ECTTM - Energy Conserving Trustworthy Topology Management Mechanism for Wireless Sensor Networks

Senthi, Theagarajan; Kannapiran, B.

doi:10.22266/ijies2017.0831.17

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…The main drawback of this protocol is every node has to calculate its Trust and distrust values before transmission to other node, due to this Computation and communication cost may increases. Theagarajan Senthil, Balasubramanian Kannapiran [18] proposes an energy efficient, cluster based and trustworthy Energy Conserving Trustworthy Topology Management (ECTTM) algorithm. The area of the network is divided into number of griids of equal in size, and the sensor nodes are randomly deployed in entire grids.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficient Clustering Protocol Using Fuzzy K-means and Midpoint Algorithm for Lifetime Improvement in WSNs

Srikanth¹,

Prasad²

2018

IJIES

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Due to shortage of power source, energy is the significant concern part in Wireless Sensor Systems. Wireless Sensor Networks (WSNs) are currently used in numerous kinds of WSN simulators have been established to visually illustrate the coverage, energy consumption status and expected lifetime of WSN sensors. Most of the Researchers have proposed and develop routing algorithm to increase the network lifetime. Among them clustering is the best technique and it is well known for accomplishing energy effectiveness in WSNs. In this paper, Energy Efficient Multi-hop Routing Clustering Protocol (EEMRCP) based on Fuzzy K-Means and Centralized Mid-point Algorithm (FKM-CMA) is proposed for network lifetime improvement. An existing and frequently used algorithm is K-means algorithm in WSN. The main limitation of this K-means algorithm is random initial centroid selection. To improve K-means algorithm, a Midpoint method in initial centroid selection is used. This is named as FKM-CMA. There are two main considerations for cluster head selection in proposed work, one is it's residual energy, and another one is Euclidean distance used in basic Fuzzy K-means algorithm. Finally, Multi-hop communication is performed for transmitting the packets from CHs to Base Station depending on the distance between them. Furthermore, stimulated outcomes showed that the total network performance of the proposed approach is improved than the other existing approaches.

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Section: Literature Reviewmentioning

confidence: 99%

Efficient Clustering Protocol Using Fuzzy K-means and Midpoint Algorithm for Lifetime Improvement in WSNs

Srikanth¹,

Prasad²

2018

IJIES

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“…Thus, Computational Intelligence (CI) [12] based approaches such as Artificial Immune System (AIS), Evolutionary Algorithms (EAs), Reinforcement Learning (RL) and added newly, Artificial Bee Colony (ABC) has been widely used as the population based metaheuristic for EECP in WSNs [13]. The protocol which associates energy efficient routing for specific applications with data aggregation and attains improved WSN lifetime is nothing but Low Energy Adaptive Clustering Hierarchy (LEACH) and a flexible AODV-based (Ad hoc On-Demand Distance Vector) routing protocol [14,15]. LEACH acquaint with an algorithm for rotating CHs positions and adapts clusters to regularly allocate the energy load amid all SNs and thus allows WSNs self-organization.…”

Section: Related Workmentioning

confidence: 99%

Efficient Energy Clustering Protocol UsingGenetic Algorithm in Wireless Sensor Networks

Srikanth¹,

Prasad²

2018

JESTR

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Nowadays, Wireless Sensor Networks (WSNs) are pondered as an exploration subject. Currently, progress in electronic communications has directed to multipurpose Sensor Nodes (SNs) with less price and power consumption. Energy efficiency is a major concern in WSNs as the sensor nodes are battery-operated devices. Clustering based techniques are implemented through data aggregation to make equal energy consumption among SNs for energy efficient data transmission. The existing clustering techniques make use of distinct Harmony Search Algorithm (HSA), Low-Energy Adaptive Clustering Hierarchy (LEACH) and Particle Swarm Optimization (PSO) algorithms. However, these algorithms have exploration exploitation trade-off and local search constraint individually. In order to obtain a global search with faster convergence, Efficient Energy Clustering Protocol (EECP) based on Genetic Algorithm (GA) is recently proposed to detect their immediate neighbors, balance energy consumption load among data transmission routes and energy efficient cluster head selection. The proposed algorithm exhibited high search efficiency and dynamic capability that improves lifetime of SNs. The presentation of the proposed algorithm was assessed using throughput, packet delivery ratio, energy consumption and end to end delay. The proposed algorithm showed an improvement in energy consumption and throughput by 95 and 90 Mbps respectively than existing clustering algorithm.

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ECTTM - Energy Conserving Trustworthy Topology Management Mechanism for Wireless Sensor Networks

Cited by 2 publications

References 12 publications

Efficient Clustering Protocol Using Fuzzy K-means and Midpoint Algorithm for Lifetime Improvement in WSNs

Efficient Clustering Protocol Using Fuzzy K-means and Midpoint Algorithm for Lifetime Improvement in WSNs

Efficient Energy Clustering Protocol UsingGenetic Algorithm in Wireless Sensor Networks

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