Simple Destination-Swap Strategies for Adaptive Intra- and Inter-Tenant VM Migration

Simple Destination-Swap Strategies for Adaptive Intra- and Inter-Tenant VM Migration

Abstract

This paper investigates the opportunities and limitations of adaptive virtual machine (VM) migration to reduce communication costs in a virtualized environment. We introduce a new formal model for the problem of online VM migration in two scenarios: (1) VMs can be migrated arbitrarily in the substrate network; e.g., a private cloud provider may have an incentive to reduce the overall communication cost in the network. (2) VMs can only be migrated within a given tenant; e.g., a user that was assigned a set of physical machines may exchange the functionality of the VMs on these machines. We propose a simple class of Destination-Swap algorithms which are based on an aggressive collocation strategy (inspired by splay datastructures) and which maintain a minimal and local amount of per-node (amortized cost) information to decide where to migrate a VM and how; thus, the algorithms react quickly to changes in the load. The algorithms come in two main flavors, an indirect and distributed variant which keeps existing VM placements local, and a direct variant which keeps the number of affected VMs small. We show that naturally, inter-tenant optimizations yield a larger potential for optimization, but generally also a tenant itself can improve its embedding. Moreover, there exists an interesting tradeoff between direct and indirect strategies: indirect variants are preferable under skewed and sparse communication patterns due to their locality properties.

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Authors
  • Avin, Chen
  • Dunay, Omer
  • Schmid, Stefan
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Supplemental Material
Shortfacts
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
6th IEEE/ACM International Conference on Utility and Cloud Computing (UCC)
Divisions
Communication Technologies
Subjects
Informatik Allgemeines
Event Location
Dresden, Germany
Event Type
Conference
Event Dates
December 2013
Date
2013
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