Maximizing throughput for low duty-cycled sensor networks

Sensing and communication are foundations of the Internet of Things(IoT). Although energy efficiency is an important issue in MAC protocol design for general energy limited sensor networks, throughput is non trivial for some specific sensor networks. In this paper, we propose a new duty cycling scheme called MaxPut that can maximize throughput without sacrificing energy efficiency through the appropriate combination of random and scheduled duty cycling schemes. MaxPut attempts to identify risky nodes and enables risky nodes to maximize the utilization of active periods of their neighbors such that MaxPut can avoid potential buffer overflow due to aggregation of bursty data. We obtain overall throughput in networks with homogeneous and heterogeneous event occurrence processes respectively. Further, we compare MaxPut against a fully random duty cycling scheme. The simulation results show that MaxPut outperforms prior work with respect to the network throughput, while energy consumption is almost equivalent to the existing duty cycling scheme.