H-IECBR: HBO based-Improved Energy Efficient Chain Based Routing protocol in WSN

Gupta, Aman; Thakur, Abhishek; Saini, Hardeep Singh; Kumar, Rajesh; Kumar, Naveen

doi:10.1109/icpeices.2016.7853587

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…In the literature, intensive research has been carried out on energy efficient routing protocols [18][19][20][21][22][23] and node placement [24][25][26][27] to reduce energy consumption for WSN. Early work often models the optimization problem with a single objective.…”

Section: Related Work For the Multi-objective Coverage Optimization Problemmentioning

confidence: 99%

Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization

Ding

et al. 2018

Applied Soft Computing

103

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In Wireless Sensor Networks (WSN), maintaining a high coverage and extending the network lifetime are two conflicting crucial issues considered by real world service providers. In this paper, we consider the coverage optimization problem in WSN with three objectives to strike the balance between network lifetime and coverage. These include minimizing the energy consumption, maximizing the coverage rate and maximizing the equilibrium of energy consumption. Two improved hybrid multi-objective evolutionary algorithms, namely Hybrid-MOEA/D-I and Hybrid-MOEA/D-II, have been proposed. Based on the well-known MOEA/D algorithm, Hybrid-MOEA/D -I hybrids a genetic algorithm and a differential evolutionary algorithm to effectively optimize sub-problems of the multi-objective optimization problem in WSN. By integrating a discrete particle swarm algorithm, we further enhance solutions generated by Hybrid-MOEA/D-I in a new Hybrid-MOEA/D-II algorithm. Simulation results show that the proposed Hybrid-MOEA/D-I and Hybrid-MOEA/D-II algorithms have a significantly better performance compared with existing algorithms in the literature in terms of all the objectives concerned.

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Section: Related Work For the Multi-objective Coverage Optimization Problemmentioning

confidence: 99%

Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization

Ding

et al. 2018

Applied Soft Computing

103

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“…Mondal et. al (2016) utilizam fuzzy logic para eleição do cluster head, Gupta et. al (2016) utilizam a técnica Honey Bee Optimization para selecionar o próximo nó na transmissão dos dados e Bhatti e Kaur (2017) propõem um algoritmo de roteamento com sink móvel baseado em grid virtual.…”

Section: Trabalhos Relacionadosunclassified

Uma avaliação da eficiência energética de uma Rede de Sensores Sem Fios em relação ao posicionamento do nó sink

Alcantud¹,

Silva²,

Jubileu³

et al. 2017

Anais Do IV Encontro Nacional De Computação Dos Institutos Federais (EnCompIF 2017)

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A pesquisa em relação ao uso de tecnologias de conexão sem fio em diversas áreas propulsionou esse estudo referente à eficiência energética de Redes de Sensores sem Fio (RSSF), considerando a variação de quantidade de nós sensores, o tempo de coleta de dados desses nós e o posicionamento do nó sink. Para a realização desse estudo foi utilizado o simulador Castalia como instrumento de análise do comportamento de uma RSSF em um ambiente real, reduzindo custo e tempo.

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“…In this paper [8], it optimized the routing path in IECBR (Improved Energy Efficient Chain Based Routing) protocol which is one of the most recent techniques depend on PEGASIS (power Efficient Gathering in Sensor Information System). It used Honey Bee Optimization (HBO) method to select the next node which is to be added for the chain construction for the data transmission from the network to the base station.…”

Section: Literature Reviewmentioning

confidence: 99%

Survey on Recent Reliable Routing protocols in WSN

Meshram¹,

Mehetre²

2017

International Journal of Advanced Research in Computer and Comm

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In wireless sensor network (WSN) technology has offered the accessibility of small as well as low-cost sensor nodes with capability of sensing different types of physical and environmental conditions, data processing, and wireless communication. Various types of sensing capabilities results in large amount of application domain. Moreover, the characteristics of wireless sensor networks need more effective techniques for data forwarding along with processing. In WSN, the sensor nodes have a limited transmission range, and their processing and storage capabilities as well as their energy resources are also limited. For managing the routes in the network and to ensure reliable multihop interaction under these conditions routing protocols in wireless sensor networks are responsible. This paper, studies the different types of recent routing protocols in Wireless Sensor Network and compare their strengths and limitations.

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H-IECBR: HBO based-Improved Energy Efficient Chain Based Routing protocol in WSN

Cited by 6 publications

References 11 publications

Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization

Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization

Uma avaliação da eficiência energética de uma Rede de Sensores Sem Fios em relação ao posicionamento do nó sink

Survey on Recent Reliable Routing protocols in WSN

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