Abstract
Data collection is a fundamental yet challenging task of Wireless Sensor Networks (WSN) to support a variety of applications, due to the inherent distinguish characteristics for sensor networks, such as limited energy supply, self-organizing deployment and QoS requirements for different applications. Mobile sink and virtual MIMO (vMIMO) techniques can be jointly considered to achieve both time efficient and energy efficient for data collection. In this paper, we aim to minimize the overall data collection latency including both sink moving time and sensor data uploading time. We formulate the problem and propose a multihop weighted revenue (MWR) algorithm to approximate the optimal solution. To achieve the trade-off between full utilization of concurrent uploading of vMIMO and the shortest moving tour of mobile sink, the proposed algorithm combines the amount of concurrent uploaded data, the number of neighbours, and the moving tour length of sink in one metric for polling point selection. The simulation results show that the proposed MWR effectively reduces total data collection latency in different network scenarios with less overall network energy consumption.