Cloudlets Activation Scheme for Scalable Mobile Edge Computing with Transmission Power Control and Virtual Machine Migration
Cloudlets Activation Scheme for Scalable Mobile Edge Computing with Transmission Power Control and Virtual Machine Migration
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DOI：
10.1109/tc.2018.2818144
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发表时间：
2018-09-01
影响因子：
3.7
通讯作者：
Temma, Katsuhiro
中科院分区：
文献类型：
--
作者：
Rodrigues, Tiago Gama;Suto, Katsuya;Temma, Katsuhiro
由于保证移动设备移动性的设计选择，移动设备有几个限制。一种超越这些限制的方法是通过移动边缘计算在网络边缘使用称为Cloudlet的云服务器。然而，随着客户端和设备数量的增长，服务还必须提高其可扩展性，以保证延迟限制和质量阈值。这可以通过部署和激活更多的Cloudlet来实现，但由于物理服务器的成本，这种解决方案很昂贵。最好的选择是通过智能的配置选择来优化Cloudlet的资源，从而降低延迟并提高可伸缩性。因此，本文提出了一种利用虚拟机迁移和传输功率控制的算法，结合移动边缘计算中延迟的数学模型和一种称为粒子群优化的启发式算法来平衡云小程序之间的工作负载，从而最大化成本效益。我们的方案是第一个在我们假设的规模内同时考虑通信、计算和迁移的方案，因此，在服务用户数量方面，我们的方案成功地超越了其他传统方法。
Mobile devices have several restrictions due to design choices that guarantee their mobility. A way of surpassing such limitations is to utilize cloud servers called cloudlets on the edge of the network through Mobile Edge Computing. However, as the number of clients and devices grows, the service must also increase its scalability in order to guarantee a latency limit and quality threshold. This can be achieved by deploying and activating more cloudlets, but this solution is expensive due to the cost of the physical servers. The best choice is to optimize the resources of the cloudlets through an intelligent choice of configuration that lowers delay and raises scalability. Thus, in this paper we propose an algorithm that utilizes Virtual Machine Migration and Transmission Power Control, together with a mathematical model of delay in Mobile Edge Computing and a heuristic algorithm called Particle Swarm Optimization, to balance the workload between cloudlets and consequently maximize cost-effectiveness. Our proposal is the first to consider simultaneously communication, computation, and migration in our assumed scale and, due to that, manages to outperform other conventional methods in terms of number of serviced users.