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This paper discusses a novel self-regulating algorithm called Trickle, designed to optimize code propagation and maintenance in wireless sensor networks. Key features include load distribution analysis, packet transmission patterns, and empirical studies on mote communication. The algorithm's gossip interval (τ) is pivotal in managing overhead, balancing rapid propagation with minimized delays. An innovative implementation allows users to create virtual machines on TinyOS, ensuring efficient routine updates with minimal data overhead. The Trickle algorithm significantly improves network efficiency while maintaining optimal resource use.
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Trickle: A Self-Regulating Algorithm for Code Propagation and Maintenance in Wireless Sensor Networks Sections 4.4, 4.5, 5, and 5.1
Load Distribution • Which Motes are sending/Receiving Packets? • Evenly Distributed? Random Pattern
Empirical Study • Motes on a small table • Low transmission signal strength (multi-hop) • Results: Similar to scaling by TOSSIM-bit (should it have compare TOSSIM-packet?) • Redundancy of 1.1 vs. 1.3 (very close)
Propagation • Gossip interval (τ) determines overhead • High τ value means fewer broadcasts; higher delay • Low τ value means more broadcasts; lower delay • Dynamic Scaling of τ • Lower/upper bounds • When τ expires, double it; otherwise reset it • Best of both worlds: • rapid propagation • Low overhead
Trickle Pseudocode • When There’s Nothing New to Say, Gossip Infrequently
Mate, a Trickle Implementation • Allows users to build VMs on TinyOSsesnors • Language + Events + Primitives • Each routine is within 30 bytes • Vector used to keep track of routines • Trickle Implementation: When mote hears an old Vector, it rebroadcasts newer routines three times
