The Experts below are selected from a list of 39207 Experts worldwide ranked by ideXlab platform
Shuhui Yang - One of the best experts on this subject based on the ideXlab platform.
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Scan-Based Movement-Assisted Sensor Deployment Methods in Wireless Sensor Networks
IEEE Transactions on Parallel and Distributed Systems, 2007Co-Authors: Shuhui YangAbstract:The efficiency of Sensor networks depends on the coverage of the monitoring area. Although, in general, a sufficient number of Sensors are used to ensure a certain degree of redundancy in coverage, a good Sensor Deployment is still necessary to balance the workload of Sensors. In a Sensor network with locomotion facilities, Sensors can move around to self-deploy. The movement-assisted Sensor Deployment deals with moving Sensors from an initial unbalanced state to a balanced state. Therefore, various optimization problems can be defined to minimize different parameters, including total moving distance, total number of moves, communication/computation cost, and convergence rate. In this paper, we first propose a Hungarian-algorithm-based optimal solution, which is centralized. Then, a localized scan-based movement-assisted Sensor Deployment method (SMART) and several variations of it that use scan and dimension exchange to achieve a balanced state are proposed. An extended SMART is developed to address a unique problem called communication holes in Sensor networks. Extensive simulations have been done to verify the effectiveness of the proposed scheme.
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Optimal movement-assisted Sensor Deployment and its extensions in wireless Sensor networks
Simulation Modelling Practice and Theory, 2007Co-Authors: Shuhui YangAbstract:Abstract In wireless Sensor networks (WSNs), a good Sensor Deployment method is vital to the quality of service (QoS) provided by WSNs. This QoS depends on the coverage of the monitoring area. In WSNs with locomotion facilities, Sensors can move around and self-deploy to ensure coverage and load balancing, where each unit of monitoring area is covered by the same number of Sensors. The movement-assisted Sensor Deployment deals with moving Sensors to meet coverage and load balancing requirements. In SMART [J. Wu, S. Yang, SMART: a scan-based movement-assisted Sensor Deployment method in wireless Sensor networks, in: Proceedings of INFOCOM, 2005], various optimization problems are defined to minimize different parameters, including total moving distance, total number of moves, communication/computation cost, and convergence rate. In this paper, we focus on minimizing the total moving distance and propose an optimal, but centralized solution, based on the Hungarian method. This solution is illustrated in an application where the monitoring area is a 2-D grid-based mesh. We then propose several efficient, albeit non-optimal, distributed solutions based on the scan-based solution in Wu and Yang (2005). Extensive simulations have been done to verify the effectiveness of the proposed distributed solutions.
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smart a scan based movement assisted Sensor Deployment method in wireless Sensor networks
International Conference on Computer Communications, 2005Co-Authors: Shuhui YangAbstract:The efficiency of Sensor networks depends on the coverage of the monitoring area. Although in general a sufficient number of Sensors are used to ensure a certain degree of redundancy in coverage so that Sensors can rotate between active and sleep modes, a good Sensor Deployment is still necessary to balance the workload of Sensors. In a Sensor network with locomotion facilities, Sensors can move around to self-deploy. The movement-assisted Sensor Deployment deals with moving Sensors from an initial unbalanced state to a balanced state. Therefore, various optimization problems can be defined to minimize different parameters, including total moving distance, total number of moves, communication/computation cost, and convergence rate. In this paper, we propose a Scan-based Movement-Assisted Sensor Deployment method (SMART) that uses scan and dimension exchange to achieve a balanced state. SMART also addresses a unique problem called communication holes in Sensor networks. Using the concept of load balancing, SMART achieves good performance especially when applied to uneven distribution Sensor networks, and can be a complement to the existing Sensor Deployment methods. Extensive simulation has been done to verify the effectiveness of the proposed scheme.
