A survey on intelligent routing protocols in wireless sensor networks
This paper surveys intelligent routing protocols which contribute to the optimization of network lifetime in wireless sensor networks (WSNs). Different from other surveys on routing protocols for WSNs, this paper first puts forward new ideas on the definition of network lifetime. Then, with a view t...
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| Veröffentlicht in: | Journal of network and computer applications Jg. 38; S. 185 - 201 |
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01.02.2014
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| Abstract | This paper surveys intelligent routing protocols which contribute to the optimization of network lifetime in wireless sensor networks (WSNs). Different from other surveys on routing protocols for WSNs, this paper first puts forward new ideas on the definition of network lifetime. Then, with a view to prolonging network lifetime, it discusses the routing protocols based on such intelligent algorithms as reinforcement learning (RL), ant colony optimization (ACO), fuzzy logic (FL), genetic algorithm (GA), and neural networks (NNs). Intelligent algorithms provide adaptive mechanisms that exhibit intelligent behavior in complex and dynamic environments like WSNs. Inspired by such an idea, some intelligent routing protocols have recently been designed for WSNs. Under each category, it discusses the representative routing algorithms and further analyzes the performance of network lifetime defined in three aspects. This paper intends to give assistance in the optimization of network lifetime in WSNs, together with offering a guide for the collaboration between WSNs and computational intelligence (CI). |
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| AbstractList | This paper surveys intelligent routing protocols which contribute to the optimization of network lifetime in wireless sensor networks (WSNs). Different from other surveys on routing protocols for WSNs, this paper first puts forward new ideas on the definition of network lifetime. Then, with a view to prolonging network lifetime, it discusses the routing protocols based on such intelligent algorithms as reinforcement learning (RL), ant colony optimization (ACO), fuzzy logic (FL), genetic algorithm (GA), and neural networks (NNs). Intelligent algorithms provide adaptive mechanisms that exhibit intelligent behavior in complex and dynamic environments like WSNs. Inspired by such an idea, some intelligent routing protocols have recently been designed for WSNs. Under each category, it discusses the representative routing algorithms and further analyzes the performance of network lifetime defined in three aspects. This paper intends to give assistance in the optimization of network lifetime in WSNs, together with offering a guide for the collaboration between WSNs and computational intelligence (CI). |
| Author | Guo, Wenjing Zhang, Wei |
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| Keywords | Fuzzy logic Ant colony optimization Intelligent routing protocols Genetic algorithm Neural networks Reinforcement learning Liveness Durability Routing Neural network Adaptive method Fuzzy algorithm Wireless network Swarm intelligence Routing protocols Sensor array Artificial intelligence |
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| SubjectTerms | Access methods and protocols, osi model Ant colony optimization Applied sciences Artificial intelligence Computer science; control theory; systems Computer systems and distributed systems. User interface Exact sciences and technology Fuzzy logic Genetic algorithm Intelligent routing protocols Neural networks Radiocommunications Reinforcement learning Software Telecommunications Telecommunications and information theory Teleprocessing networks. Isdn |
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