A Biologically Inspired Networking Model for Wireless Sensor Networks
dc.contributor | Cui, Shuguang | |
dc.creator | Charalambous, Charalambos | |
dc.date.accessioned | 2011-02-22T22:24:03Z | |
dc.date.accessioned | 2011-02-22T23:47:17Z | |
dc.date.accessioned | 2017-04-07T19:57:57Z | |
dc.date.available | 2011-02-22T22:24:03Z | |
dc.date.available | 2011-02-22T23:47:17Z | |
dc.date.available | 2017-04-07T19:57:57Z | |
dc.date.created | 2009-12 | |
dc.date.issued | 2011-02-22 | |
dc.description.abstract | Wireless sensor networks (WSNs) have emerged in strategic applications such as target detection, localization, and tracking in battlefields, where the large-scale na- ture renders centralized control prohibitive. In addition, the finite batteries in sensor nodes demand energy-aware network control. In this thesis, we propose an energy- efficient topology management model inspired by biological inter-cellular signaling schemes. The model allows sensor nodes to cluster around imminent targets in a purely distributed and autonomous fashion. In particular, nodes in the target vicinity collaborate to form clusters based on their relative observation quality values. Sub- sequently, the clustered sensor nodes compete based on their energy levels until some of them gain active status while the rest remain idle, again according to a distributed algorithm based on biological processes. A final phase of the model has the active cluster members compete until one of them becomes the clusterhead. We examine the behavior of such a model in both finite-size and infinite-size networks. Specifically, we show that the proposed model is inherently stable and achieves superior energy efficiency against reference protocols for networks of finite size. Furthermore, we dis- cuss the behavior of the model in the asymptotic case when the number of nodes goes to infinity. In this setting, we study the average number of cluster members. | |
dc.identifier.uri | http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7508 | |
dc.language.iso | en_US | |
dc.subject | bio-inspired | |
dc.subject | sensor networks | |
dc.subject | distributed | |
dc.subject | clustering | |
dc.subject | induction | |
dc.subject | node activation | |
dc.subject | inhibition | |
dc.subject | topology control | |
dc.subject | networking model | |
dc.title | A Biologically Inspired Networking Model for Wireless Sensor Networks | |
dc.type | Book | |
dc.type | Thesis |