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Energy-efficient auto-scaling of virtualized network function instances based on resource execution pattern
Computers & Electrical Engineering ( IF 4.0 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.compeleceng.2020.106814
Asif Mehmood , Afaq Muhammad , Talha Ahmed Khan , Javier Jose Diaz Rivera , Javed Iqbal , Ihtesham Ul Islam , Wang-Cheol Song

Abstract To scale virtualized network functions (VNF), information about computing resource utilization plays an important role. With the usage of both virtualized and physical resources, introduced new challenges that need to be solved by virtual network functions manager (VNFM), which are responsible for managing the lifecycle of VNFs. These challenges demand an auto-scaling mechanism that relies on proper factors. The proposed system considers the execution time, thresholds of a VNF, and weight factor reflecting virtualization overhead as the practical factors. An auto-scaling application, along with the monitoring application, is developed. These two applications communicate with each other via application programming interfaces (API) to generate the auto-scaling configurations of resources. In the light of mentioned factors, mechanism, and later provided results, the proposed system proves to be useful in solving the challenges related to energy and allocation of resources for both virtual and physical infrastructures.

中文翻译:

基于资源执行模式的虚拟化网络功能实例的节能自动扩展

摘要 要扩展虚拟化网络功能(VNF),有关计算资源利用率的信息起着重要作用。随着虚拟化和物理资源的使用,引入了需要由负责管理 VNF 生命周期的虚拟网络功能管理器 (VNFM) 解决的新挑战。这些挑战需要一种依赖于适当因素的自动缩放机制。所提出的系统将执行时间、VNF 的阈值和反映虚拟化开销的权重因子视为实际因素。开发了一个自动缩放应用程序以及监控应用程序。这两个应用程序通过应用程序编程接口 (API) 相互通信以生成资源的自动缩放配置。鉴于上述因素,机制,
更新日期:2020-12-01
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