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A Bipopulation-Based Evolutionary Algorithm for Solving Full area coverage problems

IEEE SENSORS JOURNAL 2013年第12期13卷 4796-4807页

作者： Seok, Joon-Hong Lee, Joon-Yong Kim, Won Lee, Ju-Jang Korea Adv Inst Sci & Technol Dept Elect Engn Taejon 305701 South Korea Iowa State Univ Dept Genet Dev & Cell Biol Ames IA 50010 USA Woosong Univ Dept Comp Sci Taejon 110810 South Korea

The full area coverage sensor deployment problem is a challenging issue in wireless sensor networks. We focus on sensor deployment strategies that aim to acquire a full-coverage state with a minimum number of sensors in a predetermined target region that includes non-penetrable obstacles. This paper presents an efficient bipopulation-based evolutionary full area coverage (BEFAC) algorithm that involves a bipopulation structure composed of a full-and partial-coverage populations. Fitness functions, stochastic unary recombination operators, and selection procedures between the two populations are well designed. Through applying the proposed BEFAC, a full-coverage state is acquired with a minimum number of deployed sensors in the target region, which has non-penetrable obstacles, and the algorithm avoids getting caught in local minima. The performance results reveal that BEFAC outperforms the conventional deployment methods in terms of the number of deployed sensors and the number of required fitness evaluations.

关键词： area coverage problem evolutionary sensor deployment full coverage problem

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DISTRIBUTED ENERGY-EFFICIENT ALGORITHMS FOR coverage problem IN ADJUSTABLE SENSING RANGES WIRELESS SENSOR NETWORKS

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DISCRETE MATHEMATICS ALGORITHMS AND APPLICATIONS 2009年第3期1卷 299-317页

作者： Vu, Chinh Cai, Zhipeng Li, Yingshu Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA Univ Alberta Dept Comp Sci Edmonton AB T6G 2E8 Canada

Due to wide range of applications of Wireless Sensor Network (WSN), lots of effort has been dedicated to solve its various issues. Among those issues, coverage is one of the most fundamental ones of which a WSN has to watch over the environment such as a forest (area coverage) or set of subjects such as collection of precious renaissance paintings (target of point coverage) and collect environment parameters and maybe, further monitor the environment. With variable sensing range, the difficulties to cover a continuous space (where number of points is infinity) in the area coverage problem becomes somewhat harder than covering limited number of discrete points in the target coverage problem. Very few papers have paid effort for the former problem. In this paper, we consider the area coverage problem for WSN where sensors can arbitrarily change their sensing ranges under some upper bound. We first improve the work in [1] so that the boundary effect is ruled out and the monitored area can be completely covered at all cases. Next, we extend that improved algorithm by introducing two distributed scheduling algorithms which are trade-off in term of network lifetime and algorithms efficiency. The major objective of each of our 3 proposed algorithms in this paper is to balance energy consumption and to maximize network lifetime. Our proposed algorithm efficiency is shown by algorithms complexity analysis and extensive simulation. In compared with the work in [1], our proposed algorithms are not only better in providing coverage quality, they could also greatly lengthen network lifetime and greatly reduce the unnecessary coverage redundancy.

关键词： Wireless sensor network area coverage problem adjustable sensing range distributed algorithms balancing energy-efficient Delaunay-triangulation

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An efficient genetic algorithm for maximizing area coverage in wireless sensor networks

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INFORMATION SCIENCES 2019年 488卷 58-75页

作者： Nguyen Thi Hanh Huynh Thi Thanh Binh Nguyen Xuan Hoai Palaniswami, Marimuthu Swami Hanoi Univ Sci & Technol Hanoi Vietnam Phuong Dong Univ Hanoi Vietnam AI Acad Hanoi Vietnam Univ Melbourne Melbourne Vic Australia

Wireless sensor networks collect and transfer environmental data from a predefined region to a base station to be processed and analyzed. A major problem when designing these networks is deploying sensors such that their area coverage is maximized. Given a number of sensors with heterogeneous sensing ranges, the problem of coverage maximization is known to be NP-hard. As such, prevailing methods often rely on metaheuristic techniques while employing approximated fitness functions, resulting in modest solution quality and stability. This paper proposes a novel and efficient metaheuristic in the form of a genetic algorithm, which overcomes several weaknesses of existing metaheuristics, along with an exact method for calculating the fitness function for this problem. The proposed genetic algorithm includes a heuristic population initialization procedure, the proposed exact integral area calculation for the fitness function, and a combination of Laplace Crossover and Arithmetic Crossover Method operators. Experiments have been conducted to compare the proposed algorithm with five state-of-the-art methods on a wide range of problem instances. The results show that our algorithm delivers the best performance in terms of solution quality and stability on a majority of the tested instances. (C) 2019 Elsevier Inc. All rights reserved.

