Patience-Aware Scheduling for Cloud Services: Freeing Users from the Chains of Boredom
Scheduling of service requests in Cloud computing has traditionally focused on the reduction of pre-service wait, generally termed as waiting time. Under certain conditions such as peak load, however, it is not always possible to give reasonable response times to all users. This work explores the fact that different users may have their own levels of tolerance or patience with response delays. We introduce scheduling strategies that produce better assignment plans by prioritising requests from users who expect to receive results earlier and by postponing servicing jobs from those who are more tolerant to response delays. Our analytical results show that the behaviour of users’ patience plays a key role in the evaluation of scheduling techniques, and our computational evaluation demonstrates that, under peak load, the new algorithms typically provide better user experience than the traditional FIFO strategy.
KeywordsCloud Computing Cloud Service Peak Load Schedule Strategy Patience Index
Unable to display preview. Download preview PDF.
- 2.Assunção, M.D., et al.: Context-aware job scheduling for cloud computing environments. In: 5th IEEE Int. Conf. on Utility and Cloud Computing, UCC (2012)Google Scholar
- 4.AuYoung, A., et al.: Service contracts and aggregate utility functions. In: 15th IEEE Int. Symp. on High Performance Distributed Computing, HPDC 2006 (2006)Google Scholar
- 5.Braun, T.D., Siegel, H.J., Beck, N., Bölöni, L.L., Maheswaran, M., Reuther, A.I., Robertson, J.P., Theys, M.D., Yao, B., Hensgen, D., et al.: A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems. Journal of Parallel and Distributed Computing 61(6), 810–837 (2001)CrossRefGoogle Scholar
- 7.Cardonha, C., et al.: Patience-aware scheduling for cloud services: Freeing users from the chains of boredom. arXiv preprint cs/1308.4166 (2013)Google Scholar
- 8.Cunha, C.R., Jaccoud, C.F.B.: Determining www user’s next access and its application to pre-fetching. In: 2nd IEEE Symp. on Computers and Communications (ISCC 1997), Washington, DC, USA, p. 6 (1997)Google Scholar
- 11.Galletta, D.F., Henry, R.M., McCoy, S., Polak, P.: Web site delays: How tolerant are users? Journal of the Association for Information Systems 5(1), 1–28 (2004)Google Scholar
- 13.Kahneman, D., Tversky, A.: Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society, 263–291 (1979)Google Scholar
- 14.Precise and Realistic Utility Functions for User-Centric Performance Analysis of Schedulers (2007)Google Scholar
- 15.Netto, M.A.S., Assunção, M.D., Bianchi, S.: Leveraging attention scarcity to improve the overall user experience of cloud services. In: Proceedings of the IFIP 9th International Conference on Network and Service Management, CNSM 2013 (2013)Google Scholar
- 17.Taylor, S.: Waiting for service: the relationship between delays and evaluations of service. The Journal of Marketing, 56–69 (1994)Google Scholar