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21st International Conference on Computer Information Systems and Industrial Management (CISIM)

作者： Trojanowski, krzysztof Mikitiuk, Artur Grzeszczak, Jakub A. Cardinal Stefan Wyszynski Univ Warsaw Woycickiego 1-3 PL-01938 Warsaw Poland

ISBN: (纸本)9783031105395;9783031105388

Unmanned aerial vehicles (UAVs) with base stations can deliver communication and support services in emergency conditions. Their positions over, e.g., a disaster or festive area, are of utmost importance for ground users' connectivity quality. We propose a new model of UAVs deployment optimization problem to minimize the number of UAVs used to provide wireless coverage. An evolutionary approach equipped with the problem-specific representation of solution and perturbation operators reduces the number of UAVs by their smart deployment over the area. For simulations, we propose a new set of benchmark problems. Simulation results show the algorithm's efficiency and reveal the most beneficial values of the algorithm's parameters.

关键词： Unmanned aerial vehicles Efficient placement Evolutionary algorithm k-coverage problem

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A Fast Optimization Algorithm for k-coverage problem 13th

A Fast Optimization Algorithm for <i>K</i>-Coverage Problem

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13th International Conference on Intelligent Computing (ICIC)

作者： Pei, Jingwen Maomao Wang, Jiayin Univ Connecticut Dept Comp Sci & Engn Storrs CT 06269 USA Xi An Jiao Tong Univ Sch Management Xian Shaanxi Peoples R China Xi An Jiao Tong Univ Inst Data Sci & Informat Qual Xian Shaanxi Peoples R China Xi An Jiao Tong Univ Shaanxi Engn Res Ctr Med & Hlth Big Data Xian 710049 Shaanxi Peoples R China

ISBN: (纸本)9783319633091;9783319633084

k-coverage optimization is widely used in healthcare environments, which minimizing the number of directional receivers that guarantee a given region is covered k times. As k-coverage optimization is NP-hard, a commonly used approach for finding the optimal solution is integer linear programming. However, it can be slow for many practical instances. In this article, we propose an exact dynamic programming algorithm based on tree-decomposition. A probability-distribution density function is introduced to describe the relative importance of various areas and compute the minimal optimized sub-structures. We also show that this algorithm can be easily extended to provide exact solutions for different coverage ratio requirements. When compared with the ILP approach and greedy algorithm, our algorithm provides accurate solutions without scarifying too much on efficiency.

关键词： k-coverage problem ILP Tree decomposition algorithm

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Discrete grey wolf optimization algorithm for solving k-coverage problem in directional sensor networks with network lifetime maximization viewpoint

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APPLIED SOFT COMPUTING 2023年 146卷

作者： Ekhlas, Vahid Reza Shirvani, Mirsaeid Hosseini Dana, Arash Raeisi, Nima Islamic Azad Univ Dept Elect Engn Cent Tehran Branch Tehran Iran Islamic Azad Univ Dept Comp Engn Sari Branch Sari Iran

Unlike the traditional wireless sensor networks (WSNs) which apply omni-directional sensors, the directional sensor networks (DSNs) utilize directional sensor nodes. Each directional sensor in DSN is a self-configured in one direction and one coverage range at a same time. In critical industries, the target coverage problem in which every target should be observed by k different sensors increases the reliability and leads the fault tolerant observation. In this case, the huge amount of energy is consumed in comparison with one coverage problem. Since the business continuity in such industries strongly depends on the network lifetime, the energy management and lifetime maximization of such resource-limited networks are still of the most important challenges. To address the issue, this paper formulates the k-coverage challenge to a discrete optimization problem with the network lifespan expansion viewpoint which is an NP-Hard problem. To solve this combinatorial problem, a discrete grey wolf optimization algorithm (D-GWA) is presented. This D-GWA proposes abundant novel exploration and exploitation procedures which permutes discrete search space efficiently. In this regard, the new fitness function is also defined which steers solutions in the directions to engage sensors uniformly in different rounds. It potentially improves network lifetime because of uniform battery usage. During the course of optimization, it utilizes temperature concept of simulated annealing algorithm to running away from local trap. To verify the proposed algorithm in solving k-coverage problem in DSNs, twelve scenarios are conducted. The simulation results experimentally prove that the totally dominance of the proposed algorithm against state-of-the-arts HTOH, LA-based, GWA, and hybrid PSO-GA approaches respectively are the amount of 31.37%, 20.97%, 14.12%, and 7.93% improvement in term of network lifetime expansion. Furthermore, the behavior of D-GWA shows the high potential of scalability in

关键词： Directional sensor network (DSN) Video sensor network (VSN) Discrete grey wolf optimization algorithm (D-GWA) k-coverage problem Network lifespan maximization

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THE k-coverage CONCENTRATOR LOCATION problem

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APPLIED MATHEMATICAL MODELLING 1992年第2期16卷 94-100页

