Knowledge-aware Proactive Nodes Selection approach for energy management in Internet of Things

@article{Liu2017KnowledgeawarePN,
  title={Knowledge-aware Proactive Nodes Selection approach for energy management in Internet of Things},
  author={Xiao Liu and Shaona Zhao and Anfeng Liu and Naixue N. Xiong and Athanasios V. Vasilakos},
  journal={Future Generation Comp. Syst.},
  year={2017},
  volume={92},
  pages={1142-1156}
}
Abstract Internet of Things will serve communities across the different domains of life. Tracking mobile targets is one important system engineering application in IOT, and the resource of embedded devices and objects working under IoT implementation are constrained. Thus, building a scheme to make full use of energy is key issue for mobile target tracking applications. To achieve both energy efficiency and high monitoring performance, an effective Knowledge-aware Proactive Nodes Selection… CONTINUE READING

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Key Quantitative Results

  • The experimental results demonstrate that compared with Probability-based target Prediction and Sleep Scheduling strategy (PPSS), KPNS scheme improves the energy efficiency by 60%, and can reduce target missing rate and tracking delay to 66%, 75% respectively.

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