Energy- and Delay-Efficient Algorithm for Large-Scale Data Collection in Mobile-Sink WSNs

This paper deals with the problem of large-scale data collection in wireless sensor networks equipped with multiple multi-interface mobile sinks. Employing mobile sinks for data collection leads to a trade-off between energy consumption and delay. We propose a new algorithm called “Data Gathering with Multi-interface Mobile Sink (DGM
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S)” to reduce both energy consumption and delay in the network. DGM
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S considers delays due to sink mobility and sink stopping for receiving the aggregated data from Cluster Heads (CHs). The proposed scheme partitions the network into smaller sub-areas, where in each sub-area, an appropriate trajectory is determined for the corresponding sink. In each partition, DGM
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S uses an Energy- and Delay-efficient Polling point Selection (EDPS) strategy to determine data of which CHs should be collected at different points of the corresponding sink tour. EDPS considers path loss and shadowing phenomena, as well as the considerations for delay and energy consumption. As another advantage, DGM
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S employs a scheduling mechanism to make the best use of the multi-interface technology in collecting data of CHs at each polling point. Extensive simulations are conducted to illustrate the advantages of the proposed DGM
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S algorithm in terms of energy consumption, delay, network’s lifetime, and time complexity.