文章摘要
Yang Xiumei(杨秀梅)* **,Chen Huaxia*,Zhang Mengying* **.[J].高技术通讯(英文),2021,27(2):121~128
Resource provisioning for computation and communication in multi-cell wireless networks
  
DOI:10.3772/j.issn.1006-6748.2021.02.002
中文关键词: 
英文关键词: resource provisioning, computation and communication, multi-cell wireless network, network edge
基金项目:
Author NameAffiliation
Yang Xiumei(杨秀梅)* ** (*Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, P.R.China) (**Key Laboratory of Wireless Sensor Network and Communications, Chinese Academy of Sciences, Shanghai 200050, P.R.China) 
Chen Huaxia* (*Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, P.R.China) (**Key Laboratory of Wireless Sensor Network and Communications, Chinese Academy of Sciences, Shanghai 200050, P.R.China) 
Zhang Mengying* ** (*Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, P.R.China) (**Key Laboratory of Wireless Sensor Network and Communications, Chinese Academy of Sciences, Shanghai 200050, P.R.China) 
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中文摘要:
      
英文摘要:
      The convergence of computation and communication at network edges plays a significant role in coping with computation-intensive and delay-critical tasks. During the stage of network planning, the resource provisioning problem for edge nodes has to be investigated to provide prior information for future system configurations. This work focuses on how to quantify the computation capabilities of access points at network edges when provisioning resources of computation and communication in multi-cell wireless networks. The problem is formulated as a discrete and non-convex minimization problem, where practical constraints including delay requirements, the inter-cell interference, and resource allocation strategies are considered. An iterative algorithm is also developed based on decomposition theory and fractional programming to solve this problem. The analysis shows that the necessary computation capability needed for certain delay guarantee depends on resource allocation strategies for delay-critical tasks. For delay-tolerant tasks, it can be approximately estimated by a derived lower bound which ignores the scheduling strategy. The efficiency of the proposed algorithm is demonstrated using numerical results.
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