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Target coverage through distributed clustering in directional sensor networks

EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2015年第1期000卷 1-18页

作者： Islam, Md. Mofijul Ahasanuzzaman, Md. Razzaque, Md. Abdur Hassan, Mohammad Mehedi Alelaiwi, Abdulhameed Xiang, Yang Univ Dhaka Dept Comp Sci & Engn Green Networking Res Grp Dhaka 1000 Bangladesh King Saud Univ Coll Comp & Informat Sci Informat Syst Dept Riyadh 11543 Saudi Arabia Deakin Univ Sch Informat Technol Burwood Vic 3125 Australia

Maximum target coverage with minimum number of sensor nodes, known as an MCMS problem, is an important problem in directional sensor networks (DSNs). For guaranteed coverage and event reporting, the underlying mechanism must ensure that all targets are covered by the sensors and the resulting network is connected. Existing solutions allow individual sensor nodes to determine the sensing direction for maximum target coverage which produces sensing coverage redundancy and much overhead. Gathering nodes into clusters might provide a better solution to this problem. In this paper, we have designed distributed clustering and target coverage algorithms to address the problem in an energy-efficient way. To the best of our knowledge, this is the first work that exploits cluster heads to determine the active sensing nodes and their directions for solving target coverage problems in DSNs. Our extensive simulation study shows that our system outperforms a number of state-of-the-art approaches.

关键词： directional sensor networks Target coverage Distributed algorithm Network lifetime Cluster

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A New Learning Automata-Based Algorithm to the Priority-Based Target Coverage Problem in directional sensor networks 6

A New Learning Automata-Based Algorithm to the Priority-Base...

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6th International ICST Conference on Mobile networks and Management (MONAMI)

作者： Salleh, Shaharuddin Marouf, Sara Mohamadi, Hosein Univ Teknol Malaysia Ctr Ind & Appl Math Johor Baharu Malaysia

ISBN: (纸本)9783319162928;9783319162911

One of the main operations in directional sensor networks (DSNs) is the surveillance of a set of events (targets) that occur in a given area and, at the same time, maximization of the network lifetime;this is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

关键词： directional sensor networks Target coverage problem Cover set formation Learning automata

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A Learning Automata-Based Solution to the Priority-Based Target Coverage Problem in directional sensor networks

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WIRELESS PERSONAL COMMUNICATIONS 2014年第3期79卷 2323-2338页

作者： Mohamadi, Hosein Salleh, Shaharuddin Ismail, Abdul Samad Univ Teknol Malaysia UTM Ctr Ind & Appl Math Johor Baharu 81310 Malaysia Univ Teknol Malaysia Fac Comp Dept Comp Sci Johor Baharu 81310 Malaysia

In recent years, directional sensor networks composed of directional sensors have attracted a great deal of attention due to their extensive applications. The main difficulties associated with directional sensors are their limited battery power and restricted sensing angle. Moreover, each target may have a different coverage quality requirement that can make the problem even more complicated. Therefore, satisfying the coverage quality requirement of all the targets in a specific area and maximizing the network lifetime, known as priority-based target coverage problem, has remained a challenge. As sensors are often densely deployed, organizing the sensor directions into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set can satisfy coverage quality requirement of all the targets. In order to verify the performance of the proposed algorithm, several simulations were conducted. The obtained results showed that the proposed algorithm was successful in extending the network lifetime.

关键词： directional sensor networks Target coverage problem Cover set formation Learning automata

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Heuristic methods to maximize network lifetime in directional sensor networks with adjustable sensing ranges

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2014年 46卷 26-35页

作者： Mohamadi, Hosein Salleh, Shaharuddin Razali, Mohd Norsyarizad Univ Teknol Malaysia Ctr Ind & Appl Math Johor Baharu 81310 Malaysia Univ Teknol Malaysia Fac Sci Johor Baharu 81310 Malaysia

During recent years, several efficient algorithms have been designed for solving the target coverage problem in directional sensor networks (DSNs). Conventionally, it is assumed that sensors have a single power level. Though, it is clear that, in real applications, sensors may have multiple power levels that determine different sensing ranges and power consumptions. One of the most significant challenges associated with the DSNs is monitoring all the targets in a given area and, at the same time, maximizing the network lifetime. In this paper, this issue is known as Maximum Network Lifetime with Adjustable Ranges (MNLAR) which has not been already studied in the DSNs. In this paper, we propose two heuristic algorithms (Algorithms 1 and 2) to solve the problem. In order to evaluate the performance of the proposed algorithms, extensive experiments were conducted. The obtained results were compared to a theoretical upper bound in order to measure the quality of the solutions provided by the proposed algorithms. The results demonstrated that Algorithm 2 was more successful than Algorithm 1 in terms of extending the network lifetime. Crown Copyright (C) 2014 Published by Elsevier Ltd. All rights reserved.

