJ/bit
εfs 10 pJ/bit/m2
Emp 0.0013
pJ/bit/m4
As mentioned earlier, the impacts of cluster sizing, the number and the location of the sink(s), the
number of tiers and the node density on energy consumption are represented comprehensively.
Simulations are performed under three structural titles depending on how the clusters are sized.
As clarified previously, these are: clusters closer to the sink with smaller sizes and remote clusters
with larger sizes (ClsSizeModel1), clusters closer to the sink with larger sizes and remote clusters
with smaller sizes (ClsSizeModel2) and all clusters with equal sizes (ClsSizeModel3).
4.1. Clusters Close to the Sink with Smaller Sizes (ClsSizeModel1)
Another alternative solution proposed by the researchers is to slice the topology into tiers. As
shown in Figure 5, incrementing the number of tiers redundantly makes a negative impact on the
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lifetime of the network. With a topology of containing 500 nodes, the best performance is
provided by utilizing 2 tiers. SelectCH_Centre, SelectCH_EN_AfterCentre and
SelectCH_EN_withNoCons correspond to the CH election schemes CH Election Model 1, CH
Election Model 2 and CH Election Model 3 respectively.
Figure 5. Change in the network lifetime depending on the number of tiers
Another possible factor that may affect the network lifetime is the number of nodes in the
network that is node density. By holding the size of the topology area constant, increasing the
number of nodes increases the node density. However, more nodes means more data packets to be
transmitted. Thus, the load is observed to be shared by the time the density increases; however,
increase in the network traffic balances this factor. Figures 6-8 show the lifetime performance
depending on the node density for the networks that the sink(s) positioned one side, sink at the
centre and sink(s) surrounding the nodes respectively.
Figure 6. Change in the network lifetime depending on the node density for (SinkPositionModel1,
ClsSizeModel1) pair
Figure 7. Change in the network lifetime depending on the node density for (SinkPositionModel2,
ClsSizeModel1) pair
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Figure 8. Change in the network lifetime depending on the node density for (SinkPositionModel3,
ClsSizeModel1) pair
Figures 6-8 clarify that a topology model surrounded with the sinks provides the best
performance in terms of network lifetime.
Another possible factor that can affect the network performance is the number of sinks in the
system. We examined whether an increase in the number of sinks prolongs the lifetime of the
network.
Figure 9. Change in the network lifetime depending on the number of sinks for (SinkPositionModel1,
ClsSizeModel1) pair
Figure 10. Change in the network lifetime depending on the number of sinks for (SinkPositionModel3,
ClsSizeModel1) pair
Figures 9-10 reprove that with SinkPositionModel3, network lifetime is doubled by increasing the
number of sinks in the network. Since, the sensor nodes have limited coverage capacities and the
energy consumption is proportional with the communication distance, multi-hop communication
is preferred in WSNs. In our simulation model, CHs directly forward the aggregated data to the
sink(s) if they are in the communication range. However, this causes an extra burden. As
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mentioned in the previous section, energy consumption of the communication unit is
exponentially proportional with the distance between the receiver and the sender. This idea is
supported by Figures 11-13. Radio coverage improvement does not bring an extra advantage in
terms of energy conservation.
Figure 11. Change in the network lifetime depending on the radio coverage for (SinkPositionModel1,
ClsSizeModel1) pair
Figure 12. Change in the network lifetime depending on the radio coverage for (SinkPositionModel2,
ClsSizeModel1) pair
Figure 13. Change in the network lifetime depending on the radio coverage for (SinkPositionModel3,
ClsSizeModel1) pair
4.2. Clusters Close to the Sink with Larger Sizes (ClsSizeModel2)
Figures 14-21 present the changes occur in the network lifetime depending on the parameters
presented in the previous section. This time, clusters closer to the sink(s) have larger sizes and the
further ones with smaller sizes.
