JOURNAL ARTICLE

Scalable Traffic-Aware Virtual Machine Management for Cloud Data Centers

Abstract

Virtual Machine (VM) management is a powerful mechanism for providing elastic services over Cloud Data Centers (DC)s. At the same time, the resulting network congestion has been repeatedly reported as the main bottleneck in DCs, even \nwhen the overall resource utilization of the infrastructure remains low. However, most current VM management strategies are traffic-agnostic, while the few that are traffic-aware only concern a static initial allocation, ignore bandwidth oversubscription, or do not scale.<p></p> \nIn this paper we present S-CORE, a scalable VM migration algorithm to dynamically reallocate VMs to servers while minimizing the overall communication footprint of active traffic flows. We formulate the aggregate VM communication as an optimization problem and we then define a novel distributed migration scheme that iteratively adapts to dynamic traffic changes. Through extensive simulation and implementation results, we show that S-CORE achieves significant (up to 87%) communication cost reduction while incurring minimal overhead and downtime.

Keywords:
Computer science Bottleneck Cloud computing Server Scalability Virtual machine Computer network Distributed computing Downtime Overhead (engineering) Bandwidth (computing) Operating system Embedded system

Metrics

38
Cited By
16.95
FWCI (Field Weighted Citation Impact)
33
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
Software-Defined Networks and 5G
Physical Sciences →  Computer Science →  Computer Networks and Communications
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
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