A novel two-phase energy efficient load balancing scheme for efficient data collection for energy harvesting WSNs using mobile sink

This paper studies data collection schedule for energy harvesting wireless sensor networks (EHWSNs) using an autonomous vehicle called mobile sink (MS). The MS collects data while moving on a path from the nearby sensors called sub-sinks. The remaining sensors forward their data to the MS through the sub-sinks. However, the data collection throughput using the MS based data collection is relatively low. Efficient distribution of data among the sub-sinks and efficient data collection schedule are leveraged to improve the data collection throughput. A novel two-phase data distribution algorithm using a minimum cost network flow technique is proposed for efficient distribution of data. It helps to minimize idle time of the MS during data collection as well as improves the data accumulation at the sub-sinks. A novel adaptive data collection schedule is proposed for collecting the data from the sub-sinks. Finally, the performance of the proposed algorithm is compared with two existing solutions. It reveals that the two-phase data distribution algorithm together with the data collection schedule improves the data collection throughput by 20-25%. Moreover, it also significantly improves total data collection and preserves the energy efficiency and energy neutrality of the energy harvesting rechargeable sensors.