湘江高端学术报告会：

Computation Offloading in Fog Computing:

A Combinatorial Optimization Approach

bat365在线平台官方网站计算机科学与工程学院将于2024年1月2日（周二）举行湘江高端论坛，主题为“Computation Offloading in Fog Computing: A Combinatorial Optimization Approach” 的学术报告会。敬请光临！

报告题目：Computation Offloading in Fog Computing: A Combinatorial Optimization Approach

报 告 人：IEEE Fellow、欧洲科学院院士、湖南大学特聘教授 李克勤

报告时间：2024年1月2日周二下午 16:00-17:00

报告地点：逸夫楼201会议室

报告摘要：

The investigation in this study makes the following important contributions to combinatorial optimization of computation offloading in fog computing. First, we rigorously define the two problems of optimal computation offloading with energy constraint and optimal computation offloading with time constraint. We do this in such a way that between execution time and energy consumption, we can fix one and minimize the other. We prove that our optimization problems are NP-hard, even for very special cases. Second, we develop a unique and effective approach for solving the proposed combinatorial optimization problems, namely, a two-stage method. In the first stage, we generate a computation offloading strategy. In the second stage, we decide the computation speed and the communication speeds. This method is applicable to both optimization problems. Third, we use a simple yet efficient greedy method to produce a computation offloading strategy by taking all aspects into consideration, including the properties of the communication channels, the power consumption models of computation and communication, the tasks already assigned and allocated, and the characteristics of the current task being considered. Fourth, we experimentally evaluate the performance of our heuristic algorithms. We observe that while various heuristics do exhibit noticeably different performance, there can be a single and simple heuristic which can perform very well. Furthermore, the method of compound algorithm can be applied to obtain slightly improved performance. Fifth, we emphasize that our problems and algorithms can be easily extended to study combined performance and cost optimization (such as cost-performance ratio and weighted cost-performance sum optimization), and to accommodate more realistic and complicated fog computing environments (such as preloaded mobile edge servers and multiple users) with little extra effort. To the best of our knowledge, there has been no similar study in the existing fog computing literature.

个人简介：

李克勤， 纽约州立大学特聘教授和湖南大学（中国）国家特聘教授，纽约州立大学杰出学院成员， AAAS Fellow、IEEE Fellow、AAIA Fellow 和 ACIS Founding Fellow，欧洲科学院院士（Academia Europaea），1985 年获清华大学计算机科学学士学位，1990 年获休斯顿大学计算机科学博士学位。撰写或合著了 970 多篇期刊论文、书籍章节和经评审的会议论文。曾多次获得国际会议最佳论文奖，包括 PDPTA-1996、NAECON-1997、IPDPS-2000、ISPA-2016、NPC-2019、ISPA-2019 和 CPSCom-2022。拥有近 75 项中国国家知识产权局公布或授权的专利。在并行计算和分布式计算领域的单年度和职业生涯影响位居世界前五位（Scopus引文数据库）。连续二十多年入选《马奎斯科学与工程名人录》、《美国名人录》、《世界名人录》和《美国教育名人录》。2017年荣获阿尔伯特-纳尔逊-马奎斯终身成就奖。2018 年获得休斯顿大学计算机科学系颁发的杰出校友奖。 2022 年获得 IEEE CS 云计算技术委员会 IEEE TCCLD 研究影响奖。于 2023 年获得 IEEE CS 服务计算技术社区颁发的 IEEE TCSVC 研究创新奖。 2023 年荣获 IEEE 第一区技术创新奖（学术）。