PEAL: Power Efficient and Adaptive Latency Hierarchical Routing Protocol for Cluster-Based WSN

Hidoussi, Faouzi; Toral-Cruz, Homero; Boubiche, Djallel Eddine; Martínez-Peláez, Rafael; Velarde-Alvarado, Pablo; Barbosa, Romeli; Chan, F.

doi:10.1007/s11277-017-4963-z

Cited by 23 publications

(12 citation statements)

References 14 publications

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“…FaouziHidowssi et al (2017) [13] proposed PEAL (Power Efficient and Adaptive Latency) wireless networks, to extend network life time and achieved 47% more life time than the LEACH (Low Energy Adaptive Clustering Hierarchy) model but with more delay. Kaushik et al proposed a distance-based energy efficient and load balancing method for addressing the problems associated with compactly populated network such as interference, many transmission routes, to reduce the burden of distant nodes involved in communication for saving energy [22].…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Objective Spider Monkey Optimization for Energy Efficient clustering and Routing in wireless sensor networks

Samiayya

Ramalingam

2021

Preprint

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In wireless sensor network (WSN), the gateways far away from the base station (BS) uses the gateways nearer to the BS to forward the data. It causes heavy traffic to the gateways in proximity with the BS. They need to manage this heavy traffic load but it leads to additional energy consumption and reduction in network lifetime. In order to overcome these issues, loads around the gateways need to be balanced. In this paper, multi objective based spider monkey optimization (MOSMO) has been presented to balance the load and to improve the network lifetime through energy efficient routing and clustering. The objective functions such as routing fitness and clustering fitness have been considered for optimal routing and clustering. The routing fitness function is found by incorporating both the minimum distance traversed by the gateways and minimum number of the gateway hops. The clustering fitness function is the minimum fitness function of gateways. The fitness function of each gateway is computed based on both the mean load of gateways as well as the distance between gateways and BS. The performance of the proposed MOSMO based routing and clustering scheme is compared with the existing Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) based routing and clustering scheme. The QoS features such as delay, energy consumption, delivery ratio, throughput and network lifetime with various node density are analyzed. The proposed work is simulated using MATLAB. The results show that, the reduction in delay and energy consumption is about 18% and 17% respectively whereas improvement in delivery ratio, throughput and network life time is about 15%, 24% and 19% respectively when compared to the existing PSO and GWO methods.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-Objective Spider Monkey Optimization for Energy Efficient clustering and Routing in wireless sensor networks

Samiayya

Ramalingam

2021

Preprint

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“…For UWSNs [26]- [29], different clustering schemes have been presented. However, none of them considers the hotspot issue.…”

Section: Our Proposed Scheme a Motivationmentioning

confidence: 99%

A Multi-Layer Cluster Based Energy Efficient Routing Scheme for UWSNs

et al. 2019

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Underwater Wireless Sensor Networks (UWSNs) have emerged as a remarkable interest for scholars worldwide in terms of various applications such as monitoring offshore oil and gas reservoirs, pollution, oceans for defense, and other applications such as tsunami. Terrestrial Wireless Sensor Networks (TWSN) and UWSNs share many characteristics apart from having different communication medium and working environment as UWSNs face the challenges of low-bandwidth, long latency, and high bit error rate. These have caused for UWSNs many problems such as low reliability, packet retransmission, and high consumption of energy. To alleviate the aforementioned issues, many techniques have been proposed. However, most of them merely consider the issue of hotspot which occurs due to the unbalanced transmission of load on sensor nodes near the surface sink. In this article, we propose a multi-layer cluster-based Energy Efficient (MLCEE) protocol for UWSNs to address the issue of hotspot and energy consumption. There are different stages in MLCEE, first of which is the division of the whole network in layers, the second is clustering of the nodes at same layers. In the last stage of transmission, the cluster head (CH) selects the next hop among the CHs based on greater fitness value, small Hopid and small layer number. To mitigate the issue of hotspot, the first layer remains un-clustered and any node in the first layer transfers data to the sink directly while cluster heads (CHs) are selected based on Bayesian Probability and residual energy. The simulation results of the proposed technique, done using MATLAB, have revealed that MLCEE achieves superior performance than the other techniques with regard to the network lifetime, energy consumption, and data transmission amount.INDEX TERMS Underwater wireless sensor networks (UWSNs), BN Bayesian probability (BN), network lifetime, dynamic clustering, cluster head (CH) selection, energy efficiency. I. INTRODUCTIONRecently, UWSNs are fascinating more considerations from industry and academia due to their comprehensive application fields, for example, auxiliary navigation, ecological observing, resource exploration, and calamities avoidance, etc. Underwater nodes are mostly deployed sparsely in the monitoring area from surface to bottom and these nodes are equipped with an acoustic modem. Communications through optical signals in underwater are not adequate dueThe associate editor coordinating the review of this manuscript and approving it for publication was Fatos Xhafa.

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“…Hence, energy efficient and energy balance are primary design objectives in a routing protocol. Cluster-based routing protocols have been proposed in the terrestrial wireless sensor networks [30][31][32][33]. After clustering, member sensor nodes collect and send data to the cluster head, cluster head sends the data to the sink node after data fusion.…”

Section: Design Of Proposed Protocol (Eerblc)mentioning

confidence: 99%

An Energy Efficient Routing Protocol Based on Layers and Unequal Clusters in Underwater Wireless Sensor Networks

Fang

Wei

2018

Journal of Sensors

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Underwater Wireless Sensor Networks (UWSNs) have drawn tremendous attentions from all fields because of their wide application. Underwater wireless sensor networks are similar to terrestrial Wireless Sensor Networks (WSNs), however, due to different working environment and communication medium, UWSNs have many unique characteristics such as high bit error rate, long end-to-end delay and low bandwidth. These characteristics of UWSNs lead to many problems such as retransmission, high energy consumption and low reliability. To solve these problems, many routing protocols for UWSNs are proposed. In this paper, a localization-free routing protocol, named energy efficient routing protocol based on layers and unequal clusters (EERBLC) is proposed. EERBLC protocol consists of three phases: layer and unequal cluster formation, transmission routing, maintenance and update of clusters. In the first phase, the monitoring area under the water is divided into layers, the nodes in the same layer are clustered. For balancing energy of the whole network and avoiding the “hotspot” problem, a novel unequal clustering method based on layers for UWSNs is proposed, in which a new calculation method of unequal cluster size is presented. Meanwhile, a new cluster head selection mechanism based on energy balance and degree is given. In the transmission phase, EERBLC protocol proposes a novel next forwarder selection method based on the forwarding ratio and the residual energy. In the third phase, Intra and inter cluster updating method is presented. The simulation results show that the EERBLC can effectively balance the energy consumption, prolong the network lifetime, and increase the amount of data transmission compared with DBR and EEDBR protocols.

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PEAL: Power Efficient and Adaptive Latency Hierarchical Routing Protocol for Cluster-Based WSN

Cited by 23 publications

References 14 publications

Multi-Objective Spider Monkey Optimization for Energy Efficient clustering and Routing in wireless sensor networks

Multi-Objective Spider Monkey Optimization for Energy Efficient clustering and Routing in wireless sensor networks

A Multi-Layer Cluster Based Energy Efficient Routing Scheme for UWSNs

An Energy Efficient Routing Protocol Based on Layers and Unequal Clusters in Underwater Wireless Sensor Networks

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