Abstract
Cloud computing enables delivery of services on-demand networks. Cloud servers with set of resources can response to different user requirements. However, allocating resources to various tasks is still a challenging problem. In this paper in order to provide dynamic resource allocation, we propose alienable services, which improves demanded resources allocation. Our experimental results show the performance of the proposed approach is a factor of 1.47 compared to the common service base models.
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
Wang, L., Laszewski, G., Kunze, M., Tao, J.: Cloud computing: A perspective study. In: Proc. Grid Computing Environments Workshop (2008)
Chang, M., He, J., Leon, E.C.: Service-oriented in the computing infrastructure. In: Proc. IEEE Int. Symp. on Service-Oriented System Engineering (2006)
Armbrust, M., Fox, A., Griffith, R., Joseph, A., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: A view of cloud computing. Communications of the ACM 53(4), 50–58 (2010)
The NIST Definition of Cloud Computing, http://www.csrc.nist.gov
Deelman, E., Singh, G., Livny, M., Berriman, B., Good, J.: The cost of doing science on the cloud: the montage example. ACM/IEEE Conf. on Supercomputing, 1–12 (2008)
Randles, M., Lamb, D., Bendiab, A.T.: A comparative study into distributed load balancing algorithms for cloud computing. In: Proc. IEEE Int. Advanced Information Networking and Applications Workshop, pp. 551–556 (2010)
Zhang, B., Gao, J., Ai, J.: Cloud loading balance algorithm. In: IEEE Int. Conf. on Information Science and Engineering (2011)
Yau, S., An, H.: Adaptive resource allocation for service-based systems. Journal of Software Informatics 3(4), 483–499 (2009)
Riad, A., Hassan, Q.: Service-oriented architecture: A new alternative to traditional integration methods in b2b applications. Journal of Convergence Information Technology 3(1), 41 (2008)
Walsh, W.E., Tesauro, G., Kephart, J.O., Das, R.: Utility functions in autonomic systems. In: Proc. IEEE Int. Conf. on Autonomic Computing, pp. 70–77 (2004)
Adam, C., Stadler, R.: Service middleware for self-managing large-scale systems. IEEE Trans. on Network and Service Management 4(3), 50–64 (2008)
Yazir, Y.O., Matthews, C., Farahbod, R., Neville, S., Guitouni, A., Ganti, S., Coady, Y.: Dynamic resource allocation in computing clouds using distributed multiple criteria decision analysis. In: IEEE Int. Conf. on Cloud Computing, pp. 91–98 (2010)
Ranjan, R.: Coordinated resource provisioning in federated grids. Ph.D. thesis, The University of Melbourne, Australia (2009)
Crawford, C.H., Bate, G.P., Cherbakov, L., Holly, K.L., Tsocanos, C.: Toward an on demand service oriented architecture. IBM Systems Journal 44(1), 81–107 (2005)
Pasley, J.: How bpel and soa are changing web services development. In: IEEE Int. Conf. on Computing (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Salehpour, M., Shahbahrami, A. (2011). Alienable Services for Cloud Computing. In: Brazier, F.M.T., Nieuwenhuis, K., Pavlin, G., Warnier, M., Badica, C. (eds) Intelligent Distributed Computing V. Studies in Computational Intelligence, vol 382. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24013-3_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-24013-3_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24012-6
Online ISBN: 978-3-642-24013-3
eBook Packages: EngineeringEngineering (R0)