Abstract
Resource allocation for multi-user across multiple data centers is an important problem in cloud computing environments. Many geographically-distributed users may request virtualized resources simultaneously. And the distances from users to allocated resources have much impact on the quality of service (QoS) in multiple data centers environment. Most existing methods do not take all these factors into account when allocating resources. They usually result in poor runtime performance of users’ virtual computing environment and the remarkable difference of users’ QoS. In this paper, we propose RAMD, a resource allocation algorithm based on multi-stage decision in multiple data centers. The RAMD algorithm allocate VMs to users, taking into account the correlation and interaction between multiple users, so as to minimize the sum of all users’ service distances (i.e. determined by user location and network distance of virtual machines). Experimental results show that the algorithm can effectively deal with the cloud resource allocation for multi-user across multiple data centers. It can improve the runtime performance of users’ virtualized resources and reduce the difference of QoS.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Lu, X., Wang, H., Wang, J., Xu, J., Li, D.: Internet-based virtual computing environment: beyond the data center as a computer. Future Generation Computer Systems 29(1), 309–322 (2013)
SCOPE Alliance. Telecom grade cloud computing (2011), http://www.scope-alliance.org
Gottlieb, A.: Beware the network cost gotchas of cloud computing. Cloud Computing Journal (June 2011)
Meng, X., Pappas, V., Zhang, L.: Improving the scalability of data center networks with traffic-aware virtual machine placement. In: 2010 Proceedings of IEEE INFOCOM, pp. 1–9. IEEE (March 2010)
Hyser, C., Mckee, B., Gardner, R., Watson, B.J.: Autonomic virtual machine placement in the data center. Hewlett Packard Laboratories, Tech. Rep. HPL-2007-189, 2007-189 (2007)
Padala, P., Hou, K.Y., Shin, K.G., Zhu, X., Uysal, M., Wang, Z., Merchant, A.: Automated control of multiple virtualized resources. In: Proceedings of the 4th ACM European Conference on Computer Systems, pp. 13–26. ACM (April 2009)
Mylavarapu, S., Sukthankar, V., Banerjee, P.: An optimized capacity planning approach for virtual infrastructure exhibiting stochastic workload. In: Proceedings of the 2010 ACM Symposium on Applied Computing, pp. 386–390. ACM (March 2010)
Menasce, D., Bennani, M.N.: Autonomic virtualized environments. In: 2006 International Conference on Autonomic and Autonomous Systems, ICAS 2006, p. 28. IEEE (July 2006)
Song, Y., Li, Y., Wang, H., Zhang, Y., Feng, B., Zang, H., Sun, Y.: A service-oriented priority-based resource scheduling scheme for virtualized utility computing. In: Sadayappan, P., Parashar, M., Badrinath, R., Prasanna, V.K. (eds.) HiPC 2008. LNCS, vol. 5374, pp. 220–231. Springer, Heidelberg (2008)
Song, Y., Wang, H., Li, Y., Feng, B., Sun, Y.: Multi-tiered on-demand resource scheduling for VM-based data center. In: Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 148–155. IEEE Computer Society (May 2009)
Zhou, W., Yang, S., Fang, J., Niu, X., Song, H.: Vmctune: A load balancing scheme for virtual machine cluster using dynamic resource allocation. In: 2010 9th International Conference on Grid and Cooperative Computing (GCC), pp. 81–86. IEEE (November 2010)
Wood, T., Shenoy, P., Venkataramani, A., Yousif, M.: Sandpiper: Black-box and gray-box resource management for virtual machines. Computer Networks 53(17), 2923–2938 (2009)
Padala, P., Hou, K.Y., Shin, K.G., Zhu, X., Uysal, M., Wang, Z., Merchant, A.: Automated control of multiple virtualized resources. In: Proceedings of the 4th ACM European Conference on Computer Systems, pp. 13–26. ACM (April 2009)
Xu, W., Zhu, X., Singhal, S., Wang, Z.: Predictive control for dynamic resource allocation in enterprise data centers. In: 10th IEEE/IFIP Network Operations and Management Symposium, NOMS 2006, pp. 115–126. IEEE (April 2006)
Alicherry, M., Lakshman, T.V.: Network aware resource allocation in distributed clouds. In: 2012 Proceedings IEEE INFOCOM, pp. 963–971. IEEE (March 2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, J., Li, D., Zheng, J., Quan, Y. (2014). Location-Aware Multi-user Resource Allocation in Distributed Clouds. In: Wu, J., Chen, H., Wang, X. (eds) Advanced Computer Architecture. Communications in Computer and Information Science, vol 451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44491-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-662-44491-7_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-44490-0
Online ISBN: 978-3-662-44491-7
eBook Packages: Computer ScienceComputer Science (R0)