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INFOCOM - SMART: a scan-based movement-assisted Sensor Deployment method in wireless Sensor networks
Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies., 1Co-Authors: Shuhui YangAbstract:The efficiency of Sensor networks depends on the coverage of the monitoring area. Although in general a sufficient number of Sensors are used to ensure a certain degree of redundancy in coverage so that Sensors can rotate between active and sleep modes, a good Sensor Deployment is still necessary to balance the workload of Sensors. In a Sensor network with locomotion facilities, Sensors can move around to self-deploy. The movement-assisted Sensor Deployment deals with moving Sensors from an initial unbalanced state to a balanced state. Therefore, various optimization problems can be defined to minimize different parameters, including total moving distance, total number of moves, communication/computation cost, and convergence rate. In this paper, we propose a Scan-based Movement-Assisted Sensor Deployment method (SMART) that uses scan and dimension exchange to achieve a balanced state. SMART also addresses a unique problem called communication holes in Sensor networks. Using the concept of load balancing, SMART achieves good performance especially when applied to uneven distribution Sensor networks, and can be a complement to the existing Sensor Deployment methods. Extensive simulation has been done to verify the effectiveness of the proposed scheme.
T F La Porta - One of the best experts on this subject based on the ideXlab platform.
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proxy based Sensor Deployment for mobile Sensor networks
Mobile Adhoc and Sensor Systems, 2004Co-Authors: Guiling Wang, Guohong Cao, T F La PortaAbstract:To provide satisfactory coverage is very important in many Sensor network applications such as military surveillance. In order to obtain the required coverage in harsh environments, mobile Sensors are helpful since they can move to cover the area not reachable by static Sensors. Previous work on mobile Sensor Deployment is based on a round by round process, where Sensors move iteratively until the maximum coverage is reached. Although these solutions can deploy mobile Sensors in a distributed way, the mobile Sensors may move in a zig-zag way and waste a lot of energy compared to moving directly to the final location. To address this problem, we propose a proxy-based Sensor Deployment protocol. Instead of moving iteratively, Sensors calculate their target locations based on a distributed iterative algorithm, move logically, and exchange new logical locations with their new logical neighbors. Actual movement only occurs when Sensors determine their final locations. Simulation results show that the proposed protocol can significantly reduce the energy consumption compared to previous work, while maintaining similar coverage.
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movement assisted Sensor Deployment
International Conference on Computer Communications, 2004Co-Authors: Guiling Wang, Guohong Cao, T F La PortaAbstract:Sensor Deployment is an important issue in designing Sensor networks. We design and evaluate distributed self-Deployment protocols for mobile Sensors. After discovering a coverage hole, the proposed protocols calculate the target positions of the Sensors where they should move. We use Voronoi diagrams to discover the coverage holes and design three movement-assisted Sensor Deployment protocols, VEC (vector-based), VOR (Voronoi-based), and minimax based on the principle of moving Sensors from densely deployed areas to sparsely deployed areas. Simulation results show that our protocols can provide high coverage within a short deploying time and limited movement.
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INFOCOM - Movement-assisted Sensor Deployment
IEEE INFOCOM 2004, 1Co-Authors: Guiling Wang, Guohong Cao, T F La PortaAbstract:Sensor Deployment is an important issue in designing Sensor networks. We design and evaluate distributed self-Deployment protocols for mobile Sensors. After discovering a coverage hole, the proposed protocols calculate the target positions of the Sensors where they should move. We use Voronoi diagrams to discover the coverage holes and design three movement-assisted Sensor Deployment protocols, VEC (vector-based), VOR (Voronoi-based), and minimax based on the principle of moving Sensors from densely deployed areas to sparsely deployed areas. Simulation results show that our protocols can provide high coverage within a short deploying time and limited movement.
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MASS - Proxy-based Sensor Deployment for mobile Sensor networks
2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975), 1Co-Authors: Guiling Wang, Guohong Cao, T F La PortaAbstract:To provide satisfactory coverage is very important in many Sensor network applications such as military surveillance. In order to obtain the required coverage in harsh environments, mobile Sensors are helpful since they can move to cover the area not reachable by static Sensors. Previous work on mobile Sensor Deployment is based on a round by round process, where Sensors move iteratively until the maximum coverage is reached. Although these solutions can deploy mobile Sensors in a distributed way, the mobile Sensors may move in a zig-zag way and waste a lot of energy compared to moving directly to the final location. To address this problem, we propose a proxy-based Sensor Deployment protocol. Instead of moving iteratively, Sensors calculate their target locations based on a distributed iterative algorithm, move logically, and exchange new logical locations with their new logical neighbors. Actual movement only occurs when Sensors determine their final locations. Simulation results show that the proposed protocol can significantly reduce the energy consumption compared to previous work, while maintaining similar coverage.
