Chaos: Versatile and Efficient All-to-All Data Sharing and In-Network Processing at Scale
Paper in proceeding, 2013

An important building block for low-power wireless systems is to efficiently share and process data among all devices in a network. However, current approaches typically split such all-to-all interactions into sequential collection, processing, and dissemination phases, thus handling them inefficiently. We introduce Chaos, the first primitive that natively supports all-to-all data sharing in low-power wireless networks. Different from current approaches, Chaos embeds programmable in-network processing into a communication support based on synchronous transmissions. We show that this design enables a variety of common all-to-all interactions, including network-wide agreement and data aggregation. Results from three testbeds and simulations demonstrate that Chaos scales efficiently to networks consisting of hundreds of nodes, achieving severalfold improvements over LWB and CTP/Drip in radio duty cycle and latency with almost 100 % reliability across all scenarios we tested. For example, Chaos computes simple aggregates, such as the maximum, in a 100-node multi-hop network within less than 90 milliseconds.


Olaf Landsiedel

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Federico Ferrari

Swiss Federal Institute of Technology in Zürich (ETH)

Marco Zimmerling

Swiss Federal Institute of Technology in Zürich (ETH)

SenSys '13: Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems

978-1-4503-2027-6 (ISBN)

Areas of Advance

Information and Communication Technology


Subject Categories

Computer Science





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