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Volume 46 Issue 4
Apr.  2024
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ZHANG Zheng, YI Chen, LIN Jinzhao, PANG Yu, LI Guoquan, LI Zhangyong, LI Chunguo. Resource Scheduling Based on Multi-factor Priority for High Performance Requirements in Wireless Body Area Network[J]. Journal of Electronics & Information Technology, 2024, 46(4): 1247-1256. doi: 10.11999/JEIT230733
Citation: ZHANG Zheng, YI Chen, LIN Jinzhao, PANG Yu, LI Guoquan, LI Zhangyong, LI Chunguo. Resource Scheduling Based on Multi-factor Priority for High Performance Requirements in Wireless Body Area Network[J]. Journal of Electronics & Information Technology, 2024, 46(4): 1247-1256. doi: 10.11999/JEIT230733

Resource Scheduling Based on Multi-factor Priority for High Performance Requirements in Wireless Body Area Network

doi: 10.11999/JEIT230733
Funds:  The National Natural Science Foundation of China (U21A20447), The Science and Technology Research Program of Chongqing Municipal Education Commission under Grant (KJQN202200627), The Innovative Talent Program for Doctoral Students of Chongqing University of Posts and Telecommunications (BYJS202206)
  • Received Date: 2023-07-19
  • Rev Recd Date: 2024-01-23
  • Available Online: 2024-02-19
  • Publish Date: 2024-04-24
  • Media Access Control (MAC) plays a pivotal role in ensuring proper operation of Wireless Body Area Networks (WBAN). However, current solutions still cannot satisfy high performance requirements of low latency and energy consumption for emergency data reporting. A Multi-factor Emergency Scheduling Scheme (MESS) is proposed to meeting such a strict demand. First, a data classification method is designed to sort data as periodic data and emergency data, respectively. Unlike consistent data characteristics in other schemes, data heterogeneity is considered in our solution, which is more practical for different nodes. Second, a multi-factor priority division scheme is devised, according to the disease-related factor, critical degree factor, health severity factor and age of information factor. This is a more comprehensive consideration of the key characteristics of the node. In addition, a dynamic slot allocation and sequencing approach is designed, in which time slots of nodes are allocated based on the data classification and multi-factor priority-based ordering. This enhances low latency and guarantees energy efficiency of nodes. Theoretical and simulation results demonstrate the advantages of MESS in terms of delay and energy efficiency.
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