Guiling Wang - One of the best experts on this subject based on the ideXlab platform.
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proxy based Sensor Deployment for mobile Sensor networks
Mobile Adhoc and Sensor Systems, 2004Co-Authors: Guiling Wang, Guohong Cao, T F La PortaAbstract:To provide satisfactory coverage is very important in many Sensor network applications such as military surveillance. In order to obtain the required coverage in harsh environments, mobile Sensors are helpful since they can move to cover the area not reachable by static Sensors. Previous work on mobile Sensor Deployment is based on a round by round process, where Sensors move iteratively until the maximum coverage is reached. Although these solutions can deploy mobile Sensors in a distributed way, the mobile Sensors may move in a zig-zag way and waste a lot of energy compared to moving directly to the final location. To address this problem, we propose a proxy-based Sensor Deployment protocol. Instead of moving iteratively, Sensors calculate their target locations based on a distributed iterative algorithm, move logically, and exchange new logical locations with their new logical neighbors. Actual movement only occurs when Sensors determine their final locations. Simulation results show that the proposed protocol can significantly reduce the energy consumption compared to previous work, while maintaining similar coverage.
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movement assisted Sensor Deployment
International Conference on Computer Communications, 2004Co-Authors: Guiling Wang, Guohong Cao, T F La PortaAbstract:Sensor Deployment is an important issue in designing Sensor networks. We design and evaluate distributed self-Deployment protocols for mobile Sensors. After discovering a coverage hole, the proposed protocols calculate the target positions of the Sensors where they should move. We use Voronoi diagrams to discover the coverage holes and design three movement-assisted Sensor Deployment protocols, VEC (vector-based), VOR (Voronoi-based), and minimax based on the principle of moving Sensors from densely deployed areas to sparsely deployed areas. Simulation results show that our protocols can provide high coverage within a short deploying time and limited movement.
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INFOCOM - Movement-assisted Sensor Deployment
IEEE INFOCOM 2004, 1Co-Authors: Guiling Wang, Guohong Cao, T F La PortaAbstract:Sensor Deployment is an important issue in designing Sensor networks. We design and evaluate distributed self-Deployment protocols for mobile Sensors. After discovering a coverage hole, the proposed protocols calculate the target positions of the Sensors where they should move. We use Voronoi diagrams to discover the coverage holes and design three movement-assisted Sensor Deployment protocols, VEC (vector-based), VOR (Voronoi-based), and minimax based on the principle of moving Sensors from densely deployed areas to sparsely deployed areas. Simulation results show that our protocols can provide high coverage within a short deploying time and limited movement.
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MASS - Proxy-based Sensor Deployment for mobile Sensor networks
2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975), 1Co-Authors: Guiling Wang, Guohong Cao, T F La PortaAbstract:To provide satisfactory coverage is very important in many Sensor network applications such as military surveillance. In order to obtain the required coverage in harsh environments, mobile Sensors are helpful since they can move to cover the area not reachable by static Sensors. Previous work on mobile Sensor Deployment is based on a round by round process, where Sensors move iteratively until the maximum coverage is reached. Although these solutions can deploy mobile Sensors in a distributed way, the mobile Sensors may move in a zig-zag way and waste a lot of energy compared to moving directly to the final location. To address this problem, we propose a proxy-based Sensor Deployment protocol. Instead of moving iteratively, Sensors calculate their target locations based on a distributed iterative algorithm, move logically, and exchange new logical locations with their new logical neighbors. Actual movement only occurs when Sensors determine their final locations. Simulation results show that the proposed protocol can significantly reduce the energy consumption compared to previous work, while maintaining similar coverage.
Fethi Yazid Bouhidel - One of the best experts on this subject based on the ideXlab platform.
