Rapid Convergecast on Commodity Hardware: Performance Limits and Optimal Policies

The increased industrial interest in wireless sensor networks demands a shift from optimizing protocols for energy-efficient reporting of sporadic events to developing solutions for high-rate real-time data collection and dissemination. We study time-optimal convergecast under the communication constraints of commodity sensor network platforms, and propose a novel convergecast model in which packet copying between the microcontroller and the radio transceiver is separated from packet transmission, thereby improving channel utilization and system throughput. Based on this model, we establish tight lower bound on the number of time slots for convergecast in networks with tree routing topology, and present both centralized and distributed algorithms for generating time-optimal convergecast schedules. Our scheme is also memory-efficient as each node needs to buffer at most one packet at any time. We evaluate our scheme in simulation and on real hardware, and show that our scheme can achieve a throughput of 203 kbit/s (86.4% of the theoretical upper bound) and up to 86.24% improvement compared with traditional TDMA-based convergecast. With optimal routing tree and maximum MAC layer payload, convergecast in a network with 20 sensor nodes can be completed in only 100 ms.