NDLI: A Dynamic-cluster Energy-aware Routing Algorithm Based on Neural Structure in the Wireless Sensor Networks

Content Provider	IEEE Xplore Digital Library
Author	Guo Bin Li Zhe Wei Ze-Jun
Copyright Year	2005
Description	Author affiliation: Sch. of Inf. Sci. & Eng., Northeastern Univ., ShenYang (Guo Bin; Li Zhe; Wei Ze-Jun)
Abstract	The function of neural network of human beings is quite similar to that of the sensor network, which is a cluster of firmly related individual units performing a special function. According to the architecture of neural network, a dynamic-cluster energy-aware routing algorithm (DCEAR) has been proposed in this paper. The nodes on the network have adopted an active routing based on event awaking. Firstly, the event data dynamically elects a temporary cluster-header. Then the temporary cluster-header handles all the data it receives, and the handled data reflects the general instance of the region. In this way it has decreased the information that has to be forwarded and has reduced the energy consumption of the entire network. The backbone of the network is originated by genetic-tree algorithm. It will timely update the trunk of the genetic-tree in order to trade off the energy consumption of the whole network. So it has prolonged the lifetime of the network greatly. The result of our simulation indicates that it is a quite effective energy saving routing algorithm
Sponsorship	Univ. of Aizu, Japan Nat. Natural Sci. Found. China Fudan GrandHorizon Inf. Technol., Inc. China Hewlett-Packard Co., Ltd
Starting Page	401
Ending Page	405
File Size	224777
Page Count	5
File Format	PDF
ISBN	076952432X
DOI	10.1109/CIT.2005.8
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent networks Wireless sensor networks Energy consumption Information science Heuristic algorithms Neural networks Spine Clustering algorithms Routing protocols Sensor systems
Content Type	Text
Resource Type	Article

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