Multi-sink data aggregation routing and scheduling with dynamic radii in WSNs

In wireless sensor networks (WSNs) with multiple sink nodes, energy is wasted on idle listening, redundant transmissions, and unnecessary power consumption. The total energy consumption may be minimized by properly scheduling communications in conjunction with aggregating data and dynamically adjusting radii. We propose near-optimal data aggregation routing and duty cycle scheduling heuristics, denoted by MDAR and O-MAC, which achieve energy efficiency and bound latency within a reasonable range. These heuristics outperform other general data aggregation routing heuristics (e.g., CNS, GIT, and SPT) and scheduling protocols (e.g., S-MAC and T-MAC) by 7%-45%, according to our experimental results.