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Figure 14. Change in the network lifetime depending on the node density for (SinkPositionModel1,
ClsSizeModel2) pair
Figure 15. Change in the network lifetime depending on the node density for (SinkPositionModel2,
ClsSizeModel2) pair
Figure 16. Change in the network lifetime depending on the node density for (SinkPositionModel3,
ClsSizeModel2) pair
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Figure 17. Change in the network lifetime depending on the number of sinks for (SinkPositionModel1,
ClsSizeModel2) pair
Figure 18. Change in the network lifetime depending on the number of sinks for (SinkPositionModel3,
ClsSizeModel2) pair
Figure 19. Change in the network lifetime depending on the radio coverage for (SinkPositionModel1,
ClsSizeModel2) pair
Figure 20. Change in the network lifetime depending on the radio coverage for (SinkPositionModel2,
ClsSizeModel2) pair
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Figure 21. Change in the network lifetime depending on the radio coverage for (SinkPositionModel3,
ClsSizeModel2) pair
4.3. All Clusters with Equal Sizes (ClsSizeModel3)
Finally, Figures 22-29 present the changes that occur in the network lifetime depending on the
parameters presented in the previous section. This time, all the clusters in the network have equal
sizes.
Figure 22. Change in the network lifetime depending on the node density for (SinkPositionModel1,
ClsSizeModel3) pair
Figure 23. Change in the network lifetime depending on the node density for (SinkPositionModel2,
ClsSizeModel3) pair
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Figure 24. Change in the network lifetime depending on the node density for (SinkPositionModel3,
ClsSizeModel3) pair
Figure 25. Change in the network lifetime depending on the number of sinks for (SinkPositionModel1,
ClsSizeModel3) pair
Figure 26. Change in the network lifetime depending on the number of sinks for (SinkPositionModel3,
ClsSizeModel3) pair
Figure 27. Change in the network lifetime depending on the radio coverage for (SinkPositionModel1,
ClsSizeModel3) pair
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Figure 28. Change in the network lifetime depending on the radio coverage for (SinkPositionModel2,
ClsSizeModel3) pair
Figure 29. Change in the network lifetime depending on the radio coverage for (SinkPositionModel3,
ClsSizeModel3) pair
5. CONCLUSIONS
The primary energy-consuming unit of a sensor node is the communication unit. It is crucial that
while designing protocols, methods, and architectures for WSNs, this energy constraint problem
should be considered. Up to now, several research activities performed and various methods have
been proposed about cluster-based WSNs. This paper presents a brief analysis of the effects of the
various structural factors in terms of energy consumption in cluster-based WSNs. General belief
about cluster-based WSNs is that in order to alleviate the hot-spot problem, clusters located near
the sink should be smaller-sized than the remote ones. Other possible factors that may affect the
lifetime of the network are the number of tiers, the node density, the communication radio
coverage radius, the number and location of the sinks. All these parameters are examined for all
possible combinations in detail. Depending on our simulations, the best performance in terms of
the network lifetime is provided by positioning the sinks around the network. Increasing the node
density up to a level is another factor that affects the energy consumption positively. Also, it is
proved that sizing the clusters closer to the sink smaller than those further away enhances the
energy conservation. Furthermore, it is also clarified that larger radio coverage does not have a
definite positive effect in terms of energy conservation.
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AUTHORS
Taner Cevik received the B. S., M.S. and Ph.D. degrees in computer engineering from
Istanbul Technical University in 2001, Fatih University in 2008, and Istanbul
University in 2012 respectively. In 2006, he joined the Department of Computer
Engineering, Fatih University, as a research assistant, and in 2010 became an
instructor at the same university. Since 2013, he has served as an assistant professor at
Fatih University.
Fatih Ozyurt received the B.S. and M.S. degrees in computer engineering from Eastern
Mediterranean University Cyprus, and Fatih University Istanbul Institute of Science in
2011 and 2014, respectively. He continues his education as a PHD student in Software
Engineering at Firat University in Elazig.