Energy-aware mobile sink visiting nodes selection using a mean-shift clustering strategy for data accumulation in WSNs

Guduri Sulakshana () and Govardhan Reddy Kamatam ()
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Guduri Sulakshana: Jawaharlal Nehru Technological University – Ananthapuramu (JNTUA)
Govardhan Reddy Kamatam: Department of Computer Science and Engineering, G. Pulla Reddy Engineering College

Telecommunication Systems: Modelling, Analysis, Design and Management, 2023, vol. 84, issue 2, No 5, 215-233

Abstract: Abstract In Wireless Sensor Networks (WSNs), the energy-hole problem is challenging because it isolates the base station and disrupts the data accumulation process. A mobile sink is introduced to mitigate this issue, and it is used to accumulate packets from the Sensor Nodes (SNs) in a WSN instead of traditional routing methods. However, visiting each SN in the network is a time-consuming task and increases the mobile sink traveling distance, which further results in a longer delay in transmitting data. By choosing selective visiting points (VP) to gather SNs data, the SNs can send their data to their nearest VP. Nevertheless, finding such optimized and top-performing VPs in WSNs is challenging. It is more challenging to construct a tour among them with a low computational complexity. In this context, we proposed a Mean-Shift Clustering-based VP selection (MSCVP) algorithm to determine the efficient VPs out of the randomly deployed SNs. Next, we construct a near-optimal tour among the VPs with a linear time complexity using a computational geometric strategy to accumulate the data from the VPs. We simulate and test run the proposed MSCVP approach with the existing approaches and evaluate various metrics under different scenarios. We noted improved performance of the MSCVP over the existing works and noticed a decrease in computational complexity.

Keywords: Wireless sensor networks; Data accumulation; Mean-shift clustering; Mobile sink path selection; Network lifetime; Computational geometry (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11235-023-01038-w

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