计算机科学
计算卸载
移动边缘计算
动态定价
边缘计算
计算机网络
无线
无线网络
资源配置
服务器
分布式计算
GSM演进的增强数据速率
电信
营销
业务
作者
Ming Tao,Xueqiang Li,Kaoru Ota,Mianxiong Dong
出处
期刊:IEEE Transactions on Computational Social Systems
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:: 1-11
标识
DOI:10.1109/tcss.2023.3308563
摘要
Along with emerging mobile Internet applications embedded in tremendous growth of computing demand, mobile edge computing (MEC) could effectively address the issue of compute-intensive and latency-sensitive computation imposed on mobile terminals through performing computation offloading strategies. However, how to find optimal decisions of transmission power, computing capacity demand, and offloading demand at the end-user and how to determine the resource pricing and allocation at the MEC server with the limited computing capacity still remain challenging issues in operating the MEC system in an optimal fashion. For multiuser in signal cell network with MEC, a dynamic pricing-based computation offloading solution is investigated in this article. Through the use of Q-learning algorithm comprehensively considering those sensitive factors, e.g., time cost, energy consumption and dynamic pricing, the offloading decision at the end-user is achieved with the consideration of time-varying wireless channel conditions. According to the resources supply and demand relationship, a dynamic pricing algorithm for the MEC server is designed to adjust the pricing strategy to achieve the win–win situation. Simulation results have been shown to demonstrate the efficiency in making offloading decision while the wireless channel is fast fading and the resource pricing is adjusted dynamically, and in enhancing utilities for both end-users and the MEC server.
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