Skip to main content
Log in

Optimization-based resource allocation for software as a service application in cloud computing

  • Published:
Journal of Scheduling Aims and scope Submit manuscript

Abstract

Software as a service (SaaS) is a software that is developed and hosted by the SaaS vendor. SaaS cloud provides software as services to the users through the internet. To provide good quality of service for the user, the SaaS relies on the resources leased from infrastructure as a service cloud providers. As the SaaS services rapidly expand their application scopes, it is important to optimize resource allocation in SaaS cloud. The paper presents optimization-based resource allocation approach for software as a service application in cloud. The paper uses optimization decomposition approach to solve cloud resource allocation for satisfying the cloud user’s needs and the profits of the cloud providers. The paper also proposes a SaaS cloud resource allocation algorithm. The experiments are designed to compare the performance of the proposed algorithm with other two related algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Abhishek, V., Zenia, P. G., Noella, F., & Flavin, C. (2015). Cloud computing using OCRP and virtual machines for dynamic allocation of resources. Technologies for sustainable development (ICTSD), 2015 International Conference on (pp 1–5)

  • Abdul, H., Alireza, K., & Rajiv, R. (2014). A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems. Computing, 98(7), 1–24.

    Google Scholar 

  • Abhinandan, S. P., & Shrisha, R. (2014). A mechanism design approach to resource procurement in cloud computing. IEEE Transactions on Computers, 63(1), 17–30.

    Article  Google Scholar 

  • Al-Ayyoub, M., Jararweh, Y., Daraghmeh, M., & Althebyan, Q. (2015). Multi-agent based dynamic resource provisioning and monitoring for cloud computing systems infrastructure. Cluster Computing, 18(2), 919–932.

    Article  Google Scholar 

  • Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., et al. (2010). A view of cloud computing. Communications of the ACM, 53, 50–58.

    Article  Google Scholar 

  • Bo, A., Lesser, V., Irwin, D., et al. (2010). Automated negotiation with decommitment for dynamic resource allocation in cloud computing. In Proceedings of the 9th international conference on autonomous agents and multiagent systems, AAMAS ’10 (Vol. 1, pp. 981–988)

  • Chaisiri, S., Lee, B.-S., & Niyato, D. (2012). Optimization of resource provisioning cost in cloud computing. IEEE Transactions on Services Computing, 5(2), 164–177.

    Article  Google Scholar 

  • Cheng, Y., Chen, Y., Wei, R., & Luo, H. (2015). Development of a construction quality supervision collaboration system based on a SaaS private cloud. Journal of Intelligent & Robotic Systems, 79(3), 613–627.

    Article  Google Scholar 

  • Chrysa, P., Leivadeas, A., Papavassiliou, S., Maglaris, V., Cervello’-Pastor, C., & Monje, A. (2013). On the optimal allocation of virtual resources in cloud computing networks. IEEE Transactions on Computers, 62(6), 1060–1071.

  • CloudSim. (2014). www.cloudbus.org/cloudsim/

  • Erdil, D. C. (2012). Simulating peer-to-peer cloud resource scheduling. Peer-to-Peer Networking and Applications, 5(3), 219–230.

    Article  Google Scholar 

  • Florin, P., Dobre, C., Cristea, V., Bessis, N., Xhafa, F., & Barolli, L. (2015). Deadline scheduling for aperiodic tasks in inter-Cloud environments a new approach to resource management. The Journal of Supercomputing, 71(5), 1754–1765.

    Article  Google Scholar 

  • Hassan, M. M., Hossain, M. S., Sarkar, A. M. J., & Huh, E.-N. (2014). Cooperative game-based distributed resource allocation in horizontal dynamic cloud federation platform. Information Systems Frontiers, 16(4), 523–542.

