Bi-objective Heterogeneous Consolidation in Cloud Computing

  • Luis-Angel Galaviz-Alejos
  • Fermín Armenta-Cano
  • Andrei TchernykhEmail author
  • Gleb Radchenko
  • Alexander Yu. Drozdov
  • Oleg Sergiyenko
  • Ramin Yahyapour
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 796)


In this paper, we address the problem of power-aware Virtual Machines (VMs) consolidation considering resource contention. Deployment of VMs can greatly influence host performance, especially, if they compete for resources on insufficient hardware. Performance can be drastically reduced and energy consumption increased. We focus on a bi-objective experimental evaluation of scheduling strategies for CPU and memory intensive jobs regarding the quality of service (QoS) and energy consumption objectives. We analyze energy consumption of the IBM System x3650 M4 server, with optimized performance for business-critical applications and cloud deployments built on IBM X-Architecture. We create power profiles for different types of applications and their combinations using SysBench benchmark. We evaluate algorithms with workload traces from Parallel Workloads and Grid Workload Archives and compare their non-dominated Pareto optimal solutions using set coverage and hyper volume metrics. Based on the presented case study, we show that our algorithms can provide the best energy and QoS trade-offs.


Virtual machine Consolidation Energy aware scheduling SLA violations Green cloud 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.CICESE Research CenterEnsenadaMexico
  2. 2.South Ural State UniversityChelyabinskRussia
  3. 3.Moscow Institute of Physics and Technology, State UniversityMoscowRussia
  4. 4.Universidad Autónoma de Baja CaliforniaMexicaliMexico
  5. 5.University of GöttingenGöttingenGermany

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