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Smart workload migration on external cloud service providers to minimize delay, running time, and transfer cost
International Journal of Communication Systems ( IF 1.7 ) Pub Date : 2020-11-23 , DOI: 10.1002/dac.4686
Afzal Badshah 1 , Anwar Ghani 1 , Azeem Irshad 2 , Husnain Naqvi 1 , Saru Kumari 3
Affiliation  

With limited resources, overutilization is a challenging issue in the emerging system of smart devices, resulting in higher costs, poor performance and low prices due to service level agreement (SLA) violations. These factors extremely annoy the customers as well as providers. External resources are hired to overcome the resources scalability challenges; however, external resources cause higher delay, running time, and transfer cost. The lift in delay explicitly means more cost and more customers dissatisfaction. The delay and transfer cost increases with geographical distance and overutilization. In this article, a mechanism is proposed to make efficient migration decisions to external cloud service providers (CSPs) to minimize the delay, running time, and transfer cost by searching an optimum data center (DC), where the resources may be taken with optimum conditions. The Cloud Analyst is extended to simulate the proposed framework. Results were calculated for three different phenomena, where hiring the resources from underutilized DC decreases the running time to 0.237 ms; however, the response time and transfer cost increases to 499 ms and 0.228 $, respectively; similarly, getting the resources of nearest DC drops the delay time and transfer cost to 80 ms and 0.065 $ respectively; however, the execution time increases to 0.500 ms. The proposed framework optimized the delay time, execution time and transfer cost to 50 ms, 0.237 ms, and 0.065 $, respectively.

中文翻译:

外部云服务提供商上的智能工作负载迁移可最大程度地减少延迟,运行时间和转移成本

在资源有限的情况下,过度使用是新兴的智能设备系统中的一个挑战性问题,由于违反服务水平协议(SLA),导致更高的成本,更差的性能和更低的价格。这些因素极大地困扰了客户和提供商。雇用外部资源来克服资源可扩展性挑战;但是,外部资源会导致更高的延迟,运行时间和传输成本。延迟的增加显然意味着更多的成本和更多的客户不满。延迟和转移成本随着地理距离和过度利用而增加。本文提出了一种机制,可以通过搜索最佳数据中心(DC)来做出向外部云服务提供商(CSP)的有效迁移决策,以最大程度地减少延迟,运行时间和传输成本,可以在最佳条件下获取资源的地方。扩展了Cloud Analyst以模拟提出的框架。计算了三种不同现象的结果,其中从未充分利用的DC中租用资源可将运行时间缩短至0.237 ms;但是,响应时间和传输成本分别增加到499 ms和0.228 $;同样,获取最近的DC资源将延迟时间和传输成本分别降低到80 ms和0.065 $;但是,执行时间增加到0.500 ms。所提出的框架将延迟时间,执行时间和传输成本分别优化为50 ms,0.237 ms和0.065 $。从未充分利用的DC中租用资源将运行时间减少到0.237 ms;但是,响应时间和传输成本分别增加到499 ms和0.228 $;同样,获取最近的DC资源将延迟时间和传输成本分别降低到80 ms和0.065 $;但是,执行时间增加到0.500 ms。所提出的框架将延迟时间,执行时间和传输成本分别优化为50 ms,0.237 ms和0.065 $。从未充分利用的DC中租用资源将运行时间减少到0.237 ms;但是,响应时间和传输成本分别增加到499 ms和0.228 $;同样,获取最近的DC资源将延迟时间和传输成本分别降低到80 ms和0.065 $;但是,执行时间增加到0.500 ms。所提出的框架将延迟时间,执行时间和传输成本分别优化为50 ms,0.237 ms和0.065 $。
更新日期:2021-01-04
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