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An optimised algorithm to detect faulty readings along the substrate access wireless long-thin sensor networks

Barati, A ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/EMS.2011.42
  3. Abstract:
  4. Wireless sensor networks (WSNs) are composed of hundreds or thousands of small nodes, which work together and associate with a specific task or tasks to do. It is expected that wireless sensor networks will be used widely in many applications in the near future. One of the most important issues in WSNs is localisation. There are crucial problems over network localisation such as security attacks (internal or external), energy efficiency, and accuracy, which impact performance and energy-consuming of wireless sensor networks. The main source of these problems is network topology. A long-thin network topology (LTNT) in wireless sensor can produce errors in network localisation due to special deployment of nodes, also it can cause detecting nodes with faulty readings. This paper proposes an optimised algorithm based on Debraj De algorithm to determine faulty readings in WSNs. This algorithm uses a correlation parameter of two nodes to detect nodes with faulty readings. The proposed algorithm reduces computational complexity of the correlation algorithm, which causes network energy consumption becomes significantly low when compared with the original algorithm
  5. Keywords:
  6. Faulty readings ; Long-thin networks ; Network energy consumption ; Wireless sensor networks ; Correlation algorithm ; Correlation parameters ; DE algorithms ; Impact performance ; Localisation ; Long-thin network ; Network topology ; Original algorithms ; Security attacks ; Specific tasks ; Wireless sensor ; Algorithms ; Electric network topology ; Energy efficiency ; Energy utilization ; Sensor nodes
  7. Source: Proceedings - UKSim 5th European Modelling Symposium on Computer Modelling and Simulation, EMS 2011 ; 2011 , Pages 372-377 ; 9780769546193 (ISBN)
  8. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6131240