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Coverage and connectivity based lifetime maximization with topology update for WSN in smart grid applications

2022    Serper, Elif Zeynep; Altin-Kayhan, Aysegul

The self-sufficient Smart Grid (SG) with two-way data communication among its constituents is proposed as a remedy to the shortcomings of the traditional power grid. Due to their low cost and ease of deployment along with the advanced communication capabilities they offer, WSNs are seen as an important technology for SG applications. To this end, it is important to design energy-efficient communication protocols to achieve a long network lifetime while maintaining the desired coverage level. In this paper, we consider the case where the transmission paths are re-adapted to topology changes as long as the required coverage level and connectivity to the base station can be maintained with the current set of sensors with positive residual energy. We first propose a novel 0-1 mixed-integer programming (MIP) model, and then present two alternative 0-1 MIP models opti-mizing the network behavior in unit time decomposition with an emphasis on energy consumption. Our study is unique in terms of including topology adaptation due to energy depletion within a holistic solution framework based on optimization methods. We avoid the traditional time until the first sensor dies metric and allow the WSN to continue to function optimally as long as the predetermined coverage level and connectivity to the BS can be achieved with the remaining sensors. We observe that network lifetime can be increased significantly even after a one-time reorganization. Moreover, we analyze how the solutions of the three models differ in terms of lifetime and coverage level. As a side contribution, we show that maximizing the time until the first sensor dies is equivalent to minimizing the energy consumption of the most used sensor for the classical single-period problem, which is not necessarily true when there is an adaptation to a topology change. Hence, we provide a practical tool to determine the theoretical upper bound on the network lifetime with coverage and connectivity-based QoS requirements.