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Surface Coverage Algorithm in directional sensor networks for Three-Dimensional Complex Terrains

Tsinghua Science and Technology 2016年第4期21卷 397-406页

作者： Fu Xiao Xiekun Yang Meng Yang Lijuan Sun Ruchuan Wang Panlong Yang College of Computer Nanjing University of Posts and Telecommunications and Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks College of Computer Nanjing University of Posts and Telecommunications School of Management and Engineering Nanjing University College of Computer Science and Technology University of Science and Technology of China

Coverage is an important issue in the area of wireless sensor networks, which reflects the monitoring quality of the sensor networks in scenes. Most sensor coverage research focuses on the ideal two-dimensional （2-D） plane and full three-dimensional （3-D） space. However, in many real-world applications, the target field is a 3-D complex surface, which makes conventional methods unsuitable. In this paper, we study the coverage problem in directional sensor networks for complex 3-D terrains, and design a new surface coverage algorithm. Based on a 3-D directional sensing model of nodes, this algorithm employs grid division, simulated annealing, and local optimum ideas to improve the area coverage ratio by optimizing the position coordinates and the deviation angles of the nodes, which results in coverage enhancement for complex 3-D terrains. We also conduct extensive simulations to evaluate the performance of our algorithms.

关键词： directional sensor networks surface coverage simulated annealing complex terrains

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A Hybrid Approach to Maximize the Lifetime of directional sensor networks with Smoothly Varying Sensing Ranges

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Chinese Journal of Electronics 2017年第4期26卷 703-709页

作者： LIU Shufen GAO Sihua BAO Tie ZHANG Yikun College of Computer Science and Technology Jilin University

The difficulty of maximizing the lifetime in directional sensor networks has gained increasing attention recently. Most of the existing studies are focused on directional sensors with single or several predefined sensing ranges. In the present study, directional sensors can change sensing ranges smoothly. We address the problem of maximizing the lifetime in directional sensor networks with such smoothly varying sensing ranges,and propose a hybrid approach that combines a column generation method with an immune genetic algorithm. We search for attractive columns with the genetic algorithm, and optimize them by designing dynamic vaccines. Computational results demonstrate the performance of the proposed approach. Meanwhile,the advantage of the mentioned sensors in terms of solution quality is also revealed.

关键词： directional sensor networks Column generation Immune genetic algorithm

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Solving target coverage problem in directional sensor networks with ability to adjust sensing range using continuous learning automata

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021年第6期41卷 6831-6844页

作者： Qarehkhani, Azam Golsorkhtabaramiri, Mehdi Mohamadi, Hosein Tabari, Meisam Yadollahzadeh Islamic Azad Univ Dept Comp Engn Babol Branch Babol Iran Islamic Azad Univ Dept Comp Engn Azadshahr Branch Azadshahr Iran

directional sensor networks (DSNs) are classified under wireless networks that are largely used to resolve the coverage problem. One of the challenges to DSNs is to provide coverage for all targets in the network and, at the same time, to maximize the lifetime of network. Asolution to this problem is the adjustment of the sensors' sensing ranges. In this approach, each sensor adjusts its own sensing range dynamically to sense the corresponding target(s) and decrease energy consumption as much as possible through forming the best cover sets possible. In the current study, a continuous learning automata-based method is proposed to form such cover sets. To assess the proposed algorithm's performance, it was compared to the results obtained from a greedy algorithm and a learning automata algorithm. The obtained results demonstrated the superiority of the proposed algorithm regarding the maximization of the network lifetime.

关键词： directional sensor networks continuous learning automata target-coverage cover set formation

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A Survey on Barrier Coverage Problem in directional sensor networks

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IEEE sensorS JOURNAL 2015年第2期15卷 876-885页

作者： Tao, Dan Wu, Tin-Yu Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Natl Ilan Univ Dept Comp Sci & Informat Engn Yilan 26041 Taiwan

Barrier coverage guarantees to detect any intruder attempting to cross the barrier of sensor networks. In the majority of studies on barrier coverage using wireless sensor networks, sensors are assumed to have an isotropic sensing model. However, in certain applications like monitoring a region using video cameras, the sensors have directional sensing model. The nature of directional sensor networks demands novel algorithms and solutions. In directional sensor networks, this paper starts from the concept and characteristics of a directional sensing model, and then summarizes the sensing properties and behaviors of directional sensors. In particular, we classify the existing research results into different categories, such as strong barrier and weak barrier, 1-barrier and k-barrier, worst and best-case coverage and exposure path coverage, any-view coverage and full-view coverage, and overview each category in terms of problem definition, assumption, usage, solution, and performance. Finally, the open research problems to be solved and future work are also discussed.

关键词： directional sensor networks barrier coverage coverage optimization directional sensor directional sensing model field-of-view

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Energy-Efficient Probabilistic Barrier Construction in directional sensor networks

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IEEE sensorS JOURNAL 2017年第3期17卷 897-908页

作者： Fan, Xinggang Chen, Qihui Che, Zhicong Hao, Xiang Zhejiang Univ Technol Dept Comp Sci & Technol Hangzhou 310023 Zhejiang Peoples R China

k-barrier coverage is one of the critical issues in directional sensor networks. In actual application, the sensing distance becomes small with the increase of sensing angle, and the event sensing probability is constantly changing as the distance between node and event changes. But so far, there is no high efficient distributed barrier construction scheme based on a directional probabilistic sensing model. This paper first creates a directional probabilistic sensing model with changing angle, based on which four target locations of barrier member are created in a distributed manner. In addition, the energy efficiency ratio (EER) is investigated to minimize the energy consumption. Based on these two models, a distributed probabilistic barrier construction scheme based on EER is proposed, which commences the initiator of the barrier on the west end boundary and selects suitable relay sensors from left to right until the east end boundary is reached. The target locations and corresponding orientations of barrier member are determined only by its ancestor. When there are many candidate relay sensors, the one with the largest EER is the actual relay sensor. Simulation results indicate our method could form k-barrier coverage with smaller energy consumption than other methods.

