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Using Learning Algorithms for Energy Efficient Routing in Wireless Sensor Network

Heidarzadeh, Elahe | 2011

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 42360 (52)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Beigy, Hamid
  7. Abstract:
  8. Wireless Sensor Networks (WSNs) have attracted much attention in recent years for their unique characteristics and wide use in many different applications. WSNs are composed of many tiny sensor nodes that have limitations on energy level, bandwidth, processing power and memory. Therefore, reducing energy consumption and the increased network lifetime and scalability are the main routing challenges in sensor networks. Many algorithms were presented for routing in sensor networks; a class of theses algorithms is hierarchical algorithms based on clustering. Their main goals are to reduce energy consumption, distribution energy consumption in the whole network and increasing scalability. There are problems in many routing algorithms based on clustering that causes a lack of efficiency. Assumption of the same initial energy of nodes, algorithms with lack of knowledge about the energy level and place of nodes, overhead due clustering phase and sending single-hop data from the cluster head to the sink are some of these problems. This research aims to investigate a new clustering-based routing algorithm to solve the mentioned problems or reduce their negative effects. The purpose of this algorithm is to form balanced clusters with good physical shape, energy consumption balance and multi hop routing from the cluster head to the sink. We study how the learning algorithms based on clustering protocols can be used to find a good route between a node and the sink node without additional control packets for route maintenance. This algorithm is aware of the location and energy level of nodes whose clusters of nodes are based on spatial information and selecting the cluster head in each round is based on the energy level of nodes. Simulation results show that using this algorithm for routing can achieve longer lifetime than LEACH, and MuELSC algorithms in the network
  9. Keywords:
  10. Learning Algorithm ; Routing ; Wireless Sensor Network ; Energy Efficiency

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