Green Approach for Joint Management of Geo-Distributed Data Centers and Interconnection Networks

Abstract

Every time an Internet user downloads a video, shares a picture, or sends an email, his/her device addresses a data center and often several of them. These complex systems feed the web and all Internet applications with their computing power and information storage, but they are very energy hungry. The energy consumed by Information and Communication Technology (ICT) infrastructures is currently more than 4% of the worldwide consumption and it is expected to double in the next few years. Data centers and communication networks are responsible for a large portion of the ICT energy consumption and this has stimulated in the last years a research effort to reduce or mitigate their environmental impact. Most of the approaches proposed tackle the problem by separately optimizing the power consumption of the servers in data centers and of the network. However, the Cloud computing infrastructure of most providers, which includes traditional telcos that are extending their offer, is rapidly evolving toward geographically distributed data centers strongly integrated with the network interconnecting them. Distributed data centers do not only bring services closer to users with better quality, but also provide opportunities to improve energy efficiency exploiting the variation of prices in different time zones, the locally generated green energy, and the storage systems that are becoming popular in energy networks. In this paper, we propose an energy aware joint management framework for geo-distributed data centers and their interconnection network. The model is based on virtual machine migration and formulated using mixed integer linear programming (MILP). It can be solved using state-of-the art solvers such as CPLEX in reasonable time. The proposed approach covers various aspects of Cloud computing systems. Alongside, it jointly manages the use of green and brown energies using energy storage technologies. The obtained results show that significant energy cost savings can be achieved compared to a baseline strategy, in which data centers do not collaborate to reduce energy and do not use the power coming from renewable resources.

Resource Management in a Containerized Cloud: Status and Challenges

“…Aral & Ovatman [27] 2018 Barkat et al [35] 2018 Govindaraj & Artemenko [62] 2018 Guo et al [65] 2018 Jia et al [77] 2018 Jia et al [78] 2018 Lin et al [93] 2018 Stoyanov & Kollingbaum [141] 2018 Wang & Gelenbe [148] 2018 Wei et al [151] 2018 application workloads. Somewhat related, Wu et al studied the overhead introduced by launching new VMs in the context of Cloud bursting [154].…”

“…As a result, the authors introduced a VM launching overhead reference model based on operational data, which could help to decide when and where a new VM should be launched. Global provisioning and scheduling often includes VM consolidation [35,58,65,74,80,111,118], which typically aims to pack the virtual machines onto few physical servers in order to reduce the operational costs. Huang et al for example presented a framework for VM consolidation that aims to achieve a balance among multiple objectives [74], which can also be used in a context that requires minimal system re-configurations.…”