Task offloading in Edge and Cloud Computing: A survey on mathematical, artificial intelligence and control theory solutions
Task offloading in Edge and Cloud Computing: A survey on mathematical, artificial intelligence and control theory solutions
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DOI：
10.1016/j.comnet.2021.108177
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发表时间：
2021-08
期刊：
影响因子：
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通讯作者：
Firdose Saeik;Marios Avgeris;Dimitrios Spatharakis;Nina Santi;Dimitrios Dechouniotis;John Violos;
中科院分区：
文献类型：
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作者：
Firdose Saeik;Marios Avgeris;Dimitrios Spatharakis;Nina Santi;Dimitrios Dechouniotis;John Violos;
下一代通信网络预计将容纳大量新的、资源丰富的应用程序，这些应用程序可以提供给大量的最终用户。尽管终端设备变得越来越强大，但可用的本地资源仍无法满足这些应用程序的要求。这带来了一个称为任务卸载的新挑战，其中计算密集型任务需要卸载到资源更强大的远程设备。当然，云计算是经过充分测试的基础设施，可以促进任务卸载。然而，云计算作为集中式远程基础设施会产生严重的通信延迟，无法满足新兴延迟敏感应用程序的要求。为此，人们提出了边缘计算的概念，将云计算能力重新定位到更靠近网络边缘的终端设备。本文详细介绍了如何将边缘和/或云结合在一起以解决任务卸载问题。特别强调数学、人工智能和控制理论优化方法，这些方法可用于满足这种端到端应用程序执行方法的各种目标、约束和动态条件。调查最后确定了当前问题的开放挑战和未来方向。
Next generation communication networks are expected to accommodate a high number of new and resource-voracious applications that can be offered to a large range of end users. Even though end devices are becoming more powerful, the available local resources cannot cope with the requirements of these applications. This has created a new challenge called task offloading, where computation intensive tasks need to be offloaded to more resource powerful remote devices. Naturally, the Cloud Computing is a well-tested infrastructure that can facilitate the task offloading. However, Cloud Computing as a centralized and distant infrastructure creates significant communication delays that cannot satisfy the requirements of the emerging delay-sensitive applications. To this end, the concept of Edge Computing has been proposed, where the Cloud Computing capabilities are repositioned closer to the end devices at the edge of the network. This paper provides a detailed survey of how the Edge and/or Cloud can be combined together to facilitate the task offloading problem. Particular emphasis is given on the mathematical, artificial intelligence and control theory optimization approaches that can be used to satisfy the various objectives, constraints and dynamic conditions of this end-to-end application execution approach. The survey concludes with identifying open challenges and future directions of the problem at hand.