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| 报告人简介：张永敏，中南大学计算机学院特聘教授。于2015毕业于浙江大学控制科学与工程专业。2013-2014年曾到美国加州理工学院计算机工程系进行访问交流，导师为Steven Low教授。2015年12月至2019年5月在加拿大维多利亚大学电子工程系蔡霖教授课题组开展博士后研究。在IEEE JSAC、ToN、TMC、TSG、TITS等国际权威期刊以及IEEE INFOCOM、SECON等国际会议上发表论文20余篇。曾获IEEE PIMRC 2012国际会议最佳论文奖，IEEE通信协会亚太区的杰出论文奖。曾担任IEEE Globecom, WCNC, ICC, VTC等重要国际会议程序委员会成员。
报告简介：Both the edge and the cloud can provide computing services for mobile devices to enhance their performance. The edge can reduce the conveying delay by providing local computing services while the cloud can support enormous computing requirements. Their cooperation can improve the utilization of computing resources and ensure the QoS, and thus is critical to edge-cloud computing business models. This paper proposes an efficient framework for mobile edge-cloud computing networks, which enables the edge and the cloud to share their computing resources in the form of wholesale and buyback. To optimize the computing resource sharing process, we formulate the computing resource management problems for the edge servers to manage their wholesale and buyback scheme and the cloud to determine the wholesale price and its local computing resources. Then, we solve these problems from two perspectives: i) social welfare maximization and ii) profit maximization for the edge and the cloud. For i), we have proved the concavity of the social welfare and proposed an optimal cloud computing resource management to maximize the social welfare. For ii), we first proved the concavity of the wholesaled computing resources with respect to the wholesale price and designed an optimal pricing and cloud computing resource management to maximize their profits. Numerical evaluations show that the total profit can be maximized by social welfare maximization while the respective profits can be maximized by the optimal pricing and cloud computing resource management.
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