Abstract
Cloud computing is a growing technology where lot of heterogeneous resources are available and large amount of requests are submitted by the customers simultaneously. So it is difficult to match the requests and resources based on the expectations of customers and providers. This paper proposes the resource allocation using auction based technique to reduce the complexity of providing the resources for customers job execution and fulfill the expectations of both customers and providers in cloud environment. In the proposed work the Enhanced Multi-attribute Combinative Double Auction (EMCDA) resource allocation algorithm is used to conduct the auction to the customers bids with the providers bids by the cloud auctioneer for finding the best customer-providers pairs and achieves the customers and providers satisfaction using the normalization factors during price calculation in the cloud computing environment. The experimental result demonstrates that the proposed Enhanced Multi-attribute Combinative Double Auction (EMCDA) resource allocation algorithm performs efficiently than the existing Combinatorial Double Auction Resource Allocation (CDARA) model. The proposed EMCDA model is incentive-compatible, which encourage the participants of an auction to reveal their true valuation during bidding.
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Shang, S., Jiang, J, Wu, Y., Huang, Z., G. Yang, W. Zheng, (2010). DABGPM: A double auction bayesian game-based pricing model in cloud market, Network and Parallel Computing, pp. 155–164.
Jiang, C., Duan, L., Liu, C., Wan, J., Zhou, L., (2012). VRAA: Virtualized resource auction and allocation based on incentive and penalty, Cluster Computing. pp. 1–12.
Wang, X., Sun, J., Huang, M., Wu, C. (2012). A resource auction based allocation mechanism in the cloud computing environment. In: 26th IEEE International parallel and Distributed Processing Symposium Workshops & Phd Forum (IPDPSW), pp. 2111–2115.
Samimi, P., Teimouri, Y., & Mukhtar, M. (2016). A Combinatorial double auction resource allocation model in cloud computing. Elsevier, Information Sciences, 357, 201–216.
Lin W. Y., Lin G. Y., Wei H. Y., (2010). Dynamic auction mechanism for cloud resource allocation.10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid) IEEE, pp.591–592.
Zaman, S., & Grosu, D. (2013). Combinatorial auction-based allocation of virtual machine instances in clouds. Journal of Parallel and Distributed Computing, 73(4), 495–508.
Xing-Wei W., Xue-yi W., Min H., (2012). A resource allocation method based on the limited English combinatorial auction under cloud computing environment. In: 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, pp. 905–909.
Song B., Hassan M. M., Huh E. N., (2009). A novel cloud market infrastructure for trading service. International Conference on Computational Science and its Applications (ICCSA’09). IEEE, pp. 44–50.
Shang S., Jiang J., Wu Y., Yang G., & Zheng W., (2010). A knowledge-based continuous double auction model for cloud market. 6th International Conference on Semantics Knowledge and Grid (SKG). IEEE, pp. 129–134.
Sun J., Wang X., Huang M., & Gao C., (2013). A cloud resource allocation scheme based on microeconomics and wind driven optimization. 8th China Grid Annual Conference (ChinaGrid). IEEE, pp. 34–39.
Baranwal, G., & Vidyarthi, D. P. (2015). A fair multi-attribute combinatorial double auction model for resource allocation in cloud computing. The Journal of Systems and Software, 108, 60–76.
Li, L., Liu, Y.-A., Liu, K.-M., Ma, X.-L., & Yang, M. (2009). Pricing in combinatorial double auction-based grid allocation model. The Journal of China Universities of Posts and Telecommunications, 16(3), 59–65.
Izakian, H., Abraham, A., & Ladani, B. T. (2010). An auction method for resource allocation in computational grids. Future Generation Computer Systems, 26(2), 228–235.
Tang, R., Yue, Y., Ding, X., & Qiu, Y. (2014). Credibility-based cloud media resource allocation algorithm. Journal of Network and Computer Applications, 46, 315–321.
