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Conference proceeding
Using Virtual Markets to Program Global Behavior in Sensor Networks
EW 11: Proceedings of the 11th workshop on ACM SIGOPS European workshop
2004
Abstract
This paper presents market-based macroprogramming (MBM), a new paradigm for achieving globally efficient behavior in sensor networks. Rather than programming the individual, low-level behaviors of sensor nodes, MBM defines a virtual market where nodes sell "actions" (such as taking a sensor reading or aggregating data) in response to global price information. Nodes take actions to maximize their own utility, subject to energy budget constraints. The behavior of the network is determined by adjusting the price vectors for each action, rather than by directly specifying local node actions, resulting in a globally efficient allocation of network resources. We present the market-based macro-programming paradigm, as well as several experiments demonstrating its value for a sensor network vehicle tracking application.
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29 citations in Scopus
Details
- Title
- Using Virtual Markets to Program Global Behavior in Sensor Networks
- Creators
- Geoffrey Bruce Mainland - Harvard University PressLaura Kang - Harvard University PressSébastien Lahaie - Harvard University PressDavid C Parkes - Harvard University PressMatthew D Welsh
- Publication Details
- EW 11: Proceedings of the 11th workshop on ACM SIGOPS European workshop
- Publisher
- Association for Computing Machinery
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Scopus ID
- 2-s2.0-77951476054
- Other Identifier
- 991021868090304721