On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks

Yu, Jiguo; Chen, Ying; Ma, Liran; Huang, Baogui; Cheng, Xiuzhen

doi:10.3390/s16010104

Cited by 44 publications

(17 citation statements)

References 28 publications

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“…By studying the above network model, it can be determine that in order to realize mutual communication between network links, it is necessary to detect each other within the transmission distance of the network node and the carrier sense distance [16,17]. To calculate the transmission distance of each node, we need to calculate the maximum range of the generating node and receiving node.…”

Section: Node Transmission Distance Calculationmentioning

confidence: 99%

Energy-balance node-selection algorithm for heterogeneous wireless sensor networks

Khan

Singh

2018

ETRI Journal

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To solve the problem of unbalanced loads and the short network lifetime of heterogeneous wireless sensor networks, this paper proposes a node‐selection algorithm based on energy balance and dynamic adjustment. The spacing and energy of the nodes are calculated according to the proximity to the network nodes and the characteristics of the link structure. The direction factor and the energy‐adjustment factor are introduced to optimize the node‐selection probability in order to realize the dynamic selection of network nodes. On this basis, the target path is selected by the relevance of the nodes, and nodes with insufficient energy values are excluded in real time by the establishment of the node‐selection mechanism, which guarantees the normal operation of the network and a balanced energy consumption. Simulation results show that this algorithm can effectively extend the network lifetime, and it has better stability, higher accuracy, and an enhanced data‐receiving rate in sufficient time.

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Section: Node Transmission Distance Calculationmentioning

confidence: 99%

Energy-balance node-selection algorithm for heterogeneous wireless sensor networks

Khan

Singh

2018

ETRI Journal

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“…Further, they presented two distributed heuristics: the energy efficiency first scheme (EEFS) and remaining energy first scheme (REFS). In [56], authors have proposed a centralized algorithm called CCTC and a distributed algorithm called DCTC for connected targetcoverage problem in heterogeneous WSNs. Both algorithms construct connected cover sets to achieve connectivity and coverage in an energy efficient way.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Fault Tolerant Coverage in Wireless Sensor Networks

Henna

2017

Journal of Sensors

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Energy efficiency and fault tolerance are two of the major concerns in wireless sensor networks (WSNs) for the target coverage. Design of target coverage algorithms for a large scale WSNs should incorporate both the energy efficiency and fault tolerance. In this paper, we study the coverage problem where the main objective is to construct two disjoint cover sets in randomly deployed WSNs based on relay energy (Erelay). Further, we present an approximation algorithm called Energy Efficient Maximum Disjoint Coverage (EMDC) with provable approximation ratios. We analyze the performance of EMDC theoretically and also perform extensive simulations to demonstrate the effectiveness of EMDC in terms of fault tolerance and energy efficiency.

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“…However, the authors do not describe how nodes should collaborate to maintain the coverage. Though centralized and distributed connected target K -coverage algorithms for the heterogeneous wireless sensor networks are proposed in [ 23 ], there is no scheduling mechanism to improve the network lifetime and to maintain the target coverage. A genetic algorithm-based sensor deployment algorithm is designed in [ 24 ] to increase the coverage of the homogeneous WSN.…”

Section: Related Workmentioning

confidence: 99%

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

Sahoo

Thakkar

Hwang

2017

Sensors

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The K-coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K-covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) and Self-Organized K-coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized.

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On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks

Cited by 44 publications

References 28 publications

Energy-balance node-selection algorithm for heterogeneous wireless sensor networks

Energy-balance node-selection algorithm for heterogeneous wireless sensor networks

Energy Efficient Fault Tolerant Coverage in Wireless Sensor Networks

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

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