Wang, X., Wang, X., Che, H., Li, K., Huang, M., & Gao, C. (2015). An intelligent economic approach for dynamic resource allocation in cloud services. IEEE Transactions on Cloud Computing, 3(3), 275–289.
Wang, X., Wang X., Wang C.-L., Li K., Huang M., (2014b). Resource allocation in Cloud environment: a model based on double multi-attribute auction mechanism. IEEE 6th International Conference on Cloud Computing Technology and Science. IEEE, pp. 599–604.
Li, H., Wu, C., Li, Z., Lau, F., (2013). Virtual machine trading in a federation of clouds: Individual profit and social welfare maximization, IEEE/ACM Transactions on Networking, pp. 1827–1840.
Zheng, Z., Gui, Y., Wu, F., & Chen, G. (2014). STAR: Strategy-proof double auctions for multi-cloud, multi-tenant bandwidth reservation. IEEE Transactions on Computers, 64(7), 2071–2083.
Lee J.S., Szymanski B.K., (2005). A novel auction mechanism for selling time-sensitive e-services. 7th IEEE International Conference on E-Commerce Technology. pp. 75–83.
Chichin, S., Vo, Q.B., Kowalczyk, R., (2015). Towards efficient Greedy allocation schemes for double-sided cloud markets. IEEE International Conference on Services Computing (SCC). pp. 194–201.
Sun, Z., Zhu, Z., Chen, L., Xu, H., Huang, L., (2015). A combinatorial double auction mechanism for cloud resource group-buying. IEEE 33rd International Performance Computing and Communications Conference (IPCCC), pp. 1–8.
Wu, X., Liu, M., Dou, W. C., Gao, L., & Yu, S. (2016). A scalable and automatic mechanism for resource allocation in self-organizing cloud. Peer-to-Peer Networking and Applications, 9(1), 28–41.
Sabzevari, R. A., & Nejad, E. B. (2015). Double combinatorial auction based resource allocation in Cloud computing by combinational using of ICA and genetic algorithms. International Journal of Computer Applications, 110(12), 1–6.
Prodan, R., Wieczorek, M., & Fard, H. M. (2011). Double auction-based scheduling of scientific applications in distributed grid and cloud environments. Journal of Grid Computing, 9(4), 531–548.
Xu, K., Zhang, Y., Shi, X., Wang, H., Wang Y., Shen M., (2014). Online combinatorial double auction for mobile cloud computing markets. IEEE 33rd International Performance Computing and Communications Conference (IPCCC), pp. 1–8.
Farajian, N., Zamanifar, K., (2013). Market-driven continuous double auction method for service allocation in cloud computing. International Conference on Advances in Computing, Communication and Control, Springer, pp. 14–24.
Singhal, R., & Singhal, A. (2021). A feedback-based combinatorial fair economical double auction resource allocation model for cloud computing. Future Generation Computer Systems, 115, 780–797.
Zhang, J., Yang, X., Xie, N., Zhang, X., Vasilakos, A. V., & Li, W. (2020). An online auction mechanism for time-varying multidimensional resource allocation in clouds. Future Generation Computer Systems, 111, 27–38.
Reza Dibaj, S. M., Miri, A., & Mostafavi, SeyedAkbar. (2020). A cloud priority-based dynamic online double auction mechanism (PB-DODAM). Journal of Cloud Computing, 9(1), 1–26.
Chen, X., Wang, H., Ma, Y., Zheng, X., & Guo, L. (2019). Self-adaptive resource allocation for cloud-based software services based on iterative QoS prediction model. Future Generation Computer Systems., 105(1), 287–296.
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Vinothiyalakshmi, P., Anitha, R. Enhanced Multi-attribute Combinative Double Auction (EMCDA) for Resource Allocation in Cloud Computing. Wireless Pers Commun 122, 3833–3857 (2022). https://doi.org/10.1007/s11277-021-09113-8
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DOI: https://doi.org/10.1007/s11277-021-09113-8