计算机科学
回程(电信)
计算机网络
移动边缘计算
核心网络
GSM演进的增强数据速率
分布式计算
蜂窝网络
边缘计算
基站
服务器
人工智能
作者
Hui Li,Chuan Sun,Xiuhua Li,Qingyu Xiong,Junhao Wen,Xiaofei Wang,Victor C. M. Leung
标识
DOI:10.1109/globecom42002.2020.9348257
摘要
With the tremendous growth of mobile data traffic generated by various devices such as smartphones, smartpads and wearable devices, it is necessary for mobile network operators to introduce revolutionary networking techniques, thereby satisfying service requirements of mobile users. Recently, mobile edge computing (MEC) has been regarded as an effective technique to alleviate the traffic burden on backhaul networks. In this paper, we investigate the issue of mobility-aware content caching and user association for ultra-dense MEC networks by minimizing the system costs. The problem is formulated as a complex pure integer nonlinear programming, which is NP-hard. To address the original long-term optimization problem, we decompose it into a series of one-slot subproblems, and then optimize the short-term subproblem in two phases (i.e., content caching and user association). We further propose a mobility-aware online caching algorithm to achieve content caching, and a lazy re-association algorithm to determine user association based on matching theory. Trace-driven evaluation results demonstrate that the proposed framework has superior performance on reducing system costs.
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