A Path Forming Method for Water Surface Mobile Sink Using Voronoi Diagram and Dominating Set

Xia, Na; Wang, Chu; Yu, Yi; Du, Huazheng; Xu, Chaonong; Zheng, Jianguo

doi:10.1109/tvt.2018.2832096

Cited by 15 publications

(2 citation statements)

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“…Thus, general equations of lines L 1 and L 2 are shown in Equation 14and Equation 15, respectively. Then, Equation 18(i.e., the straight line L 3 ) is obtained by subtraction of Equation (16) and Equation (17). Through L 1 and L 3 , the location of k 1 can be obtained, as is shown in Equation (19).…”

Section: A Selection Of Potential Visiting Pointsmentioning

confidence: 99%

“…In early studies, the mobile sink collects data from sensor nodes individually [12], [13], but it will lead to a high delay in data delivery due to the long trajectory of the mobile sink, especially in large-size sensor networks. To tackle this problem, most current studies only allow the mobile sink to collect data from some of nodes called rendezvous nodes (RNs) and non-RN nodes transmit data via RNs [14]- [16]. The selection of RNs is a challenging issue.…”

Section: Introductionmentioning

confidence: 99%

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Energy-Efficient Trajectory Planning Algorithm Based on Multi-Objective PSO for the Mobile Sink in Wireless Sensor Networks

Yang

2019

IEEE Access

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In wireless sensor networks (WSNs), collecting data with mobile sinks is an effective way to solve the ''energy hole problem''. However, most of existing algorithms of mobile sinks ignore the load balance of rendezvous nodes, which will significantly shorten the network lifetime. Moreover, most mobile sinks are usually required to visit locations of sensor nodes without taking advantage of their communication ranges. Therefore, this paper proposes an energy-efficient trajectory planning algorithm (EETP) based on multi-objective particle swarm optimization (MOPSO) to shorten the trajectory length of the mobile sink and balance the load of rendezvous nodes. EETP aims to reduce the delay in data delivery and prolong the network lifetime. To shorten the trajectory length of the mobile sink, we design a mechanism to select potential visiting points within communication overlapping ranges of sensor nodes, rather than locations of sensor nodes. Additionally, according to trajectory characteristics of the mobile sink, we design an effective trajectory encoding method that can generate a trajectory containing an unfixed number of visiting points. The simulation results show that the proposed EETP is superior to existing WRP, CB and the MOPSO-based algorithm, in terms of delay in data delivery, network lifetime and energy consumption. INDEX TERMS Mobile sink, MOPSO, load balance of rendezvous nodes, trajectory planning.

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Section: A Selection Of Potential Visiting Pointsmentioning

confidence: 99%