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- Type of Document: M.Sc. Thesis
- Language: English
- Document No: 39274 (52)
- University: Sharif University of Technology, International Campus, Kish Island
- Department: Science and Engineering
- Advisor(s): Hashemi Mohammadabad, Saeed
- Abstract:
- WSNs have been gained much attention in both industrial and educational communities, as they are expected to bring interaction between humans, environment, and machines into a new level. Due to the differences between Wireless Sensor Networks and other wireless networks, new network architectures have been developed and many new routing protocols have been proposed for these architectures. To solve routing problems in WSNs by Swarm Algorithm (SA) is an active, interesting research area and this thesis tries to bring up a new SA towards this mater. Using artificial intelligence (AI) techniques in this environment is a promising task which is challenging at the same time. In this thesis we suggest IACO a new ant colony based routing algorithm which uses machine learning method to predict and learn during its work. It also shows more flexibility as it is using the knowledge which is based on the output of our model. The simulation result shows that when the number of sensor nodes in WSNs increases the performance of IACO is better than the other widely used algorithms: PEGASIS, LEACH, AntNet, which used in routing on WSNs
- Keywords:
- Swarm Intelligence ; Wireless Sensor Network ; Data Mining ; Ant System Algorithm ; Ant Colony Optimization (ACO) ; Artificial Intelligence ; Incremental Ant Colony Optimization
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