Scale-free topology optimization for software-defined wireless sensor networks: A cyber-physical system
Ru Huang,
Xiaoli Chu,
Jie Zhang and
Yu Hen Hu
International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 6, 1550147717713626
Abstract:
Due to the limited resource and vulnerability in wireless sensor networks, maximizing the network lifetime and improving network survivability have become the top priority problem in network topology optimization. This article presents a wireless sensor networks topology optimization model based on complex network theory and cyber-physical systems using software-defined wireless sensor network architecture. The multiple-factor-driven virtual force field and network division–oriented particle swarm algorithm are introduced into the deployment strategy of super-node for the implementation in wireless sensor networks topology initialization, which help to rationally allocate heterogeneous network resources and balance the energy consumption in wireless sensor networks. Furthermore, the preferential attachment scheme guided by corresponding priority of crucial sensors is added into scale-free structure for optimization in topology evolution process and for protection of vulnerable nodes in wireless sensor networks. Software-defined wireless sensor network–based functional architecture is adopted to optimize the network evolution rules and algorithm parameters using information cognition and flow-table configure mode. The theoretical analysis and experimental results demonstrate that the proposed wireless sensor networks topology optimization model possesses both the small-world effect and the scale-free property, which can contribute to extend the lifetime of wireless sensor networks with energy efficiency and improve the robustness of wireless sensor networks with structure invulnerability.
Keywords: Software-defined wireless sensor network; scale-free network; topological optimization; super-nodes; cyber-physical systems (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:6:p:1550147717713626
DOI: 10.1177/1550147717713626
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