Time Efficient Data Collection With Mobile Sink and vMIMO Technique in Wireless Sensor Networks

Data collection is a fundamental yet challenging task of wireless sensor networks 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 multiple-input multiple-output (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 tradeoff between full utilization of concurrent uploading of vMIMO and the shortest moving tour of a mobile sink, the proposed algorithm combines the amount of concurrent uploaded data, the number of neighbors, 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.