Delivery latency minimization in wireless sensor networks with mobile sink

Adopting mobile data gathering in wireless sensor networks (WSNs) can reduce the energy consumption on data forwarding thus achieve more uniform energy consumption among sensor nodes. However, the data delivery latency inevitable increases in mobile data gathering due to the travel of the mobile sin...

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Vydáno v:2015 IEEE International Conference on Communications (ICC) s. 6481 - 6486
Hlavní autoři: Jiqiang Tang, Songtao Guo, Yuanyuan Yang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2015
Témata:
Ad hoc networks
Complexity theory
delivery latency minimization
Heuristic algorithms
Mobile communication
Mobile computing
mobile sink
Schedules
substitution heuristic algorithm
Wireless sensor networks
ISSN:1550-3607
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Shrnutí:Adopting mobile data gathering in wireless sensor networks (WSNs) can reduce the energy consumption on data forwarding thus achieve more uniform energy consumption among sensor nodes. However, the data delivery latency inevitable increases in mobile data gathering due to the travel of the mobile sink. In this paper, we consider a delivery latency minimization problem (DLMP) in a randomly deployed WSN. To solve this problem, we first select the traversed anchor points on the border of the communication range of sensor nodes to shorten the travel route, and then let the mobile sink move and collect data at the same time to reduce the travel time. In addition, we also employ the time division approach to traverse the sensor nodes whose signals cover the same travel segments. We formulate the DLMP as an integer programming problem which subjects to the direct access constraint, the data transmission constraint and the route traverse constraint. We prove that the DLMP is an NP-Complete (NPC) problem. To solve the NPC problem, we propose a substitution heuristic algorithm, a traveling salesman problem (TSP) heuristic algorithm and a random heuristic algorithm. We conduct extensive simulations to evaluate the performance of the proposed algorithms, and the results show that all the three algorithms can shorten the data delivery latency in mobile data gathering, with the substitution heuristic algorithm being the most effective one.
ISSN:1550-3607
DOI:10.1109/ICC.2015.7249357