Abstract
Providing high performance to large systems based on service-oriented architecture is a difficult issue. Such systems are composed of a big number of interacting composite services, each consisting of one or several applications. To process jobs that income to such a system collaboration between several applications is needed and processing time will be influenced by choice of a set of applications, resources that they have and time consumed to exchange data between them. For effective hardware resources utilization virtualization technologies are used. Applications that implement services functionality are placed in virtual machines, deployed in a number of physical servers. One of main advantages of a service-oriented architecture is scalability that leads to frequent changes in applications set, their placement in virtual machines and resources available to them. To provide high performance jobs queuing is needed to choose optimal set and order of applications for processing. Efficiency of jobs queuing algorithms highly depends on up-to-date information about every object in a system: applications, virtual machines, physical servers and telecommunications. That, because of inconsistency in configuration may become difficult. One of the proven methods of choosing a set of interacting services to process a complex job is use of ontologies. In this paper an extension to this method is proposed to increase performance of a system. Ontology that describes not only functional abilities of services but also information about their current performance and communicative abilities is described.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
vom Brocke, J., Braccini, A.M., Sonnenberg, C., Spagnoletti, P.: Living IT in frastructures an ontology-based approach to aligning IT infrastructure capacity and business needs. Int. J. Acc. Inf. Syst. 15, 274 (2014)
Ghijsen, M., van der Ham, J., Grosso, P., Dumitru, C., Zhu, H., Zhao, Z., De Laa, C.: A semantic-web approach for modeling computing infrastructures. Comput. Electr. Eng. 39, 2553–2565 (2013)
Li, W., Zhong, Y., Wang, X., Cao, Y.: Resource virtualization and service selection in cloud logistics. J. Netw. Comput. Appl. 36, 1696–1704 (2013)
Liu, M., Shen, W., Haob, Q., Yana, J.: An weighted ontology-based semantic similarity algorithm for web service. Expert Syst. Appl. 36, 12480–12490 (2009)
Medjahed, B., Bouguettaya, A., Elmagarmid, A.K.: Composing web services on the semantic web. Int. J. Very Large Data Bases 12, 333–351 (2003)
Nguyen, T., Loke, S.W., Torabi, T., Lu, H.: On the practicalities of place-based virtual communities: ontology-based querying, application architecture, and performance. Expert Syst. Appl. 41, 2859–2873 (2014)
Sun, L., Ma, J., Zhang, Y., Dong, H., Hussain, F.K.: Cloud-FuSeR: fuzzy ontology and MCDM based cloud service selection. Future Gener. Comput. Syst. 57, 42–55 (2016)
Teslya, N., Smirnov, A., Levashova, T., Shilov, N.: Ontology for resource self-organisation in cyber-physical-social systems. In: Klinov, P., Mouromtsev, D. (eds.) KESW 2014. CCIS, vol. 468, pp. 184–195. Springer, Heidelberg (2014)
Zubok, D.A., Maiatin, A.V., Khegai, M.V.: Ontology-based approach in the scheduling of jobs processed by applications running in virtual environments. In: Klinov, P., Mouromtsev, D. (eds.) Knowledge Engineering and the Semantic Web, vol. 518, pp. 273–282. Springer, Heidelberg (2015)
Zubok, D.A., Maiatin, A.V., Kiryushkina, V.E., Khegai, M.V.: Functional model of a software system with random time horizon, pp. 259–266 (2015)
Acknowledgements
This work was partially financially supported by the Government of Russian Federation, Grant 074-U01. The presented result is also a part of the research carried out within the project funded by grant #15-07-09229 A of the Russian Foundation for Basic Research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Khegai, M., Zubok, D., Kharchenko, T., Maiatin, A. (2016). Ontology for Performance Control in Service-Oriented System with Composite Services. In: Ngonga Ngomo, AC., Křemen, P. (eds) Knowledge Engineering and Semantic Web. KESW 2016. Communications in Computer and Information Science, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-45880-9_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-45880-9_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-45879-3
Online ISBN: 978-3-319-45880-9
eBook Packages: Computer ScienceComputer Science (R0)