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Movement-Assisted Sensor Deployment Algorithms: A Survey and Taxonomy
IEEE Communications Surveys and Tutorials, 2015Co-Authors: Mustapha Reda Senouci, Khalid Asnoune, Abdelhamid Mellouk, Fethi Yazid BouhidelAbstract:One of the fundamental design issues in mobile wireless Sensor networks is how to design efficient movement-assisted Sensor Deployment algorithms that relocate the Sensor nodes in order to meet the desired performance goals. This survey focuses on a variety of movement-assisted Sensor Deployment algorithms that have been proposed and studied by researchers and highlights their strengths and limitations. The various models, assumptions, objectives, and constraints are identified, and the different formulations are enumerated. A taxonomy of movement-assisted Sensor Deployment algorithms that captures the fundamental differences among existing solutions is introduced. Six classes of approaches are identified, each one of them uses a specific principle to relocate the nodes from their initial position to a new target position. The proposed taxonomy is used to provide an exhaustive classification of existing approaches. For each identified class, various self-Deployment algorithms are discussed. Furthermore, comparisons between the different algorithms and also between the different classes are performed, therefore providing not only a complete view of the state-of-the-art but also useful insights for selecting the self-Deployment algorithm most appropriate to the application at hand. This paper also highlights open problems in this area of research.
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Movement‐assisted Sensor Deployment Algorithms: a Survey and Taxonomy
Communications Surveys and Tutorials IEEE Communications Society, 2015Co-Authors: Mustapha Reda Senouci, Abdelhamid Mellouk, K. Assnoune, Fethi Yazid BouhidelAbstract:One of the fundamental design issues in mobile wireless Sensor networks is how to design efficient movement-assisted Sensor Deployment algorithms that relocate the Sensor nodes in order to meet the desired performance goals. This survey focuses on a variety of movement-assisted Sensor Deployment algorithms that have been proposed and studied by researchers and highlights their strengths and limitations. The various models, assumptions, objectives, and constraints are identified, and the different formulations are enumerated. A taxonomy of movement-assisted Sensor Deployment algorithms that captures the fundamental differences among existing solutions is introduced. Six classes of approaches are identified, each one of them uses a specific principle to relocate the nodes from their initial position to a new target position. The proposed taxonomy is used to provide an exhaustive classification of existing approaches. For each identified class, various self-Deployment algorithms are discussed. Furthermore, comparisons between the different algorithms and also between the different classes are performed, therefore providing not only a complete view of the state-of-the-art but also useful insights for selecting the self-Deployment algorithm most appropriate to the application at hand. This paper also highlights open problems in this area of research.
Hamid Jafarkhani - One of the best experts on this subject based on the ideXlab platform.
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Movement-Efficient Sensor Deployment in Wireless Sensor Networks With Limited Communication Range
IEEE Transactions on Wireless Communications, 2019Co-Authors: Jun Guo, Hamid JafarkhaniAbstract:We study a mobile wireless Sensor network (MWSN) consisting of multiple mobile Sensors or robots. Three key factors in MWSNs, such as sensing quality, energy consumption, and connectivity, have attracted plenty of attention, but the interaction of these factors is not well studied. To take all the three factors into consideration, we model the Sensor Deployment problem as a constrained optimization problem. Our goal is to find an optimal Sensor Deployment (or relocation) to optimize the sensing quality with a limited communication range and a specific network lifetime constraint. We derive necessary conditions for the optimal Sensor Deployment in both homogeneous and heterogeneous MWSNs. According to our derivation, some Sensors are idle in the optimal Deployment of heterogeneous MWSNs. Using these necessary conditions, we design both the centralized and distributed algorithms to provide a flexible and explicit tradeoff between sensing uncertainty and network lifetime. The proposed algorithms are successfully extended to more applications, such as area coverage and target coverage, via properly selected density functions. The simulation results show that our algorithms outperform the existing relocation algorithms.
