Augmented conflict-free Scheduling for low power WSNs

With the buzz of Internet of Things (IoT), the low power sensor are getting deployed on large scale in applications such as industrial monitoring, smart homes and e-health. For the reason that the sensor devices are battery operated, though the round-robin based Time Division Multiple Access (TDMA) scheduling is the best choice for its high energy and throughput efficiency, the performance degrades as the network scales because of longer frame duration. We address this problem by modelling the network as a tree with interfering links corresponding to the number of devices. We propose a network partitioning approach to reduce these interfering links by extending the tree to a second level. The first level interfering links correspond to optimizing the frame duration where as the second level interfering links correspond to improving the slot utilization. We show that forming this two-level tree is an NP-complete problem by formulating it as a conflict graph. We then propose two polynomial-time algorithms to address offline and online slot allocation requests that resolve these conflicts efficiently by introducing the so called virtual interference links. We illustrate the performance benefits of our proposed algorithms over the conventional round-robin scheduling in terms of improved throughput, scalability and delay.