Abstract
Cloud computing and high performance computing enable service providers to support parallel execution of provided services. Consider a client who invokes a web service to process a large dataset. The input data is split into independent partitions and multiple partitions are sent to the service concurrently. A typical customer would expect the service speedup to be directly proportional to the number of concurrent requests (or the degree of parallelism - DOP). However, we obtained that the achieved speedup is not always directly proportional to the DOP. This may because service providers employ parallel execution policies for their services based on arbitrary decisions. The goal of this paper is to analyse the performance improvement behavior of web services under parallel execution. We introduce a model of parallel execution policy of web services with three policies: Slow-down, Restriction and Penalty policies. We conduct analyses to evaluate our model. Interestingly, the results show that our model have a good accuracy in capturing parallel execution behavior of web services.
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
Notes
- 1.
Web services on the LG: http://langrid.org/service_manager/language-services.
- 2.
ProgrammableWeb: http://www.programmableweb.com/.
- 3.
Apache UIMA: http://uima.apache.org/.
References
Alba, E.: Parallel evolutionary algorithms can achieve super-linear performance. Inf. Process. Lett. 82(1), 7–13 (2002)
Almeida, J., Almeida, V., Ardagna, D., Cunha, Í., Francalanci, C., Trubian, M.: Joint admission control and resource allocation in virtualized servers. J. Parallel Distrib. Comput. 70(4), 344–362 (2010)
Amdahl, G.M.: Validity of the single processor approach to achieving large scale computing capabilities. In: Proceedings of the Spring Joint Computer Conference, pp. 483–485. ACM (1967)
Bonetta, D., Peternier, A., Pautasso, C., Binder, W.: S: a scripting language for high-performance restful web services. ACM SIGPLAN Not. 47(8), 97–106 (2012)
Ishida, T. (ed.): The Language Grid: Service-Oriented Collective Intelligence for Language Resource Interoperability. Cognitive Technologies. Springer, Heidelberg (2011)
Gusev, M., Ristov, S., Velkoski, G., Simjanoska, M.: Optimal resource allocation to host web services in cloud. In: Proceedings of the Sixth IEEE International Conference on Cloud Computing (CLOUD), pp. 948–949. IEEE (2013)
Ristov, S., Velkoski, G., Gusev, M., Kjiroski, K.: Compute and memory intensive web service performance in the cloud. In: Markovski, S., Gushev, M. (eds.) ICT Innovations 2012. AISC, vol. 207, pp. 215–224. Springer, Heidelberg (2013)
Ristov, S., Gusev, M., Velkoski, G.: Modeling the speedup for scalable web services. In: Bogdanova, A.M., Gjorgjevikj, D. (eds.) ICT Innovations 2014. AISC, vol. 311, pp. 177–186. Springer, Heidelberg (2015)
Sun, X.-H., Chen, Y.: Reevaluating amdahls law in the multicore era. J. Parallel Distrib. Comput. 70(2), 183–188 (2010)
Tallent, N.R., Mellor-Crummey, J.M.: Effective performance measurement and analysis of multithreaded applications. In: ACM Sigplan Notices, vol. 44, no. 4, pp. 229–240. ACM (2009)
Tentov, A., et al.: Performance impact correlation of message size vs. concurrent users implementing web service security on linux platform. In: Kocarev, L. (ed.) ICT Innovations 2011. AISC, vol. 150, pp. 367–377. Springer, Heidelberg (2012)
Trang, M.X., Murakami, Y., Lin, D., Ishida, T.: Integration of workflow and pipeline for language service composition. In: Proceedings of the 9th edn. of the Language Resources and Evaluation Conference (LREC ), pp. 3829–3836 (2014)
Trang, M.X., Murakami, Y., Ishida, T.: Policy-aware optimization of parallel execution of composite service. In: Proceedings of the 12th IEEE International Conference on Services Computing (SCC), pp. 106–113. IEEE (2015)
Acknowledgments
This research was partly supported by a Grant-in-Aid for Scientific Research (S) (24220002, 2012-2016) from Japan Society for Promotion of Science (JSPS).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Trang, M.X., Murakami, Y., Ishida, T. (2016). Modeling Parallel Execution Policies of Web Services. In: Zhang, Y., Peng, L., Youn, CH. (eds) Cloud Computing. CloudComp 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 167. Springer, Cham. https://doi.org/10.1007/978-3-319-38904-2_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-38904-2_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-38903-5
Online ISBN: 978-3-319-38904-2
eBook Packages: Computer ScienceComputer Science (R0)