High Performance Sleep-Wake Sensor Systems Based on Cyclic Cellular Automata

Our contribution in this paper is a scalable, easily implemented, self-organizing, energy conserving intrusion-detection sensor system applying concepts from cellular automata theory. The system self-assembles periodic wake-sensor barriers (waves) that sweep the sensor field; it is highly effective...

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Vydáno v:Information Processing in Sensor Networks; Proceedings: International Conference on Information Processing in Sensor Networks, 2008: St. Louis, MO s. 517 - 526
Hlavní autoři: Baryshnikov, Y. M., Coffman, E. G., Kwak, K. J.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Washington, DC, USA IEEE Computer Society 22.04.2008
IEEE
Edice:ACM Conferences
Témata:
Automata
Biological system modeling
Computer systems organization > Architectures > Parallel architectures > Cellular architectures
Computer systems organization > Dependable and fault-tolerant systems and networks
Costs
cyclic cellular automata
Event detection
General and reference > Cross-computing tools and techniques > Performance
Hardware > Communication hardware, interfaces and storage > Signal processing systems
Hardware > Emerging technologies > Quantum technologies > Quantum dots and cellular automata
intruder detection
Logic
Networks > Network performance evaluation
Performance loss
Protocols
self-organizing
Sensor phenomena and characterization
Sensor systems
Sleep schedule
Theory of computation > Models of computation
Wireless sensor networks
self-organizing
cyclic cellular automata
intruder detection
Sleep schedule
ISBN:9780769531571, 0769531571
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Popis
Shrnutí:Our contribution in this paper is a scalable, easily implemented, self-organizing, energy conserving intrusion-detection sensor system applying concepts from cellular automata theory. The system self-assembles periodic wake-sensor barriers (waves) that sweep the sensor field; it is highly effective even in the case of frequent communication failures, sensor failures, large obstacles, and when intruders know sensor locations.
ISBN:9780769531571
0769531571
DOI:10.1109/IPSN.2008.14