关键词： directional sensor networks barrier coverage probabilistic changing sensing angle energy consumption energy efficiency ratio

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Probabilistic coverage in directional sensor networks

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WIRELESS networks 2019年第1期25卷 355-365页

作者： Si, Pengju Wu, Chengdong Zhang, Yunzhou Chu, Hao Teng, He Northeastern Univ Fac Robot Sci & Engn Shenyang 110819 Liaoning Peoples R China

Correct and realistic sensing model is of great significance for sensor networks to perform environmental monitoring. However, the sensing capabilities of directional sensors are usually affected by environmental factors and intrinsic properties. As a result, it is not suitable to use simple binary sensing model for directional sensor networks (DSNs). In this paper, we consider probabilistic sensing models for DSNs to have practical considerations. Firstly, an exponential decay probabilistic sensing model for DSNs is considered reference to omni-directional probabilistic sensing model for traditional sensor. Secondly, we propose a fault-tolerant probabilistic sensing model with respect to orientation error and rotation error. Furthermore, combined the exponential decay probability with the fault-tolerant probability, a hybrid probabilistic sensing model is formed for DSNs. Then, based on our probability sensing models, a probabilistic coverage algorithm is introduced for random deployment to compute the coverage probability of DSNs. Performance results demonstrate that the proposed algorithm with probabilistic sensing models for DSNs is capable of providing desirable surveillance level.

关键词： directional sensor networks Probabilistic sensing model Coverage probability Random deployment Algorithm

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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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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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Optimization of the directional sensor networks With Rotatable sensors for Target-Barrier Coverage

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IEEE sensorS JOURNAL 2021年第6期21卷 8276-8288页

作者： Chen, Gong Xiong, Yonghua She, Jinhua Wu, Min Galkowski, Krzysztof China Univ Geosci Sch Automat Wuhan 430074 Peoples R China Hubei Key Lab Adv Control & Intelligent Automat C Wuhan 430074 Peoples R China Tokyo Univ Technol Sch Engn Tokyo 1920982 Japan Univ Zielona Gora Inst Control & Computat Engn PL-65417 Zielona Gora Poland

In wireless sensor networks (WSNs), the barrier coverages sensing belt can be open or closed. A closed belt is more difficult to construct than an open belt, as it has higher requirements, especially for the directional sensor networks (DSNs) with rotatable sensors. A target-barrier is a closed annular belt around a target with anti-intrusion and surveillance protection functions for both the inside and outside of the belt. Thus, a target-barrier is well suited to many applications including ecological reserve monitoring and contamination monitoring. In this paper, we employ the Virtual Target-barrier Construction (VTBC) method to facilitate its construction. First, we define and calculate a virtual barrier curve in order to convert the complicated target-barrier construction problem in a rotatable DSN into a much simpler optimization problem. Then, a distributed particle swarm optimization (D-PSO) algorithm is designed to achieve a near optimal coverage of the closed virtual barrier curve. Finally, simulations are presented to prove that VTBC has a better performance than other approaches.

关键词： sensors Wireless sensor networks Belts Optimization Particle swarm optimization Biological system modeling Surveillance directional sensor networks target-barrier coverage virtual barrier curve particle swarm optimization

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A new genetic-based approach for solving k-coverage problem in directional sensor networks

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2021年 154卷 16-26页

作者： Alibeiki, Abolghasem Motameni, Homayun Mohamadi, Hosein Islamic Azad Univ Dept Comp Engn Sari Branch Sari Iran Islamic Azad Univ Dept Comp Engn Azadshahr Branch Azadshahr Iran

In recent years, the use of directional sensor networks (DSNs) has continued to rise increasingly, which is due to their extensive use in many situations. In such networks, the main problem is how to cover the targets distributed in a defined area and simultaneously prolong the network lifetime as much as possible. The reason of this problem is the limitation of both sensing angle and energy resource of sensors in such networks. This problem gets more complex in cases where targets need to be covered by more than one sensor direction (i.e., each target needs to be monitored for at least k times). This problem is generally known as target k-coverage problem which its NP-completeness has been already proved in the literature. The k-coverage problem can be considered in over-provisioned and under-provisioned environments. In both of these environments, especially in the latter, it is important to create a balanced coverage, as these environments do not have enough sensors to monitor all targets for k times. Thus, in this paper, we proposed a genetic-based algorithm to solve the problem in over-provisioned environments, then developed the proposed algorithm in another way to solve the problem in under-provisioned networks so that it uses the minimum number of sensors. many experiments were performed to test the efficiency of the proposed algorithm, and the obtained results showed the high capacity of the proposed algorithm in solving the k-coverage problem in both environments. (C) 2021 Elsevier Inc. All rights reserved.

关键词： directional sensor networks Scheduling algorithms Genetic algorithm

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