关键词： area coverage problem Genetic algorithm Integral calculation Wireless sensor networks Monte Carlo

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Distributed coverage control for concave areas by a heterogeneous Robot-Swarm with visibility sensing constraints

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AUTOMATICA 2015年 53卷 195-207页

作者： Kantaros, Yiannis Thanou, Michalis Tzes, Anthony Duke Univ Dept Mech Engn & Mat Sci Durham NC 27708 USA Univ Patras Dept Elect & Comp Engn Rion 26500 Achaia Greece

This article addresses the coverage problem of non,convex environments by a mobile multi-robot system characterized by omnidirectional 'field of view' sensing capabilities. The mobile robotic network is heterogeneous in terms of robots' sensing ranges. Moreover, each robot is capable of communicating with all robots located within a predefined distance from its position. A distributed gradient-based coordination scheme is proposed, based on a novel partitioning of the environment, leading the network to a local optimum of an area-wise criterion. Simulation studies are carried out verifying the efficiency of the proposed distributed control law. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： area coverage problem Non-convex environment Mobile robotic networks Visibility-based power diagram

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A Partition-Based Node Deployment Strategy in Solar Insecticidal Lamps Internet of Things

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IEEE INTERNET OF THINGS JOURNAL 2020年第11期7卷 11223-11237页

作者： Yang, Fan Shu, Lei Huang, Kai Li, Kailiang Han, Guangjie Liu, Ye Nanjing Agr Univ Coll Engn Nanjing 210031 Peoples R China Jiangsu Normal Univ Sch Math & Stat Xuzhou 221116 Jiangsu Peoples R China Nanjing Agr Univ NAU Lincoln Joint Res Ctr Intelligent Engn Nanjing 210031 Peoples R China Univ Lincoln Coll Sci Sch Engn Lincoln LN6 7TS England Dalian Univ Technol Sch Software Key Lab Ubiquitous Network & Serv Software Liaoni Dalian 116024 Peoples R China

Solar insecticidal lamp (SIL) is a green prevention and control technology for pests. With the development of wireless sensor networks (WSNs), the combination of SILs and WSNs forms a novel agricultural Internet of Things-SIL Internet of Things (SIL-IoTs). However, the complex geographical characteristic of actual farmland has a great impact on SIL deployment. In this article, we study the SIL deployment problem (SILDP) with characteristics of full coverage, penetrable obstacles, irregular boundary, and partition structure. According to the partition structure caused by natural physiognomy feature, the actual farmland is divided into many subareas by ridges, and each subarea can be considered as a separate partition. Then, we formulate the SILDP in the scenario with the partition structure as the quadratic assignment problem. After that, we propose two deployment methods based on the genetic algorithm to address the SILDP. These two methods are the same in optimization objectives, but different in deployment sequence. The experimental results show that the proposed deployment methods equips better performance in terms of deployment cost compared with the other six peer algorithms.

关键词： Internet of Things Genetic algorithms Wireless sensor networks Optimization Heuristic algorithms Computational modeling Peer-to-peer computing area coverage problem genetic algorithm (GA) SIL deployment problem (SILDP) solar insecticidal lamps Internet of Things (SIL-IoTs) wireless sensor networks (WSNs)

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A new metaheuristic approach based on orbit in the multi-objective optimization of wireless sensor networks

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WIRELESS NETWORKS 2021年第1期27卷 285-305页

作者： Ozdag, Recep Canayaz, Murat Van Yuzuncu Yil Univ Dept Comp Engn TR-65080 Van Turkey

Wireless sensor networks (WSNs) is a research area which has been used in various applications and has continuously developed up to now. WSNs are used in many applications, especially in military and civilian applications, with the aim of monitoring the environment and tracking objects. For this purpose, increasing the coverage rate of WSNs is one of the important criteria that determine the effective monitoring of the network. Since the sensors that make up the WSNs have a limited capacity in terms of energy, process and memory, various algorithmic solutions have been developed to optimize this criterion. The effective dynamic deployment of sensor nodes, which is the primary goal of these solutions, has a critical role in determining the performance of the network. A new orbit-based dynamic deployment approach based on metaheuristic Whale Optimization Algorithm has been proposed in this study. The goal is to optimize the convergence speed of the nodes, the coverage rate of the network, the total displacement (movement) distances of sensors and the degree ofk-coverage of each target (Grid) point in the area by effectively performing the dynamic deployments of sensors after their random distribution. This approach is compared with MADA-WOA and MADA-EM in the literature. Simulation results indicated that the approach developed in rapidly converging sensors to each other, increasing the network's coverage rate, and in minimizing the total movement distances of the sensors in the area and the degrees ofk-coverage of Grid points covered by the sensors could be proposed.

关键词： Wireless sensor networks Sensor deployment area coverage problem Whale optimization algorithm Binary detection model Degree ofk-coverage

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Applications of Wireless Sensor Networks for area coverage in Microgrids

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IEEE TRANSACTIONS ON SMART GRID 2018年第3期9卷 1590-1598页

作者： Wu, Hongyu Shahidehpour, Mohammad Natl Renewable Energy Lab Power Syst Engn Ctr Golden CO 80401 USA IIT Dept Elect & Commun Engn Chicago IL 60616 USA

area coverage is a critical issue which will have a major impact on the sensing quality over targeted regions in wireless sensor networks. This paper studies the area coverage problem (ACP) with non-penetrable obstacles in microgrids, where a sensor cannot be deployed or sensing signals cannot pass through. The target coverage region is discretized in a deployment map representation of non-penetrable obstacles. A probability detection model is utilized to represent sensors with a variable distance coverage. The ACP is formulated as a mixed integer nonlinear programming problem and an iterative process is developed to solve the problem. The microgrid at Illinois Institute of Technology (IL Tech) is used as a practical example. Both the normal and the N-1 contingency deployments of sensors are simulated for optimizing the ACP at the IL Tech microgrid.

