Energy-collision-aware Minimum Latency Aggregation Scheduling for Energy-harvesting Sensor Networks

The emerging energy-harvesting technology enables charging sensor batteries with renewable energy sources, which has been effectively integrated into Wireless Sensor Networks (EH-WSNs). Due to the limited energy-harvesting capacities of tiny sensors, the captured energy remains scarce and differs greatly among nodes, which makes the data aggregation scheduling problem more challenging than that in energy-abundant WSNs. In this article, we investigate the Minimum Latency Aggregation Scheduling (MLAS) problem in EH-WSNs. First, we identify a new kind of collision in EH-WSNs, named as energy-collision, and design several special structures to avoid it during data aggregation. To reduce the latency, we try to choose the parent adaptively according to nodes' transmission tasks and energy-harvesting ability, under the consideration of collisions avoidance. By considering transmitting time, residual energy, and energy-collision, three scheduling algorithms are proposed under protocol interference model. Under physical interference model, several approximate algorithms are also designed by taking account of the interference from the nodes several hops away. Finally, the theoretical analysis and simulation results verify that the proposed algorithms have high performance in terms of latency.

Automated summary

This article investigates the Minimum Latency Aggregation Scheduling (MLAS) problem in EH-WSNs and identifies a new type of collision called energy-collision. Several special structures are designed to avoid it during data aggregation. Three scheduling algorithms are proposed under the protocol interference model, and several approximate algorithms are designed under the physical interference model to improve performance.