Range-Based Sleep Scheduling (RBSS) for Wireless Sensor Networks

Yen, Li-Hsing; Cheng, Yang-Min

doi:10.1007/s11277-008-9530-1

Cited by 21 publications

(12 citation statements)

References 9 publications

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“…The algorithm decreased the inferior solutions and narrowed the searching range of the algorithm. In 2014, Mini et al [6] have found that the sensor deployment is done based on the area coverage [14][15][16][17][18], which yields less network lifetime. So they focused on target coverage and optimized the sensor node deployment and scheduling to achieve the maximum target coverage and increasing the network life time.…”

Section: Literature Reviewmentioning

confidence: 99%

Minimizing sensor movement in target coverage problem: A hybrid approach using Voronoi partition and swarm intelligence

Jagtap

Gomathi²

2017

Bulletin of the Polish Academy of Sciences Technical Sciences

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Abstract. This paper addresses the major challenges that reside on target coverage problem, which is one among the two primary sub-problems of node deployment problem. In order to accomplish a cost-efficient target coverage, a Voronoi partition-based, velocity added artificial bee colony algorithm (V-VABC) is introduced. The V-VABC is an advancement over the traditional, target-based Voronoi greedy algorithm (TVgreedy). Moreover, the VABC component of V-VABC is a hybrid, heuristic search algorithm developed from the context of ABC and particle swarm optimization (PSO). The V-VABC is an attempt to solve the network, which has an equal number of both sensors and targets, which is a special case of TCOV. Simulation results show that V-VABC performs better than TV-greedy and the classical and base algorithms of V-VABC such as ABC and PSO.Key words: sensor, target, Voronoi, heuristic, ABC, PSO, VABC. Minimizing sensor movement in target coverage problem:A hybrid approach using Voronoi partition and swarm intelligence A.M. JAGTAP * and N. GOMATHI VEL-TECH Dr. RR & Dr. SR Technical University, Chennai 600 062, India to be complex in large networks. Based on immune algorithm, a new centralized algorithm is used to maximize the coverage area with less energy utilization. So, the centralized algorithm has an advantage over the very low processing power of the sensor nodes [10].Sensor deployment is the basic problem in WSNs. It is divided into two kinds of methods: based on continued points and based on grid [11]. The system cost must be low and the connected system must cover the sensing field within WSNs. So, the minimum-cost and connectivity-guaranteed grid coverage (MCGC) occurs as an optimization problem [12]. This paper addresses the challenges in the first problem of the node deployment problem, termed target coverage (TCOV) problem [5]. In order to overcome the problem, a meta-heuristic search-based node deployment algorithm is proposed. The algorithm moves the sensors to cover the target at minimum movement distance, based on Voronoi diagram and heuristic search. The heuristic search is performed by adopting a hybrid version of artificial bee colony (ABC) and particle swarm optimization (PSO). Hence, the key contributions of this paper can be presented as follows.We addressed the scenario of searching for servers (nodes) in the higher-order neighbour targets and the failure of the existing algorithm to handle it.1. We propose a Voronoi partition-based velocity added ABC, abbreviated as V-VABC. 2. We hybridize the ABC with PSO to introduce velocity added ABC (VABC). 3. We have simulated the scenario of higher order neighborhood searching for servers (nodes) and the superiority of V-VABC over TV-greedy algorithm. The rest of the paper is organized as follows. Section 2 reviews the related works and Section 3 gives the preliminaries of the system model and the objective of the TCOV solution. Section 4 explains the TV-greedy algorithm and the proposed V-VABC algorithm, and Section 5 details the hybrid version of

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Section: Literature Reviewmentioning

confidence: 99%

Minimizing sensor movement in target coverage problem: A hybrid approach using Voronoi partition and swarm intelligence

Jagtap

Gomathi²

2017

Bulletin of the Polish Academy of Sciences Technical Sciences

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“…The simulation shows improved performance of DCS over full area coverage schemes. In order to prevent coverage drop and enhance the network lifetime, the authors in [11] have presented a Distributed Sleep Scheduling Algorithm with Range Adjustment (DSRA). This sleep scheduling algorithm depends upon the residual energy of the sensor node and the size of the overlap area between the sensor and its neighboring nodes.…”

Section: Related Workmentioning

confidence: 99%

Energy preserving sleep scheduling for cluster-based wireless sensor networks

Singh

Lobiyal

2013

2013 Sixth International Conference on Contemporary Computing (IC3)

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In sensor network, sleeping technique can be used to conserve energy for maximizing the network lifetime. The sensor nodes are often densely deployed in the sensing field, which increases redundant packet transmissions thereby draining huge amount of sensor energy. However, energy wastage can be preserved by putting some nodes to sleep state, while other nodes remain active in the network. Therefore, a novel way have been determined that allows selected sensor nodes to enter sleep state without degrading sensor coverage of the network. In the proposed Energy Preserving Sleep Scheduling (EPSS) strategy, the sleeping probability of a node varies according to the density of the deployed region. Moreover, the distance of the member nodes from the head node is also taken into account in the sleep policy, thereby balancing energy consumption within a cluster. The simulation result of our proposed sleep scheduling scheme shows significant enhancements over Linear Distance-based Scheduling and Randomized Scheduling schemes respectively.

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“…A range-based sleep scheduling (RBSS) protocol [22] is a deterministic communication sleep program. RBSS divides running time into fixed-length time periods called rounds.…”

Section: Distributed Sleep/wake Schedulingmentioning

confidence: 99%

Comprehensive Review of Sleep/Wake Scheduling in Wireless Sensor Networks

Shi

Nan

Kou

et al. 2011

Communications in Computer and Information Science

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Abstract. Sleep/wake scheduling is an essential consideration in sensor network applications. Finding an optimal sleep/wake scheduling strategy that would minimize computation and communication overhead, be resilient to node failures, and provide high-quality data service is extremely challenging. In this paper, we present and compare several state-of-the-art algorithms and techniques that aim to address the sleep/wake scheduling issue, which are divided into distributed and centralized manners. Meanwhile, the advantages and disadvantages of these scheduling models and algorithms are discussed, together with open research issues.

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Range-Based Sleep Scheduling (RBSS) for Wireless Sensor Networks

Cited by 21 publications

References 9 publications

Minimizing sensor movement in target coverage problem: A hybrid approach using Voronoi partition and swarm intelligence

Minimizing sensor movement in target coverage problem: A hybrid approach using Voronoi partition and swarm intelligence

Energy preserving sleep scheduling for cluster-based wireless sensor networks

Comprehensive Review of Sleep/Wake Scheduling in Wireless Sensor Networks

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