Holistic resource management for sustainable and reliable cloud computing: An innovative solution to global challenge

被引:48
作者
Gill, Sukhpal Singh [1 ,2 ]
Garraghan, Peter [1 ]
Stankovski, Vlado [3 ]
Casale, Giuliano [4 ]
Thulasiram, Ruppa K. [5 ]
Ghosh, Soumya K. [6 ]
Ramamohanarao, Kotagiri [2 ]
Buyya, Rajkumar [2 ]
机构
[1] Univ Lancaster, Sch Comp & Commun, Lancaster, England
[2] Univ Melbourne, Sch Comp & Informat Syst, Cloud Comp & Distributed Syst CLOUDS Lab, Melbourne, Vic 3010, Australia
[3] Univ Ljubljana, Fac Civil & Geodet Engn, Ljubljana, Slovenia
[4] Imperial Coll London, Dept Comp, London, England
[5] Univ Manitoba, Dept Comp Sci, Winnipeg, MB, Canada
[6] Indian Inst Technol, Dept Comp Sci & Engn, Kharagpur, W Bengal, India
基金
英国工程与自然科学研究理事会; 澳大利亚研究理事会;
关键词
Cloud Computing; Energy Consumption; Sustainability; Reliability; Holistic Management; Cloud Datacenters; DATA CENTERS; ENERGY; FRAMEWORK; SIMULATION; QUALITY; SYSTEMS; POWER;
D O I
10.1016/j.jss.2019.05.025
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Minimizing the energy consumption of servers within cloud computing systems is of upmost importance to cloud providers toward reducing operational costs and enhancing service sustainability by consolidating services onto fewer active servers. Moreover, providers must also provision high levels of availability and reliability, hence cloud services are frequently replicated across servers that subsequently increases server energy consumption and resource overhead. These two objectives can present a potential conflict within cloud resource management decision making that must balance between service consolidation and replication to minimize energy consumption whilst maximizing server availability and reliability, respectively. In this paper, we propose a cuckoo optimization-based energy-reliability aware resource scheduling technique (CRUZE) for holistic management of cloud computing resources including servers, networks, storage, and cooling systems. CRUZE clusters and executes heterogeneous workloads on provisioned cloud resources and enhances the energy-efficiency and reduces the carbon footprint in datacenters without adversely affecting cloud service reliability. We evaluate the effectiveness of CRUZE against existing state-of-the-art solutions using the CloudSim toolkit. Results indicate that our proposed technique is capable of reducing energy consumption by 20.1% whilst improving reliability and CPU utilization by 17.1% and 15.7% respectively without affecting other Quality of Service parameters. (C) 2019 Elsevier Inc. All rights reserved.
引用
收藏
页码:104 / 129
页数:26
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