关键词： directional sensor networks Cover set formation Scheduling algorithms

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A Coverage Enhancement Algorithm Based on Constrained Artificial Fish-Swarm in directional sensor networks

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JOURNAL OF INTERNET TECHNOLOGY 2014年第1期15卷 43-52页

作者： Tao, Dan Tang, Shaojie Liu, Liang Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Sch Elect & Informat Engn Beijing Peoples R China Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA Beijing Univ Posts & Telecommun Beijing Key Lab Intelligent Telecommun Software & Beijing Peoples R China

Area coverage is an essential issue for sensor networks. The majority of the existing studies on area coverage are based on omnidirectional sensing model. However, some popular sensors have a limited angle of sensing range. This paper investigates area coverage enhancement by directional sensors with tunable sensing orientations. Firstly, we model the deployment of directional sensors as a 2D stationary Poisson point process, and evaluate the relationship between the coverage probability and the number of directional sensors. We introduce the notion of "sensing centroid," which is the geometric center of a sensing sector to simplify the pending problem. Moreover, we regard "sensing centroid" as artificial fish, which search an optimal solution in the solution space by simulate fish swarm behaviors with a tendency toward high food consistence. Considering that AFs have to satisfy both kinematic constraint and dynamic constraint in the process of motion, we propose a constrained artificial fish-swarm algorithm, and discuss the control laws to guide the behaviors of AFs with quick convergence speed. Finally, mass of simulations validate the theoretical findings of our solution.

关键词： directional sensor networks Artificial fish-swarm Area coverage Coverage enhancement

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Voronoi-based coverage improvement approach for wireless directional sensor networks

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2014年第0期39卷 202-213页

作者： Sung, Tien-Wen Yang, Chu-Sing Natl Cheng Kung Univ Dept Elect Engn Inst Comp & Commun Engn Tainan 70101 Taiwan

Differing from general omnidirectional wireless sensor networks, in the directional sensor networks, the effective sensing range of sensors is characterized by directionality and sensing angle. Therefore, there are dissimilar conditions for the discussion and research on the sensing coverage of directional sensor networks. This study used the characteristics of Voronoi diagram and direction-adjustable directional sensors to propose a distributed greedy algorithm, which can improve the effective field coverage of directional sensor networks. The sensor field is divided into Voronoi cells by the calculation of sensors, and the sensor working direction is evaluated based on Voronoi vertices. Considering the coverage contribution of convex polygonal cell of sensors and the coverage overlap of direction select between neighbor sensors, the working direction is adjusted and controlled, so as to improve the overall sensing field coverage ratio in the sensor network environment without global information. This study used simulation to change various parameters, such as the number of sensors, angle of view, and sensing radius, in the directional sensor network field to evaluate the efficiency of the proposed algorithm, and further analyzed and compared the improvement results of the overall sensing field coverage ratio. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Wireless sensor networks directional sensor networks Voronoi diagram Coverage Angle of view

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Optimization of the Virtual Potential Field Based on Coverage-enhancing Algorithm for directional sensor networks 3

Optimization of the Virtual Potential Field Based on Coverag...

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3rd International Conference on Advanced Engineering Materials and Architecture Science (ICAEMAS)

作者： Zhu, Jun Shi, Chen Zhu, Shanshan Zhang, Jun Anhui Univ Minist Educ Key Lab Intelligent Comp & Signal Proc 3 Feixi Rd Hefei 230039 Peoples R China Anhui Air Traff Management Bur Hefei 230001 Peoples R China

ISBN: (纸本)9783038352679

After directional sensor nodes are randomly thrown into target area, coverage ratio often less than the anticipant value, in order to improve the coverage, sensor nodes should turn from overlapping regions to coverage holes by a much faster way. In this paper, we improved the existing potential field based coverage-enhancing algorithm(PFCEA), presented a optimization of the virtual potential field based on coverage-enhancing algorithm for directional sensor networks(OPFCEA), we introducing a new-style virtual node to enhance the coverage of boundary region and a new-style control for the rotation angle. By these ways, we can improve network's performance. This algorithm enhanced the coverage ratio of the network, the simulation results show the effectiveness of the algorithm.