    Article  Google Scholar 

  • Kang, Z., & Hongbing, W. (2013). A novel approach to allocate cloud resource with different performance traits. In Services Computing (SCC), 2013 IEEE International Conference on (pp 128–135)

  • Kim, H.-Woo., Park, J. H., & Jeong, Y.-S. (2016). Human-centric storage resource mechanism for big data on cloud service architecture. The Journal of Supercomputing, 72(7), 2437–2452.

  • Lee, H. M., Jeong, Y.-S., & Jang, H. J. (2014). Performance analysis based resource allocation for green cloud computing. The Journal of Supercomputing, 69(3), 1013–1026.

  • Lien, D., Bert, V., Pieter, S., Filip, D. T., Bart, D., & Piet D. (2012). Efficient resource management for virtual desktop cloud computing. The Journal of Supercomputing, 62(2), 741–767.

  • Li, C., & Li, L. (2013). Efficient resource allocation for optimizing objectives of cloud user, IaaS provider and SaaS provider in cloud environment. Journal of Supercomputing, 65(2), 866–885.

    Article  Google Scholar 

  • Li, C., & Li, L. (2014). Phased scheduling for resource-constrained mobile devices in mobile cloud computing. Wireless Personal Communications, 77(4), 2817–2837. (Springer-Verlag).

    Article  Google Scholar 

  • Pattanaik, P. A,, Roy, S., & Pattnaik, P. K. (2015). Performance study of some dynamic load balancing algorithms in cloud computing. In Signal processing and integrated networks (SPIN), 2015 2nd International Conference on (pp 619–624)

  • Son, S., Jung, G., & Jun, S. C. (2013). An SLA-based cloud computing that facilitates resource allocation in the distributed data centers of a cloud provider. The Journal of Supercomputing, 64(2), 606–637.

    Article  Google Scholar 

  • Spotcloud. (2014). Cloud capacity clearing house: spot market: Home. http://www.spotcloud.com

  • Steffen, B., & Matthias, T., (2012). Towards model-driven evolution of performance critical business information systems to cloud computing architectures. Softwaretechnik-Trends, 32(2), 7–8.

  • Sukhpal, S., & Inderveer, C. (2015). QRSF QoS-aware resource scheduling framework in cloud computing. The Journal of Supercomputing, 71(1), 241–292.

    Article  Google Scholar 

  • Victor, I. M., Calin, S., & Dana, P. (2014). Multi-cloud resource management cloud service interfacing. Journal of Cloud Computing, 3(1), 1–23.

    Article  Google Scholar 

  • Wang, E. D., Wu N., & Li X. (2013). QoS-oriented monitoring model of cloud computing resources availability. In 2013 Fifth international conference on computational and information sciences (ICCIS) (pp. 1537–1540)

  • Wei, Y., & Brian, B. M. (2016). Proactive virtualized resource management for service workflows in the cloud. Computing, 98(5), 523–538.

    Article  Google Scholar 

  • Wu, L., Garg, S. K., & Buyya, R, (2011). SLA-based resource allocation for a software as a service provider in cloud computing environments. In Proceedings of the 11th IEEE/ACM international symposium on cluster computing and the grid (CCGrid 2011), May 23–26, Los Angeles

Download references

Acknowledgments

The authors thank the editors and the anonymous reviewers for their helpful comments and suggestions. The work was supported by the National Natural Science Foundation (NSF) under grants (Nos. 61472294, 61672397), Key Natural Science Foundation of Hubei Province (No. 2014CFA050), Open Project Program of Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education (No. 201602), Applied Basic Research Project of WuHan (No. 2015010101010021), Program for the High-end Talents of Hubei Province. Any opinions, findings, and conclusions are those of the authors and do not necessarily reflect the views of the above agencies.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chunlin Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, C., Liu, Y.C. & Yan, X. Optimization-based resource allocation for software as a service application in cloud computing. J Sched 20, 103–113 (2017). https://doi.org/10.1007/s10951-016-0491-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10951-016-0491-z

Keywords

Navigation