TY - GEN
T1 - Survivable virtual infrastructure mapping in virtualized data centers
AU - Xu, Jielong
AU - Tang, Jian
AU - Kwiat, Kevin
AU - Zhang, Weiyi
AU - Xue, Guoliang
PY - 2012
Y1 - 2012
N2 - In a virtualized data center, survivability can be enhanced by creating redundant Virtual Machines (VMs) as backup for VMs such that after VM or server failures, affected services can be quickly switched over to backup VMs. To enable flexible and efficient resource management, we propose to use a service-aware approach in which multiple correlated VMs and their backups are grouped together to form a Survivable Virtual Infrastructure (SVI) for a service or a tenant. A fundamental problem in such a system is to determine how to map each SVI to a physical data center network such that operational costs are minimized subject to the constraints that each VM's resource requirements are met and bandwidth demands between VMs can be guaranteed before and after failures. This problem can be naturally divided into two sub-problems: VM Placement(VMP) and Virtual Link Mapping (VLM). We present a general optimization framework for this mapping problem. Then we present an efficient algorithm for the VMP sub problem as well as a polynomial-time algorithm that optimally solves the VLM sub problem, which can be used as subroutines in the framework. We also present an effective heuristic algorithm that jointly solves the two sub problems. It has been shown by extensive simulation results based on the real VM data traces collected from the green data center at Syracuse University that compared with the First Fit Descending (FFD) and single shortest path based baseline algorithm, both our VMP+VLM algorithm and joint algorithm significantly reduce the reserved bandwidth, and yield comparable results in terms of the number of active servers.
AB - In a virtualized data center, survivability can be enhanced by creating redundant Virtual Machines (VMs) as backup for VMs such that after VM or server failures, affected services can be quickly switched over to backup VMs. To enable flexible and efficient resource management, we propose to use a service-aware approach in which multiple correlated VMs and their backups are grouped together to form a Survivable Virtual Infrastructure (SVI) for a service or a tenant. A fundamental problem in such a system is to determine how to map each SVI to a physical data center network such that operational costs are minimized subject to the constraints that each VM's resource requirements are met and bandwidth demands between VMs can be guaranteed before and after failures. This problem can be naturally divided into two sub-problems: VM Placement(VMP) and Virtual Link Mapping (VLM). We present a general optimization framework for this mapping problem. Then we present an efficient algorithm for the VMP sub problem as well as a polynomial-time algorithm that optimally solves the VLM sub problem, which can be used as subroutines in the framework. We also present an effective heuristic algorithm that jointly solves the two sub problems. It has been shown by extensive simulation results based on the real VM data traces collected from the green data center at Syracuse University that compared with the First Fit Descending (FFD) and single shortest path based baseline algorithm, both our VMP+VLM algorithm and joint algorithm significantly reduce the reserved bandwidth, and yield comparable results in terms of the number of active servers.
KW - Cloud computing
KW - data center
KW - service-aware
KW - survivability
KW - virtual machine management
UR - http://www.scopus.com/inward/record.url?scp=84866774504&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84866774504&partnerID=8YFLogxK
U2 - 10.1109/CLOUD.2012.100
DO - 10.1109/CLOUD.2012.100
M3 - Conference contribution
AN - SCOPUS:84866774504
SN - 9780769547558
T3 - Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012
SP - 196
EP - 203
BT - Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012
T2 - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012
Y2 - 24 June 2012 through 29 June 2012
ER -