作者： SHETTY, B SARATHY, R SEN, A ILLINOIS STATE UNIV DEPT ACCOUNTINGNORMALIL 61761

This paper studies the problem of assigning multiple concentrators to each terminal site in a centralized teleprocessing network. This problem requires that each terminal in the network be covered by more than one concentrator to provide increased reliability. We formulate the problem as an extension of the single-source capacitated warehouse location model and solve it using a subgradient algorithm. The subgradient optimization algorithm uses the Lagrangian relaxation technique to generate lower bounds on the optimal objective value. Upper bounds are generated by using a heuristic procedure that modifies the Lagrangian solution to attain feasibility. The algorithm has been tested on several hundred problems with variable dimensions of up to 1000 terminals, 100 concentrators, and five coverages. Computational experience indicates that our approach is extremely effective for obtaining near-optimal solutions. Most problems converged within 0.05% of the optimum and required very little computational effort on an IBM 3090.

关键词： WAREHOUSE LOCATION SUBGRADIENT OPTIMIZATION COMPUTER NETWORkS k-coverage problem

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A Novel Particle Swarm Optimization Algorithm for k-coverage problems in Wireless Sensor Networks 24

A Novel Particle Swarm Optimization Algorithm for k-Coverage...

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24th IEEE International Conference on Computer Supported Cooperative Work in Design (IEEE CSCWD)

作者： Zhang, Yingbo Shen, Weiming Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan Peoples R China

ISBN: (纸本)9781728165974

In wireless sensor network, since the sensor signal coverage is directly related to the optimization of sensor resources, it is one of the most basic problems. To find the minimum number of sensors needed for the deployment and optimize the positions of sensors, self-adaptive estimation particle swarm optimization (SEPSO) is adopted. In some scenes, sensors should be avoided being placed in the area where it is inconvenient to make deployment, and therefore in the process of searching for positions of sensors, a re-deployment method called supplementary boundary condition for SEPSO is proposed to deal with those errant sensors. Extensive experiment results showed that, compared with the virtual force approach, the proposed method can achieve better deployment with less computing time. When the number of sensors is small, the virtual force method performs well, but when the number of sensors increases gradually, the calculation time will increase significantly, but the result does not improve compared with PSO. Two application experiments were conducted in an office scene and in a forest park scene, and the results in both experiments validated the feasibility of the proposed method.

关键词： PSO boundary conditions k-coverage problem optimal sensor deployment

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Optimizing k-coverage of mobile WSNs

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EXPERT SYSTEMS WITH APPLICATIONS 2018年 92卷 142-153页

作者： Elhoseny, Mohamed Tharwat, Alaa Yuan, Xiaohui Hassanien, Aboul Ella Mansoura Univ Fac Comp & Informat Mansoura Daqahlia Egypt Frankfurt Univ Appl Sci Fac Comp Sci & Engn Frankfurt Germany Univ North Texas Dept Comp Sci & Engn Denton TX 76203 USA Cairo Univ Fac Comp & Informat Giza Egypt SRGE Cairo Egypt

Recently, Wireless Sensor Networks (WSNs) are widely used for monitoring and tracking applications. Sensor mobility adds extra flexibility and greatly expands the application space. Due to the limited energy and battery lifetime for each sensor, it can remain active only for a limited amount of time. To avoid the drawbacks of the classical coverage model, especially if a sensor died, k-coverage model requires at least k sensor nodes monitor any target to consider it covered. This paper proposed a new model that uses the Genetic Algorithm (GA) to optimize the coverage requirements in WSNs to provide continuous monitoring of specified targets for longest possible time with limited energy resources. Moreover, we allow sensor nodes to move to appropriate positions to collect environmental information. Our model is based on the continuous and variable speed movement of mobile sensors to keep all targets under their cover all times. To further prove that our proposed model is better than other related work, a set of experiments in different working environments and a comparison with the most related work are conducted. The improvement that our proposed method achieved regarding the network lifetime was in a range of 26%-41.3% using stationary nodes while it was in a range of 29.3%-45.7% using mobile nodes. In addition, the network throughput is improved in a range of 13%-17.6%. Moreover, the running time to form the network structure and switch between nodes' modes is reduced by 12%. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Wireless Sensor Networks (WSN) Genetic Algorithm (GA) k-coverage problem Mobility sensor networks

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Quasi-optimal scheduling algorithm for area coverage in multi-functional sensor networks

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INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING 2013年第2期14卷 109-122页

作者： Molnar, Miklos Simon, Gyula Goenczy, Laszlo Univ Montpellier 2 Dept Comp Sci IUT LIRMM F-34095 Montpellier 5 France Univ Pannonia Dept Comp Sci H-8200 Veszprem Hungary Budapest Univ Technol & Econ Dept Measurement & Informat Syst H-1117 Budapest Hungary

