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Data gathering via mobile sink in WSNs using game theory and enhanced ant colony optimization

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Abstract

Optimal performance and improved lifetime are the most desirable design benchmarks for WSNs and the mechanism for data gathering is a major constituent influencing these standards. Several researchers have provided significant evidence on the advantage of mobile sink (MS) in performing effective gathering of relevant data. However, determining the trajectory for MS is an NP-hard-problem. Especially in delay-inevitable applications, it is challenging to select the best-stops or rendezvous points (RPs) for MS and also to design an efficient route for MS to gather data. To provide a suitable solution to these challenges, we propose in this paper, a game theory and enhanced ant colony based MS route selection and data gathering (GTAC-DG) technique. This is a distributed method of data gathering using MS, combining the optimal decision making skill of game theory in selecting the best RPs and computational swarm intelligence of enhanced ant colony optimization in choosing the best path for MS. GTAC-DG helps to reduce data transfer and management, energy consumption and delay in data delivery. The MS moves in a reliable and intelligent trajectory, extending the lifetime and conserving the energy of WSN. The simulation results prove the effectiveness of GTAC-DG in terms of metrics such as energy and network lifetime.

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Correspondence to Ahmed M. Khedr.

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Raj, P.V.P., Khedr, A.M. & Aghbari, Z.A. Data gathering via mobile sink in WSNs using game theory and enhanced ant colony optimization. Wireless Netw (2020) doi:10.1007/s11276-020-02254-x

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Keywords

  • Ant colony optimization (ACO)
  • Data gathering (DG)
  • Game theory (GT)
  • Rendezvous points (RPs)
  • Mobile sink (MS) trajectory
  • Wireless sensor network (WSN)