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Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things.
Ding, Kaiqi; Zhao, Haitao; Hu, Xiping; Wei, Jibo.
Afiliação
  • Ding K; College of Electronic Science, National University of Defense Technology, Changsha, 410073, China. dingkaiqi15@nudt.edu.cn.
  • Zhao H; College of Electronic Science, National University of Defense Technology, Changsha, 410073, China. haitaozhao@nudt.edu.cn.
  • Hu X; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. xp.hu@siat.ac.cn.
  • Wei J; Department of Mechanical and Automation Engineering, Chinese University of Hong Kong, Hong Kong. xp.hu@siat.ac.cn.
Sensors (Basel) ; 17(11)2017 Oct 28.
Article em En | MEDLINE | ID: mdl-29143767
ABSTRACT
In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT). Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT (i) each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii) the network can rapidly converge to a collision-free transmission through each node's learning ability in the process of the distributed channel allocation; and (iii) the network throughput is further improved via the dynamic time slot optimization.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article