TY - GEN
T1 - Joint Optimization of Server and Network Resource Utilization in Cloud Data Centers
AU - Zhou, Biyu
AU - Wu, Jie
AU - Wang, Lin
AU - Zhang, Fa
AU - Liu, Zhiyong
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Virtual machine placement is a key component of cloud resource management, which may affect network bandwidth allocation. In this paper, we revisit the virtual machine placement problem in cloud data centers and aim to maximize the overall resource utilization in multiple dimensions, while ensuring that the resource constraints on both the server such as CPU capacity and the network such as bandwidth are not violated. We model the bandwidth-guaranteed virtual machine placement problem and prove its NP-hardness, and design offline and online algorithms to solve the problem. We first consider the offline version and develop approximation algorithms with bounded performance ratios for both the homogeneous and the heterogeneous cases. Then, for the online version, we propose simple and efficient heuristics based on the insights from the offline algorithm design. Comprehensive experimental results verify that the overall resource utilization can be significantly improved by applying our proposals.
AB - Virtual machine placement is a key component of cloud resource management, which may affect network bandwidth allocation. In this paper, we revisit the virtual machine placement problem in cloud data centers and aim to maximize the overall resource utilization in multiple dimensions, while ensuring that the resource constraints on both the server such as CPU capacity and the network such as bandwidth are not violated. We model the bandwidth-guaranteed virtual machine placement problem and prove its NP-hardness, and design offline and online algorithms to solve the problem. We first consider the offline version and develop approximation algorithms with bounded performance ratios for both the homogeneous and the heterogeneous cases. Then, for the online version, we propose simple and efficient heuristics based on the insights from the offline algorithm design. Comprehensive experimental results verify that the overall resource utilization can be significantly improved by applying our proposals.
UR - http://www.scopus.com/inward/record.url?scp=85046375919&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046375919&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2017.8254037
DO - 10.1109/GLOCOM.2017.8254037
M3 - Conference contribution
T3 - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
SP - 1
EP - 6
BT - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Global Communications Conference, GLOBECOM 2017
Y2 - 4 December 2017 through 8 December 2017
ER -