Boundary Recognition by Simulating a Diffusion Process in Wireless Sensor Networks
Wireless sensor networks (WSN) are becoming increasingly promising in practice. As the predeployment design and optimization are usually unpractical in random deployment scenarios, the global optimum of the WSN’s performance is achievable only if the topology dependent self-organizing process acquir...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2014-01-01
|
Series: | Abstract and Applied Analysis |
Online Access: | http://dx.doi.org/10.1155/2014/236279 |
id |
doaj-c65a22725302483f8572f303ebb5c2f0 |
---|---|
record_format |
Article |
spelling |
doaj-c65a22725302483f8572f303ebb5c2f02020-11-24T23:38:56ZengHindawi LimitedAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/236279236279Boundary Recognition by Simulating a Diffusion Process in Wireless Sensor NetworksDe Gu0Jishuai Wang1Ji Li2Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Institute of Automation, Jiangnan University, Wuxi 214122, ChinaSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaKey Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Institute of Automation, Jiangnan University, Wuxi 214122, ChinaWireless sensor networks (WSN) are becoming increasingly promising in practice. As the predeployment design and optimization are usually unpractical in random deployment scenarios, the global optimum of the WSN’s performance is achievable only if the topology dependent self-organizing process acquires the overview of the WSN, in which the boundary is the most important. The idea of this paper comes from the fact that contours only break on the geometrical boundary and the WSN are discrete sampling systems of real environments. By simulating a diffusion process in discrete form, the end point of semi-contours suggests the boundary nodes of a WSN. The simulation cases show the algorithm is well worked in WSN with average degree higher than 10. The boundary recognition could be very valuable for other algorithms dedicated to optimize the overall performance of WSN.http://dx.doi.org/10.1155/2014/236279 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
De Gu Jishuai Wang Ji Li |
spellingShingle |
De Gu Jishuai Wang Ji Li Boundary Recognition by Simulating a Diffusion Process in Wireless Sensor Networks Abstract and Applied Analysis |
author_facet |
De Gu Jishuai Wang Ji Li |
author_sort |
De Gu |
title |
Boundary Recognition by Simulating a Diffusion Process in Wireless Sensor Networks |
title_short |
Boundary Recognition by Simulating a Diffusion Process in Wireless Sensor Networks |
title_full |
Boundary Recognition by Simulating a Diffusion Process in Wireless Sensor Networks |
title_fullStr |
Boundary Recognition by Simulating a Diffusion Process in Wireless Sensor Networks |
title_full_unstemmed |
Boundary Recognition by Simulating a Diffusion Process in Wireless Sensor Networks |
title_sort |
boundary recognition by simulating a diffusion process in wireless sensor networks |
publisher |
Hindawi Limited |
series |
Abstract and Applied Analysis |
issn |
1085-3375 1687-0409 |
publishDate |
2014-01-01 |
description |
Wireless sensor networks (WSN) are becoming increasingly promising in practice. As the predeployment design and optimization are usually unpractical in random deployment scenarios, the global optimum of the WSN’s performance is achievable only if the topology dependent self-organizing process acquires the overview of the WSN, in which the boundary is the most important. The idea of this paper comes from the fact that contours only break on the geometrical boundary and the WSN are discrete sampling systems of real environments. By simulating a diffusion process in discrete form, the end point of semi-contours suggests the boundary nodes of a WSN. The simulation cases show the algorithm is well worked in WSN with average degree higher than 10. The boundary recognition could be very valuable for other algorithms dedicated to optimize the overall performance of WSN. |
url |
http://dx.doi.org/10.1155/2014/236279 |
work_keys_str_mv |
AT degu boundaryrecognitionbysimulatingadiffusionprocessinwirelesssensornetworks AT jishuaiwang boundaryrecognitionbysimulatingadiffusionprocessinwirelesssensornetworks AT jili boundaryrecognitionbysimulatingadiffusionprocessinwirelesssensornetworks |
_version_ |
1725515256281694208 |