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Priority, network and energy-aware placement of IoT-based application services in fog-cloud environments
IET Communications ( IF 1.6 ) Pub Date : 2020-07-22 , DOI: 10.1049/iet-com.2020.0007
Hiwa Omer Hassan 1 , Sadoon Azizi 1 , Mohammad Shojafar 2
Affiliation  

Fog computing is a decentralised model which can help cloud computing for providing high quality-of-service (QoS) for the Internet of Things (IoT) application services. Service placement problem (SPP) is the mapping of services among fog and cloud resources. It plays a vital role in response time and energy consumption in fog–cloud environments. However, providing an efficient solution to this problem is a challenging task due to difficulties such as different requirements of services, limited computing resources, different delay, and power consumption profile of devices in fog domain. Motivated by this, in this study, we propose an efficient policy, called MinRE, for SPP in fog–cloud systems. To provide both QoS for IoT services and energy efficiency for fog service providers, we classify services into two categories: critical services and normal ones. For critical services, we propose MinRes, which aims to minimise response time, and for normal ones, we propose MinEng, whose goal is reducing the energy consumption of fog environment. Our extensive simulation experiments show that our policy improves the energy consumption up to 18%, the percentage of deadline satisfied services up to 14% and the average response time up to 10% in comparison with the second-best results.

中文翻译:

雾云环境中基于IoT的应用程序服务的优先级,网络和能源感知布置

雾计算是一种分散的模型,可以帮助云计算为物联网(IoT)应用程序服务提供高服务质量(QoS)。服务放置问题(SPP)是雾和云资源之间的服务映射。它在雾云环境中的响应时间和能耗中起着至关重要的作用。然而,由于诸如服务的不同需求,有限的计算资源,不同的延迟以及雾域中的设备的功耗曲线之类的困难,为该问题提供有效的解决方案是一项具有挑战性的任务。因此,在本研究中,我们为雾云系统中的SPP提出了一种有效的策略,即MinRE。为了同时为物联网服务提供QoS和为雾服务提供商提供能效,我们将服务分类为类别:关键服务和普通服务。对于关键服务,我们建议使用MinRes,以最大程度地减少响应时间;对于正常服务,我们建议使用MinEng,其目的是减少雾环境的能耗。我们广泛的模拟实验表明,与第二好的结果相比,我们的策略将能耗降低了18%,按时满足服务的百分比提高了14%,平均响应时间提高了10%。
更新日期:2020-07-24
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