An autonomous framework for supporting energy efficiency and communication reliability in WSNs

We propose a novel decentralized and self-learning framework to support both communication reliability and energy-efficiency for periodic traffic applications in WSNs. Our autonomous framework comprises three main components: estimation and identification of multi-flow traffic, dynamic multi-flow wakeup scheduling, and asynchronous channel hopping. With asynchronous channel hopping the frequency hopping pattern is determined by each source node autonomously, and forwarders have to identify and follow the pattern. We also propose a light and efficient controller to eliminate the collision caused by multiflow overlap at forwarders. We present design and evaluation of our autonomous framework using real world measurements, and realistic trace-based simulation. The results show that our asynchronous channel hopping solution improves the packet reception rate compared to the single channel solutions without the need of an expensive signaling and time synchronization overhead. We also show that with this scheme the average energy consumption yields a ≈50% lower than the single channel solutions. This paper is to the best our knowledge, the first to explore channel hopping without maintaining a tight time synchronization protocol.