Proposed Energy Efficient Algorithm for Clustering and Routing in WSN

Morsy, Nehad A.; Abdelhay, Ehab H.; Kishk, Sherif

doi:10.1007/s11277-018-5948-2

Cited by 45 publications

(22 citation statements)

References 9 publications

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“…Energy-efficient CH-based GSA (GSA-EC) [61] for finding an optimal set of CHs using GSA has been proposed. To balance the energy consumption, one-hop clusters are formed using an optimal set of CHs.…”

Section: Existing Routing Techniquesmentioning

confidence: 99%

Data Collection Protocols in Wireless Sensor Networks

Guravaiah¹,

Kavitha²,

Velusamy³

2021

Wireless Sensor Networks - Design, Deployment and Applications

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In recent years, wireless sensor networks have became the effective solutions for a wide range of IoT applications. The major task of this network is data collection, which is the process of sensing the environment, collecting relevant data, and sending them to the server or BS. In this chapter, classification of data collection protocols are presented with the help of different parameters such as network lifetime, energy, fault tolerance, and latency. To achieve these parameters, different techniques such as multi-hop, clustering, duty cycling, network coding, aggregation, sink mobility, directional antennas, and cross-layer solutions have been analyzed. The drawbacks of these techniques are discussed. Finally, the future work for routing protocols in wireless sensor networks is discussed.

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Section: Existing Routing Techniquesmentioning

confidence: 99%

Data Collection Protocols in Wireless Sensor Networks

Guravaiah¹,

Kavitha²,

Velusamy³

2021

Wireless Sensor Networks - Design, Deployment and Applications

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“…Reeta Bhardwaj and Dinesh kumar [13] [16] suggested that the CH selection process be organized as a single development goal aimed at achieving a positive CH formation, the collections return. , adjusting the use of firmness, stiffness and deceleration using gravitational search algorithm (GSA).…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Nodes Clustering and Routing Using Multi-Objective Spider Monkey Optimization Algorithm in Wireless Sensor Network

Duraimurugan¹,

Avudaiammal²

2021

Preprint

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In wireless sensor network (WSN), the gateways which are placed far away from the base station (BS) forward the collected data to the BS through the gateways which are nearer to the BS. This leads to more energy consumption because the gateways nearer to the BS manages heavy traffic load. So, to overcome this issue, loads around the gateways are to be balanced by presenting energy efficient clustering approach. Besides, to enhance the lifetime of the network, optimal routing path is to be established between the source node and BS. For energy efficient load balancing and routing, multi objective based spider monkey optimization (SMO) algorithm is presented in this paper. Using this algorithm, optimal clustering and routing are performed depend on the objective functions routing fitness and clustering fitness. Simulation results show that the performance of the proposed SMO based clustering and routing scheme attains better results than that of the existing algorithms in terms of energy consumption, delivery ratio, throughput and network lifetime.

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“…In WSN optimization algorithms were presented to address the challenge of energy efficiency in the deployed network by enabled efficient data gathering. The scalability offered optimal CH selection by using improved Gravitational Search Algorithm (GSA) integrated with the PSO algorithm that performs hierarchical clustering and also it computes new cost function (Morsy et al, 2018). Here one-hop clusters were created and optimal CHS were elected.…”

Section: Related Workmentioning

confidence: 99%

Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling

Sinde

Begum

Njau³

et al. 2020

Cogent Engineering

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Network lifetime remains as a significant requirement in Wireless Sensor Network (WSN) exploited to prolong network processing. Deployment of low power sensor nodes in WSN is essential to utilize the energy efficiently. Clustering and sleep scheduling are the two major processes involved in improving network lifetime. However, abrupt and energy unaware selection of cluster head (CH) is nonoptimal in WSN which reflects in the drop of energy among sensor nodes. This paper addresses the twofold as utilization of sensor nodes to prolong the node's energy and network lifetime by LEACH-based cluster formation and Time Division Multiple Access scheduling (TDMA). Clusters are constructed by the design of an Enhanced-Low-Energy adaptive Clustering Hierarchy protocol (E-LEACH) that uses parallel operating optimization (Grey Wolf Optimization (GWO) and Discrete Particle Swarm Optimization (D-PSO)) for selecting an optimal CH and helper CH. The fitness values estimation from GWO and D-PSO is concatenated to prefer the best optimal CH. E-LEACH also manages the cluster size which is one of the conventional disadvantages in LEACH. CHs are responsible to perform energy-aware TDMA scheduling which segregates the coverage area into 24 sectors. Alternate sectors are assigned Ramadhani Sinde ABOUT THE AUTHOR Ramadhani Sinde works as an assistant lecturer in the School of Computational and Communication Sciences and Engineering at Nelson Mandela African Institution of Science and Technology (NM-AIST). Currently, he under Doctoral Environmental Management Information System project undertaking PhD studies in the field of Information and Communication of Science and Engineering. His research interests include Internet of Things (IoT) network, embedded systems, mobile computing, modelling and performance evaluation of wireless sensor networks, wireless and mobile communication. Mr. Sinde has co-authored more than 10 papers in internationally refereed journals and conferences. He is a Queen Elizabeth Scholarship -Advanced Scholars Program alumni.

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Proposed Energy Efficient Algorithm for Clustering and Routing in WSN

Cited by 45 publications

References 9 publications

Data Collection Protocols in Wireless Sensor Networks

Data Collection Protocols in Wireless Sensor Networks

Energy Efficient Nodes Clustering and Routing Using Multi-Objective Spider Monkey Optimization Algorithm in Wireless Sensor Network

Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling

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