Wireless Sensor Networks (WSNs) are widely used to perform measurement and monitoring tasks in large sensing fields. Several applications require every point in the monitored area to be covered by at least k sensors (k-coverage problem) for measurement accuracy or robustness. In heterogeneous multi-functional sensor networks, p parallel observation tasks are performed with p types of sensors, each task having its own k(i) (i = 1, 2,..., p) coverage requirement, assuming that multi-functional sensors are used which may have multiple measurement capabilities (multi-k-coverage problem). In order to prolong the lifetime of the network, active and sleeping states of sensors can be altered while maintaining the required coverage for all sensing tasks. In this paper an efficient distributed sensor state scheduling algorithm for multi-functional WSNs is proposed to solve the multi-k-coverage problem. The proposed multi-functional controlled greedy sleep algorithm is the generalisation of a recently proposed quasi-optimal scheduling algorithm. It is easy to implement and solves the common scheduling problem of heterogeneous multi-functional sensor networks. It has low local communication overhead and can adapt to dynamic changes in the network, while the required network-wide coverage for all sensing tasks is guaranteed as long as it is physically possible. The performance and the fault tolerance of the algorithm are illustrated by simulation examples.

关键词： WSNs wireless sensor networks multi-functional sensors k-coverage problem energy conservation distributed scheduling algorithm

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Online Path Planning of Autonomous UAVs for Bearing-Only Stand off Multi-Target Following in Threat Environment

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IEEE ACCESS 2018年 6卷 22531-22544页

作者： Jiang, Hao Liang, Yueqian Beihang Univ Ctr Informat & Control Res Div 7 Beijing 100191 Peoples R China

The problem of steering multiple fixed-wing autonomous unmanned aerial vehicles (UAVs) to follow the multiple noncooperative and high agile surface targets at a specified standoff distance in a threat environment is studied. Two kinds of threats and missed detection of bearing-only sensors are considered. The average nonlinear least-square estimation method is proposed to acquire the position of the targets using noisy measurements, and then, the trajectories of the targets are approximated by the quadratic functions of time. Dummy targets of the same number as UAVs are created according to the task allocation result to achieve the optimal geometric configuration of the multiple cooperative UAVs. And a case-based guidance method is established to finally accomplish the multi-target standoff following mission on-line. Simulation experiments are given to assess the proposed method.

关键词： Standoff target following autonomous system path planning threat environment k-coverage problem

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On the Self-Organization of Mobile Agents to Ensure Dynamic Multi-level coverage in Sensor Networks 19

On the Self-Organization of Mobile Agents to Ensure Dynamic ...

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2nd International Conference on Networking, Information Systems and Security (NISS)

作者： Regragui, Younes Moussa, Najem Chouaib Doukkali Univ Dept Comp Sci LAROSERI El Jadida Morocco

ISBN: (纸本)9781450366458

A critical issue for the k-coverage problem in wireless sensor networks is how efficiently deploying sensors to cover an area of interest. In many critical scenarios such as in the military field, ensuring that each point in the monitored area of interest is sufficiently covered can guaranty the effectiveness of intrusion detection for both monitoring and tracking applications. Prior research indicated that Mobile Sensor Networks (MSNs) are capable of acting with great flexibility to enhance and cover holes appeared in certain regions when a sensor died due to limited energy and battery lifetime. In this paper, we consider the use of a strategy based on the collective motion mechanisms to relocate sensors nodes to achieve a higher k-coverage level. Each sensor node is able to compare its current k-coverage level with a predefined threshold so as to react dynamically by enabling a specific mobility behavior with a high priority. Based on this mobility behavior, a sensor node can move towards other sensors in its local neighborhood, and it would then be closer enough to them in order to enhance its k-coverage level and then it participates in achieving a higher k-coverage level for the whole group. Simulation results show the effectiveness of our considered approach in terms of the k-coverage level of 30 % as well as a significant improvement in energy consumption.

关键词： Sensor Network coverage k-coverage problem Sensor coverage problem Collective Motion Mobile Sensors

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Modeling the Willingness to Interact in Cooperative Multi-robot Systems 12

Modeling the Willingness to Interact in Cooperative Multi-ro...

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12th International Conference on Agents and Artificial Intelligence (ICAART)

作者： Frasheri, Mirgita Esterle, Lukas Papadopoulos, Alessandro Malardalen Univ Vasteras Sweden Aarhus Univ DIGIT Aarhus Denmark

ISBN: (纸本)9789897583957

When multiple robots are required to collaborate in order to accomplish a specific task, they need to be coordinated in order to operate efficiently. To allow for scalability and robustness, we propose a novel distributed approach performed by autonomous robots based on their willingness to interact with each other. This willingness, based on their individual state, is used to inform a decision process of whether or not to interact with other robots within the environment. We study this new mechanism to form coalitions in the on-line multiobject k-coverage problem, and compare it with six other methods from the literature. We investigate the trade-off between the number of robots available and the number of potential targets in the environment. We show that the proposed method is able to provide comparable performance to the best method in the case of static targets, and to achieve a higher level of coverage with respect to the other methods in the case of mobile targets.

关键词： Robot Collaboration k-coverage problem Adaptive Autonomy

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