关键词： Microgrids wireless sensors area coverage problem distributed energy resource ZigBee

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Game theory based node scheduling as a distributed solution for coverage control in wireless sensor networks

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2017年 65卷 137-146页

作者： Movassagh, Mahdi Aghdasi, Hadi S. Univ Tabriz Fac Elect & Comp Engn Comp Engn Dept Tabriz *** Iran

One of the important quality of services of Wireless Sensor Networks is the coverage, which focuses on providing near optimum coverage rate without decreasing network lifetime. Many distributed solutions have been proposed for this issue most of which try to select a minimum number of nodes as active while keeping others in sleep mode to preserve energy and extend network lifetime. However, these methods suffer from lacking a mathematical basis for their nodes selection approach. In this paper, we propose a distributed method for tackling this challenge by exploiting Game Theory as the mathematical basis for selecting active nodes named Game Theory based node Scheduling for coverage control (GTSC). In GTSC, nodes compete each other to become active through exploiting their coverage redundancy, activation cost, the number of active neighbors, and uncovered region. The comparison of simulation results with the results of a well-known method and a state-of-the-art one shows that the proposed method outperforms both of them in terms of prolonging coverage, network lifetime, and energy efficiency, besides the redundancy rate reduction. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： area coverage problem Game theory Network lifetime prolonging Distributed node scheduling methods Wireless sensor networks

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A New Sensing Direction Rotation Approach to area coverage Optimization in Directional Sensor Network

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JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2020年第2期24卷 206-213页

作者： Peng, Song Xiong, Yonghua China Univ Geosci Sch Automat 388 Lumo Rd Wuhan 430074 Hubei Peoples R China

coverage is a crucial issue in directional sensor networks (DSNs), and a high coverage ratio ensures a good quality of service (QoS). However, a DSN encounters various problems because they use directional sensor nodes, which are characterized by directionality and a definite sensing angle. To address the area coverage problem of DSNs, this paper proposes a new sensing direction rotation approach to optimize coverage. First, we conduct grid partitioning in the target area and propose a coverage verification algorithm to justify the coverage situation of the grid points. Then, we utilize particle swarm optimization (PSO) to find an optimal sensing direction group of the directional sensor nodes to maximize the coverage ratio. Extensive simulation experiments were conducted to prove the effectiveness and reliability of our proposed approach. The results show that the approach improves the area coverage ratio of DSNs in various scenarios.

关键词： directional sensor network area coverage problem sensing direction rotation coverage verification algorithm particle swarm optimization

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area coverage in Heterogeneous Multistatic Sonar Networks: A Simulated Annealing Approach 15th

Area Coverage in Heterogeneous Multistatic Sonar Networks: A...

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15th International Conference of the Metaheuristics International Conference (MIC)

作者： Thuillier, Owein Le Josse, Nicolas Olteanu, Alexandru-Liviu Sevaux, Marc Tanguy, Herve Thales Def & Mission Syst Brest France Univ Bretagne Sud Lab STICC UMR CNRS 6285 Lorient France

ISBN: (纸本)9783031629211;9783031629228

In this paper, we propose a Simulated Annealing (SA) metaheuristic for efficiently solving the area coverage (AC) problem in Heterogeneous Multistatic Sonar Networks (HMSNs). In this problem, which is new in the literature, the aim is to determine the optimal location for the various sensors making up an HMSN, which is a particular case of Heterogeneous Wireless Sensor Networks (HWSNs). HMSNs are made up of a set of acoustic buoys, or sonobuoys, dropped by an airborne carrier and which can be transmitter-only (Tx), receiver-only (Rx) or transmitter-receiver (TxRx). In particular, an HMSN consists of a set of active sonar systems in monostatic and/or bistatic configuration. The bistatic case refers to the pairing between a source from a Tx or TxRx buoy with a receiver from another Rx or TxRx buoy, which may be kilometers apart from the former. This contrasts with the monostatic case, referring to the situation where both the source and receiver are integrated within the same unit, specifically a TxRx buoy. In addition, in this work, we take into account a certain number of operational aspects such as coastlines, probabilistic detection models, an adverse effect called direct blast as well as variable performance depending on the source/receiver pair under consideration. Moreover, we also consider the possibility that some pairings might be infeasible due to inter-sensor incompatibility, for example because of different operating frequencies. Finally, we present numerical results in which we compare ourselves with a set of tailored Mixed-Integer Linear Programs (MILPs) for the same problem.

关键词： OR in defense Multistatic sonar networks Heterogeneous sensors area coverage problem Metaheuristic Simulated annealing

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