Energy Efficient Network Reconfiguration for Mostly-Off Sensor Networks

A new class of sensor network applications are mostly off. Exemplified by Intel\´s FabApp, in these applications the network alternates between being off for hours or weeks, then activating to collect data for a few minutes. While configuration of traditional sensornet applications is occasional and so need not be optimized, these applications may spend half their time while awake configuring, so they require new approaches to quickly restart after a long downtime, in effect, "sensor network suspend and resume". While there are many network services that may need to be restarted, this paper focuses on the key question of when the network can determine that all nodes are now awake and ready to interact. Current resume approaches assume worst-case clock drift and so must conservatively take minutes to reconfigure after a month-long sleep. We propose two energy efficient reconfiguration protocols to address this challenge. The first approach is low-power listening with flooding, where the network restarts quickly by flooding a control message as soon as one node can determine the whole network is up. The second protocol uses local update with suppression, where nodes only notify their one-hop neighbors about the network state, avoiding the cost of flooding. Both protocols are fully distributed algorithms. Through analysis and simulations, we show that both protocols are more energy efficient than current approaches. Flooding works best in sparse networks with 6 neighbors or less, while local update with suppression works best in dense networks (more than 6 neighbors)