Low-complexity algorithms for event detection in wireless sensor networks

To ensure that a multi-hop cluster of batterypowered, wireless sensor motes can complete all of its tasks, each task must minimize its use of communication and processing resources. For event detection tasks that are subject to both measurement errors by sensors and communication errors in the wirel...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE journal on selected areas in communications Ročník 28; číslo 7; s. 1138 - 1148
Hlavní autoři: Xusheng Sun, Coyle, E J
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.09.2010
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Clustering algorithms
Clusters
Decisions
Detectors
distributed detection
energy
Error analysis
Error detection
Error probability
Fuses
Relays
Sensor networks
Sensors
Spread spectrum communication
Studies
Tasks
Wireless communication
Wireless sensor networks
ISSN:0733-8716, 1558-0008
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:To ensure that a multi-hop cluster of batterypowered, wireless sensor motes can complete all of its tasks, each task must minimize its use of communication and processing resources. For event detection tasks that are subject to both measurement errors by sensors and communication errors in the wireless channel, this implies that: (i) the Cluster-Head (CH) must optimally fuse the decisions received from its cluster in order to reduce the effect of measurement errors; (ii) the CH and all motes that relay other motes' decisions must adopt lowcomplexity processing and coding algorithms that minimize the effects of communication errors. This paper combines a Maximum a Posteriori (MAP) approach for local and global decisions in multi-hop sensor networks with low-complexity repetition codes and processing algorithms. It is shown by analysis and confirmed by simulation that there exists an odd integer M and an integer K M such the decision error probability at the CH is reduced when: (1) nodes in rings k ≤ K M hops from the CH directly relay their decisions to the CH; (2) nodes in rings k > K M locally fuse groups of M decisions and then use a repetition code to forward these fused decisions to the CH; and (3) K M is a nondecreasing function of M. This algorithm - and hybrid, hierarchical, and compression approaches based on it - enable tradeoffs amongst the probability of error, energy usage, compression ratio, complexity, and time to decision.
Bibliografie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
content type line 23
ISSN:0733-8716
1558-0008
DOI:10.1109/JSAC.2010.100918