Reconfiguration methods for mobile sensor networks
- 1 October 2007
- journal article
- Published by Association for Computing Machinery (ACM) in ACM Transactions on Sensor Networks
- Vol. 3 (4), 22
- https://doi.org/10.1145/1281492.1281497
Abstract
Motion may be used in sensor networks to change the network configuration for improving the sensing performance. We consider the problem of controlling motion in a distributed manner for a mobile sensor network for a specific form of motion capability. Mobility itself may have a high resource overhead, hence we exploit motility , a constrained form of mobility, which has very low overheads but provides significant reconfiguration potential. We present an architecture that allows each node in the network to learn the medium and phenomenon characteristics. We describe a quantitative metric for sensing performance that is concretely tied to real sensor and medium characteristics, rather than assuming an abstract range based model. The problem of determining the desirable network configuration is expressed as an optimization of this metric. We present a distributed optimization algorithm which computes a desirable network configuration, and adapts it to environmental changes. The relationship of the proposed algorithm to simulated annealing and incremental subgradient descent based methods is discussed. A key property of our algorithm is that convergence to a desirable configuration can be proved even though no global coordination is involved. A network protocol to implement this algorithm is discussed, followed by simulations and experiments on a laboratory test bed.Keywords
This publication has 18 references indexed in Scilit:
- Parallel and Serial Neural Mechanisms for Visual Search in Macaque Area V4Science, 2005
- Stability Analysis of Social Foraging SwarmsIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2004
- Distributed attention in large scale video sensor networksPublished by Institution of Engineering and Technology (IET) ,2004
- Event-based motion control for mobile-sensor networksIEEE Pervasive Computing, 2003
- Algorithms for cooperative multisensor surveillanceProceedings of the IEEE, 2001
- An active testing model for tracking roads in satellite imagesIeee Transactions On Pattern Analysis and Machine Intelligence, 1996
- OPTIMUM GUARD COVERS AND m-WATCHMEN ROUTES FOR RESTRICTED POLYGONSInternational Journal of Computational Geometry & Applications, 1993
- Optimum watchman routesInformation Processing Letters, 1988
- A short proof of Chvátal's Watchman TheoremJournal of Combinatorial Theory, Series B, 1978
- A combinatorial theorem in plane geometryJournal of Combinatorial Theory, Series B, 1975