Compatibility-based static VM placement minimizing interference. (15th April 2017)

• Record Type: Journal Article
• Authors: Rahman, Mahfuzur; Graham, Peter
• Is Part Of: Journal of network and computer applications. Volume 84(2017)
• Page Start: 68
• Page End: 81
• Publication Date: 2017-04-15
• Subjects: Resource provisioning -- Cloud computing -- VM consolidation -- Optimization; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2017.02.004
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: The static (or initial) packing of VMs into a cloud provided host is done based on their expected resource requirements as specified in Service Level Agreements (SLAs). SLAs in Infrastructure as a Service (IaaS) clouds, however, capture neither changes in requirements over a VM's lifetime nor their dynamic characteristics (e.g. cache behaviour). Placing VMs for packing efficiency alone can result in "incompatible" VMs being co-located that interfere with one another's executions. This can result in the need for costly early VM migrations. In this paper, we address this problem by introducing Compatibility-based Static VM Placement (CSVP). CSVP contributes by exploiting easy-to-obtain information about VMs' expected load variation to co-locate compatible VMs within a scheduling batch together thereby improving their initial performance. We have implemented CSVP in CloudSim and done simulations using workloads derived from a subset of the Google traces. Our results show that even using only simple threshold information about VM behaviour CSVP provides better initial VM placements to avoid some VM interference. Using CSVP, VMs are thus more likely to execute effectively together from their start thereby decreasing the overhead of VM migration. Abstract : Highlights: A new compatibility-based static algorithm for initial VM placement in IaaS clouds. Compatibility assessment can be done via a simple, low-cost threshold approach. Multi-criterion compatibility assessment is effectively supported. Simulation with a GoogleTrace subset shows consistent improvement over FFD.