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NSDI '04 — Abstract
Pp. 15–28 of the Proceedings
Trickle: A Self-Regulating Algorithm for Code Propagation and Maintenance in Wireless Sensor Networks
Best Paper!
Philip Levis, University of California, Berkeley, and Intel Research Berkeley; Neil Patel, University of California, Berkeley; David Culler, University of California, Berkeley, and Intel Research Berkeley; Scott Shenker, University of California, Berkeley, and ICSI
Abstract
We present Trickle, an algorithm for propagating and maintaining code updates in wireless sensor networks. Borrowing techniques from the epidemic/gossip, scalable multicast, and wireless broadcast literature, Trickle uses a "polite gossip" policy, where motes periodically broadcast a code summary to local neighbors but stay quiet if they have recently heard a summary identical to theirs. When a mote hears an older summary than its own, it broadcasts an update. Instead of flooding a network with packets, the algorithm controls the send rate so each mote hears a small trickle of packets, just enough to stay up to date. We show that with this simple mechanism, Trickle can scale to thousand-fold changes in network density, propagate new code in the order of seconds, and impose a maintenance cost on the order of a few sends an hour.
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