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Movement-efficient Sensor Deployment in Wireless Sensor Networks with Limited Communication Range
arXiv: Distributed Parallel and Cluster Computing, 2018Co-Authors: Jun Guo, Hamid JafarkhaniAbstract:We study a mobile wireless Sensor network (MWSN) consisting of multiple mobile Sensors or robots. Three key factors in MWSNs, sensing quality, energy consumption, and connectivity, have attracted plenty of attention, but the interaction of these factors is not well studied. To take all the three factors into consideration, we model the Sensor Deployment problem as a constrained source coding problem. %, which can be applied to different coverage tasks, such as area coverage, target coverage, and barrier coverage. Our goal is to find an optimal Sensor Deployment (or relocation) to optimize the sensing quality with a limited communication range and a specific network lifetime constraint. We derive necessary conditions for the optimal Sensor Deployment in both homogeneous and heterogeneous MWSNs. According to our derivation, some Sensors are idle in the optimal Deployment of heterogeneous MWSNs. Using these necessary conditions, we design both centralized and distributed algorithms to provide a flexible and explicit trade-off between sensing uncertainty and network lifetime. The proposed algorithms are successfully extended to more applications, such as area coverage and target coverage, via properly selected density functions. Simulation results show that our algorithms outperform the existing relocation algorithms.
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ICC - Movement-Efficient Sensor Deployment in Wireless Sensor Networks
2018 IEEE International Conference on Communications (ICC), 2018Co-Authors: Jun Guo, Hamid JafarkhaniAbstract:We study a mobile wireless Sensor network (MWSN) consisting of multiple mobile Sensors or robots. Two key issues in MWSNs - energy consumption, which is dominated by Sensor movement, and sensing coverage - have attracted plenty of attention, but the interaction of these issues is not well studied. To take both sensing coverage and movement energy consumption into consideration, we model the Sensor Deployment problem as a constrained source coding problem. Our goal is to find an optimal Sensor Deployment to maximize the sensing coverage with specific energy constraints. We derive necessary conditions to the optimal Sensor Deployment with (i) total energy constraint and (ii) network lifetime constraint. Using these necessary conditions, we design Lloyd-like algorithms to provide a trade-off between sensing coverage and energy consumption. Simulation results show that our algorithms outperform the existing relocation algorithms.
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Movement-efficient Sensor Deployment in Wireless Sensor Networks
arXiv: Information Theory, 2017Co-Authors: Jun Guo, Hamid JafarkhaniAbstract:We study a mobile wireless Sensor network (MWSN) consisting of multiple mobile Sensors or robots. Two key issues in MWSNs - energy consumption, which is dominated by Sensor movement, and sensing coverage - have attracted plenty of attention, but the interaction of these issues is not well studied. To take both sensing coverage and movement energy consumption into consideration, we model the Sensor Deployment problem as a constrained source coding problem. %, which can be applied to different coverage tasks, such as area coverage, target coverage, and barrier coverage. Our goal is to find an optimal Sensor Deployment to maximize the sensing coverage with specific energy constraints. We derive necessary conditions to the optimal Sensor Deployment with (i) total energy constraint and (ii) network lifetime constraint. Using these necessary conditions, we design Lloyd-like algorithms to provide a trade-off between sensing coverage and energy consumption. Simulation results show that our algorithms outperform the existing relocation algorithms.
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Sensor Deployment with limited communication range in homogeneous and heterogeneous wireless Sensor networks
IEEE Transactions on Wireless Communications, 2016Co-Authors: Jun Guo, Hamid JafarkhaniAbstract:We study the heterogeneous wireless Sensor networks (WSNs) and propose the necessary condition of the optimal Sensor Deployment. Similar to that in homogeneous WSNs, the necessary condition implies that every Sensor node location should coincide with the centroid of its own optimal sensing region. Moreover, we discuss the dynamic Sensor Deployment in both the homogeneous and the heterogeneous WSNs with limited communication range for the Sensor nodes. The purpose of Sensor Deployment is to improve sensing performance, reflected by distortion and coverage. We model the Sensor Deployment problem as a source coding problem with distortion reflecting sensing accuracy. However, when the communication range is limited, a WSN is divided into several disconnected sub-graphs under certain conditions as we will discuss in this paper. In such a scenario, neither the conventional distortion nor the coverage represents the sensing performance as the collected data in disconnected sub-graphs cannot be communicated with the access point. By defining an appropriate sensing performance measure, we propose a Restrained Lloyd (RL) algorithm and a deterministic annealing (DA) algorithm to optimize Sensor Deployment in both the homogeneous and heterogeneous WSNs. Our simulation results show that both the DA and the RL algorithms outperform the existing algorithms when communication range is limited.
