Ontology for Performance Control in Service-Oriented System with Composite Services
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.
KeywordsOntology Performance optimization Service-oriented architecture Queuing
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.
- 1.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)Google Scholar
- 8.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)Google Scholar
- 9.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)CrossRefGoogle Scholar
- 10.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)Google Scholar