Resource management in modern data centers has become a challenging task due to the tremendous growth of data centers. In large virtual data centers, performance of applications is highly dependent on the communication bandwidth available among virtual machines. Traditional algorithms either do not consider network I/O details of the applications or are computationally intensive. We address the problem of identifying the virtual machine clusters based on the network traffic and placing them intelligently in order to improve the application performance and optimize the network usage in large data center. We propose a greedy consolidation algorithm that ensures the number of migrations is small and the placement decisions are fast, which makes it practical for large data centers. We evaluated our approach on real world traces from private and academic data centers, using simulation and compared the existing algorithms on various parameters like scheduling time, performance improvement and number of migrations. We observed a ∼70% savings of the interconnect bandwidth and overall ∼60% improvements in the applications performances. Also, these improvements were produced within a fraction of scheduling time and number of migrations.  Categories and Subject Descriptors Algorithms Keywords network-aware placement, virtual machine scheduling Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org.
REF presented a VM grouping mechanism based on network traffic history within a data center at run-time and proposed a fast, greedy VM consolidation algorithm in order to improve hosted applications performance and optimize the network usage by saving internal bandwidth.
Network-aware virtual machine consolidation for large data centers
NDM '13
Computer Science