关键词： directional sensor networks Virtual Potential Field Coverage Enhancement

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An effective hybrid genetic algorithm and tabu search for maximizing network lifetime using coverage sets scheduling in wireless sensor networks

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JOURNAL OF SUPERCOMPUTING 2023年第3期79卷 3277-3297页

作者： Mottaki, Nemat Allah Motameni, Homayun Mohamadi, Hosein Islamic Azad Univ Dept Comp Engn Sari Branch Sari Iran Islamic Azad Univ Dept Comp Engn Azadshar Branch Azadshar Iran

Two important issues in Wireless sensor networks (WSNs) are coverage and network lifetime. Network operation in an environment can be divided into two phases, first, making coverage sets and then scheduling them. The preliminary reviews have provided a number of solutions for problem-solving in the first phase, but there is no enough solution provided for the second one. Once the number of sensors in the environment increases, the number of coverage sets as well as the number of order sequences (in which the coverage sets can be scheduled) will also increase. The present study aims to detect a near-optimal scheduling for coverage sets to prolong the network lifetime. This problem was previously introduced as MCSS (Maximum Coverage Sets Scheduling) and it was proved to be an NP-hard problem. This paper presents two algorithms, a Genetic Algorithm (GA) and a Hybrid Algorithm (HA) integrating GA and Tabu Search (TS) to solve the MCSS problem. To reveal its efficiency, the algorithms were compared with a recently proposed algorithm in terms of scheduling the coverage sets. The simulations performed in this study showed that the proposed algorithms were more successful in finding near-optimal scheduling coverage sets.

关键词： directional sensor networks Genetic algorithm Tabu search Coverage set scheduling

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Energy-Efficient Long-Range Sectored Antenna for directional sensor Network Applications

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IETE JOURNAL OF RESEARCH 2024年第5期70卷 4442-4452页

作者： Nagaraju, Shamanth Gudino, Lucy J. Kadam, Bhushan V. Khairnar, Vikas V. Rodriguez, Joseph X. Ramesha, C. K. Christ Univ Sch Engn & Technol Dept Comp Sci & Engn Bengaluru India BITS Pilani Dept Comp Sci & Informat Syst Pilani India BITS Pilani Dept Elect & Elect Engn KK Birla Goa campus Pilani Goa India VIT AP Univ Sch Elect Engn Amaravati Andhra Pradesh India Christ Univ Sch Engn & Technol Dept Elect & Elect Engn Bengaluru India

The popularity of directional sensor Network (DSN) is increasing due to their improved transmission range, spectral reusability, interference mitigation, and energy efficiency. In this paper, the radio module of the DSN is implemented using an eight-sector antenna array. Two types of sectored antennas, namely the Rectangular Patch Sectored Antenna (RPSA) and the Triangular Patch Sectored Antenna (TPSA), are proposed to operate at frequency of 2.4 GHz ISM band. The RPSA has a half-power beamwidth (HPBW) of 45 & DEG;and a peak gain of 5.2 dBi, while the TPSA has an HPBW of 48 & DEG;and a peak gain of 4.16 dBi. The design and performance evaluation of RPSA and TPSA in terms of gain, reflection characteristics (|S11|), and HPBW are conducted using Ansys High Frequency Structure Simulator (HFSS) and Vector Network Analyzer (VNA). To demonstrate the concept, the fabricated sectored antennas are connected to MicaZ Wireless sensor Network (WSN) nodes using an indigenously designed Single Pole 8 Throw (SP8T) Radio Frequency (RF) switchboard. The performance of the DSNs based on RPSA and TPSA is evaluated using the Cooja simulator and a testbed consisting of MicaZ nodes. The results show that RPSA outperforms TPSA and omnidirectional-based WSNs in terms of power consumption, received signal strength, and packet delivery ratio.

关键词： Cooja simulator directional sensor networks Microstrip patch antenna Radio frequency switchboard Sectored antenna

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A learning automata-based algorithm for solving coverage problem in directional sensor networks

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COMPUTING 2013年第1期95卷 1-24页

作者： Mohamadi, Hosein Ismail, Abdul Samad Bin Haji Salleh, Shaharuddin Univ Teknol Malaysia Dept Comp Fac Comp Sci & Informat Johor Baharu 81310 Malaysia Univ Teknol Malaysia Dept Math Fac Sci Johor Baharu 81310 Malaysia

Wireless sensor networks have been used in a wide variety of applications. Recently, networks consisting of directional sensors have gained prominence. An important challenge facing directional sensor networks (DSNs) is maximizing the network lifetime while covering all the targets in an area. One effective method for saving the sensors' energy and extending the network lifetime is to partition the DSN into several covers, each of which can cover all targets, and then to activate these covers successively. This paper first proposes a fully distributed algorithm based on irregular cellular learning automata to find a near-optimal solution for selecting each sensor's appropriate working direction. Then, to find a near-optimal solution that can cover all targets with the minimum number of active sensors, a centralized approximation algorithm is proposed based on distributed learning automata. This algorithm takes advantage of learning automata (LA) to determine the sensors that must be activated at each stage. As the presented algorithm proceeds, the activation process is focused on the sensor nodes that constitute the cover set with the minimum number of active sensors. Through simulations, we indicate that the scheduling algorithm based on LA has better performance than the greedy algorithm-based scheme in terms of maximizing network lifetime.

关键词： directional sensor networks Cover set formation Distributed learning automata

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