TY - GEN
T1 - Virtual data center allocation with dynamic clustering in clouds
AU - Shi, Li
AU - Katramatos, Dimitrios
AU - Yu, Dantong
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2015/1/20
Y1 - 2015/1/20
N2 - Clouds are being widely used for leasing resources to users in the form of on-demand virtual data centers, which comprise sets of virtual machines interconnected by sets of virtual links. Given a user request for a virtual data center with specific resource requirements, a critical problem is to select a set of servers and links in the physical data center of a cloud to satisfy the request in a manner that minimizes the amount of reserved resources. In this paper, we study the main aspects of this Virtual Data Center Allocation (VDCA) problem, and decompose it into three subproblems: virtual data center clustering, virtual machine allocation, and virtual link allocation. We prove the NP-hardness of VDCA and propose an algorithm that solves the problem by dynamically clustering the requested virtual data center and jointly optimizing virtual machine and virtual link allocation. We further compare the performance and scalability of the proposed algorithm with two existing algorithms, called LoCo and SecondNet, through simulations. We demonstrate that our algorithm generates 30%-200% more revenue than LoCo and 55%-300% than SecondNet, while being up to 12 times faster.
AB - Clouds are being widely used for leasing resources to users in the form of on-demand virtual data centers, which comprise sets of virtual machines interconnected by sets of virtual links. Given a user request for a virtual data center with specific resource requirements, a critical problem is to select a set of servers and links in the physical data center of a cloud to satisfy the request in a manner that minimizes the amount of reserved resources. In this paper, we study the main aspects of this Virtual Data Center Allocation (VDCA) problem, and decompose it into three subproblems: virtual data center clustering, virtual machine allocation, and virtual link allocation. We prove the NP-hardness of VDCA and propose an algorithm that solves the problem by dynamically clustering the requested virtual data center and jointly optimizing virtual machine and virtual link allocation. We further compare the performance and scalability of the proposed algorithm with two existing algorithms, called LoCo and SecondNet, through simulations. We demonstrate that our algorithm generates 30%-200% more revenue than LoCo and 55%-300% than SecondNet, while being up to 12 times faster.
UR - http://www.scopus.com/inward/record.url?scp=84983112881&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983112881&partnerID=8YFLogxK
U2 - 10.1109/PCCC.2014.7017105
DO - 10.1109/PCCC.2014.7017105
M3 - Conference contribution
AN - SCOPUS:84983112881
T3 - 2014 IEEE 33rd International Performance Computing and Communications Conference, IPCCC 2014
BT - 2014 IEEE 33rd International Performance Computing and Communications Conference, IPCCC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd IEEE International Performance Computing and Communications Conference, IPCCC 2014
Y2 - 5 December 2014 through 7 December 2014
ER -