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Distributed QoS routing algorithm in large scale wireless sensor networks

Kordafshari, M. S ; Sharif University of Technology | 2012

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  1. Type of Document: Article
  2. DOI: 10.1109/ISIE.2012.6237195
  3. Publisher: IEEE , 2012
  4. Abstract:
  5. This paper presents a novel routing protocol based on the Learning Automata method for large scale Wireless Sensor Networks (WSNs) codenamed DRLR (distributed reinforcement learning routing). In this method, each node is equipped with learning automata so that it can learn the best path to transmit data toward the sink. The approach proved to be efficient, reliable, and scalable. It also prevents routing hole by considering network density and average of energy levels available. The approach also increases network lifetime by balancing energy consumption. We compared our approach to two other methods (MMSPEED and EESPEED) and the simulation results show our algorithm to better meet end-to-end delay and reliability requirements and to improve network lifetime more
  6. Keywords:
  7. Balancing energy ; Best paths ; Distributed QoS routing ; Distributed reinforcement learning ; End to end delay ; Large-scale wireless sensor networks ; Learning Automata ; Network density ; Network lifetime ; Transmit data ; Energy utilization ; Wireless sensor networks ; Industrial electronics
  8. Source: IEEE International Symposium on Industrial Electronics ; 2012 , Pages 826-830 ; 9781467301589 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6237195