Abstract
Interoperable cloud computing is the one in which the services or resources of one cloud can be accessed by another cloud. The implementation of interoperable cloud architecture is a challenging one because various characteristics of the cloud computing environment need to be considered for its achievement. The aim of this work is to implement interoperable cloud computing with the awareness of service-level agreements and to provide adequate resources when shortage of resources occurs at one cloud while providing the agreed services to the user. To achieve this, we proposed a methodology of interoperability-based flexible resource management. Initially, the SLA templates of private and public cloud are mapped using the Soft TF-IDF metric with case-based reasoning (CBR) approach. Then, based on the mapped SLAs, different clusters of cloud providers are formed with the help of K-means clustering technique. And finally, if one of the cloud in a cluster faces the problem of resource shortage, the flexible resource allocation is provided through the adaptive dimensional search algorithm.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Katsaros, G., Kousiouris, G., Gogouvitis, S.V., Kyriazis, D., Menychtas, A., Varvarigou, T.: A self-adaptive hierarchical monitoring mechanism for clouds. J. Syst. Softw. 85(5), 1029–1041 (2012)
Dikaiakos, M.D., Katsaros, D., Mehra, P., Pallis, G., Vakali, A.: Cloud computing: distributed internet computing for it and scientific research. IEEE Internet Comput. 13(5), 10–13 (2009)
Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging it platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener. Comput. Syst. 25(6), 599–616 (2009)
Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., Ghalsasi, A.: Cloud computing the business perspective. Decis. Support Syst. 51(1), 176–189 (2011)
Kaufman, L.M.: Data security in the world of cloud computing. IEEE Secur. Priv. 7(4), 61–64 (2009)
Petcu, D., Macariu, G., Panica, S., Crăciun, C.: Portable cloud applicationsfrom theory to practice. Future Gener. Comput. Syst. 29(6), 1417–1430 (2013)
Ranjan, R.: The cloud interoperability challenge. IEEE Cloud Comput. 1(2), 20–24 (2014)
Hofmann, P., Woods, D.: Cloud computing: the limits of public clouds for business applications. IEEE Internet Comput. 14(6), 90–93 (2010)
Blair, G., Grace, P.: Emergent middleware: tackling the interoperability problem. IEEE Internet Comput. 1, 78–82 (2012)
Rochwerger, B., Breitgand, D., Levy, E., Galis, A., Nagin, K., Llorente, I.M., Montero, R., Wolfsthal, Y., Elmroth, E., Caceres, J., et al.: The reservoir model and architecture for open federated cloud computing. IBM J. Res. Dev. 53(4), 535–545 (2009)
Beloglazov, A., Abawajy, J., Buyya, R.: Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Gener. Comput. Syst. 28(5), 755–768 (2012)
Silaghi, G.C., Şerban, L.D., Litan, C.M.: A time-constrained sla negotiation strategy in competitive computational grids. Future Gener. Comput. Syst. 28(8), 1303–1315 (2012)
Goudarzi, H., Pedram, M.: Multi-dimensional SLA-based resource allocation for multi-tier cloud computing systems. In: 2011 IEEE International Conference on Cloud Computing (CLOUD), pp. 324–331. IEEE (2011)
Abu Sharkh, M., Jammal, M., Shami, A., Ouda, A.: Resource allocation in a network-based cloud computing environment: design challenges. IEEE Commun. Mag. 51(11), 46–52 (2013)
Huang, C.-J., Guan, C.-T., Chen, H.-M., Wang, Y.-W., Chang, S.-C., Li, C.-Y., Weng, C.-H.: An adaptive resource management scheme in cloud computing. Eng. Appl. Artif. Intell. 26(1), 382–389 (2013)
Addis, B., Ardagna, D., Panicucci, B., Squillante, M.S., Zhang, L.: A hierarchical approach for the resource management of very large cloud platforms. IEEE Trans. Dependable Secure Comput. 10(5), 253–272 (2013)
Shen, H., Liu, G.: An efficient and trustworthy resource sharing platform for collaborative cloud computing. IEEE Trans. Parallel Distrib. Syst. 25(4), 862–875 (2014)
Lu, D., Ma, J., Xi, N.: A universal fairness evaluation framework for resource allocation in cloud computing. China Commun. 12(5), 113–122 (2015)
Unger, T., Leymann, F., Mauchart, S., Scheibler, T.: Aggregation of service level agreements in the context of business processes. In: 12th International IEEE Enterprise Distributed Object Computing Conference, EDOC’08, pp. 43–52. IEEE (2008)
Cohen, W.W., Ravikumar, P.D., Fienberg, S.E., et al.: A comparison of string distance metrics for name-matching tasks. IIWeb 2003, 73–78 (2003)
Hasançebi, O., Azad, S.K.: Adaptive dimensional search: a new metaheuristic algorithm for discrete truss sizing optimization. Comput. Struct. 154, 1–16 (2015)
Xiao, Z., Song, W., Chen, Q.: Dynamic resource allocation using virtual machines for cloud computing environment. IEEE Trans. Parallel Distrib. Syst. 24(6), 1107–1117 (2013)
Breskovic, I., Maurer, M., Emeakaroha, V.C., Brandic, I., Dustdar, S.: Cost-efficient utilization of public SLA templates in autonomic cloud markets. In: 2011 Fourth IEEE International Conference on Utility and Cloud Computing (UCC), pp. 229–236. IEEE (2011)
Javadi, B., Thulasiraman, P., Buyya, R.: Cloud resource provisioning to extend the capacity of local resources in the presence of failures. In: 2012 IEEE 14th International Conference on High Performance Computing and Communication and 2012 IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), pp. 311–319. IEEE (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Anithakumari, S., Chandrasekaran, K. (2019). Adaptive Resource Allocation in Interoperable Cloud Services. In: Bhatia, S., Tiwari, S., Mishra, K., Trivedi, M. (eds) Advances in Computer Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 760. Springer, Singapore. https://doi.org/10.1007/978-981-13-0344-9_19
Download citation
DOI: https://doi.org/10.1007/978-981-13-0344-9_19
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-0343-2
Online ISBN: 978-981-13-0344-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)