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논문검색

Virtual Cluster Model in Clustered Wireless Sensor Network Using Cuckoo Inspired Metaheuristic Algorithm

초록

영어

Energy efficient clustering is well known optimization problem which has been studied widely to extend lifetime of wireless sensor networks (WSNs). Grid computing, enable different entities to share computational, memory, and data resources using a flexible and secure framework. These resources enable users to run computational jobs that exceed the capabilities of available sensor at any single location. The algorithm presented here is to create a virtual cluster within established clusters in wireless sensor network to share individual sensor resources, which permits the wireless sensor network to gain extra cluster resources to run resource consuming applications with private resource control policies. According to the power issue and the unpredictable wireless network characteristics, it is possible that applications running on the sensor nodes might fail due to sensor energy termination, hence, using Cuckoo Search Optimization (CSO) algorithm is necessary as inspired nature technique to improve the availability of sensor nodes by electing the optimum sensor node from each cluster according to precise constrains applied by network specifications. The motivation for this virtual cluster is to create a virtual cluster environment with heterogeneous resources from clusters with homogeneous nodes when a critical event take place and need a service might requires several sensors resources which make it necessary to arrange these resources to achieve the required service.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Grid Computing and Wireless Sensor Network
  3.1 Grid Architecture
  3.2 Grid Topologies
  3.3 Design Concerns and Challenges
 4. The Proposed Virtual Cluster Generation (Vir_Clu_Gen) Algo
 5. Discrete Cuckoo Searching Optimization
  5.1 Cuckoo Searching (CS)
  5.2 Nest Representation
  5.3 Discrete Step Size and Updating Scheme
  5.4 Discrete Fitness Function
  5.5 Virtual Cluster Generation (Vir_Clu_Gen) Algorithm
  5.6 Energy Consumption Model
 6. Simulation Results
 7. Conclusion
 Acknowledgements
 References

저자정보

  • May Kamil Al-Azzawi College of Computer Science and Electronic Engineering, Hunan University Changsha, Hunan, 410082, China, Al-Mansour University College, Department of Computer Science and Informatics
  • Juan Luo College of Computer Science and Electronic Engineering, Hunan University Changsha, Hunan, 410082, China
  • Renfa Li College of Computer Science and Electronic Engineering, Hunan University Changsha, Hunan, 410082, China

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