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Security-Aware computation offloading for Mobile edge computing-Enabled smart city
Journal of Cloud Computing ( IF 3.418 ) Pub Date : 2021-08-28 , DOI: 10.1186/s13677-021-00262-6
Kai Peng 1 , Peichen Liu 1 , Peng Tao 2 , Qingjia Huang 3
Affiliation  

Smart city has obtained increasing attention from both academic and industry which has the potential to improve human living standards. A smart city consists of a great number of smart devices which are generating large amounts of data and emerging applications all the time. However, the computing capacity of smart devices are limited. Fortunately, the emergence of MEC can solve the above problem. However, the resources of edge servers in MEC are limited and the capabilities of edge servers are heterogeneous. It is important to improve the average resource utilization of all edge servers and keep load balancing of edge server cluster simultaneously. On the other hand, quite a few numbers of applications are delay-sensitive, it is necessary to ensure the security of these applications. In this paper, we consider joint optimization of mobile device and edge server in MEC-enabled smart city, improving the overall performance of the system. Technically, a new multi-objective computation offloading method is implemented to reduce time consumption, energy consumption, and keep load balancing of edge servers, as well as increase average resource utilization of edge servers while meeting the deadline constraint of delay-sensitive applications. Sufficient experiments have been conducted to prove the effectiveness and superiority of our proposed method in different scenarios.

中文翻译:

支持移动边缘计算的智能城市的安全感知计算卸载

智慧城市越来越受到学术界和工业界的关注,它具有提高人类生活水平的潜力。智慧城市由大量智能设备组成,这些设备无时无刻不在产生大量数据和新兴应用。然而,智能设备的计算能力是有限的。幸运的是,MEC 的出现可以解决上述问题。然而,MEC 中边缘服务器的资源有限,边缘服务器的能力是异构的。提高所有边缘服务器的平均资源利用率并同时保持边缘服务器集群的负载平衡很重要。另一方面,相当多的应用程序对延迟敏感,有必要确保这些应用程序的安全性。在本文中,我们考虑在启用 MEC 的智慧城市中联合优化移动设备和边缘服务器,提高系统的整体性能。在技​​术上,实现了一种新的多目标计算卸载方法,以减少边缘服务器的时间消耗、能耗和保持负载平衡,并在满足延迟敏感应用程序的期限约束的同时提高边缘服务器的平均资源利用率。已经进行了足够的实验来证明我们提出的方法在不同场景中的有效性和优越性。以及提高边缘服务器的平均资源利用率,同时满足延迟敏感应用程序的期限约束。已经进行了足够的实验来证明我们提出的方法在不同场景中的有效性和优越性。以及提高边缘服务器的平均资源利用率,同时满足延迟敏感应用程序的期限约束。已经进行了足够的实验来证明我们提出的方法在不同场景中的有效性和优越性。
更新日期:2021-08-29
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