The problem of effective deployment architecture in SOA

• Autorzy: Woźniak Adrian , Nowicki Tadeusz

Identyfikatory

DOI

10.5604/01.3001.0013.6604

Warianty tytułu

PL

Problem wyznaczania efektywnej architektury wdrożeniowej SOA

• Języki publikacji: EN

Abstrakty

EN

Service Oriented Architecture is popular in many organizations. In particular, it has already deeply rooted in large corporations that need to automate entire business processes and implement them in many systems. It has a unique feature that allows unambiguously indicate service that is to realise business process step. That indication is possible to show directly in BPMN diagram. Thus, it is possible to trace which server has used resources to implement the service and how much of those resources were needed. Therefore, it is possible to build an optimization task that, with limited and unreliable resources, will determine such allocation of components to servers and such an algorithm for assigning tasks to them, so that the processes will work as well as possible. The article presents a model of such an optimization task. This model consists of four layers. The Organization Layer describes the system environment – the types and frequency of initiating business process instances. The Integration Layer describes the business processes and indicates the services that should be performed at every step. The Component Layer describes component characteristics and what services they provide. In Server Layer both: server characteristics and runtime environments necessary for the component to run are described. Finally, the optimization task and evaluation criteria are formulated.

PL

Architektura SOA jest popularna w wielu organizacjach. Została głęboko zakorzeniona szczególnie w dużych organizacjach, które muszą zautomatyzować procesy biznesowe i wdrożyć je w wielu systemach. Posiada ona unikalną cechę, która pozwalającą jednoznacznie wskazać usługę w systemie, która ma realizować krok procesu biznesowego. Wskazanie to można pokazać bezpośrednio na diagramie BPMN. W ten sposób możliwe jest śledzenie, który serwer wykorzystał zasoby do realizacji usługi i ile tych zasobów było potrzebnych. Zatem możliwe jest zbudowanie zadania optymalizacyjnego, które przy ograniczonych i zawodnych zasobach określi taki przydział komponentów do serwerów oraz taki algorytm przypisywania im zadań, aby procesy działały jak najlepiej. W artykule przedstawiono model takiego zadania optymalizacyjnego. Składa się on z czterech warstw. Warstwa organizacyjna opisuje środowisko systemowe – typy i częstotliwość inicjowania instancji procesów biznesowych. Warstwa silnika procesów biznesowych i ESB opisuje procesy biznesowe i wskazuje usługi, które powinny być wykonywane na każdym kroku procesu. Warstwa komponentów opisuje charakterystyki komponentów i przypisane do nich usługi. W warstwie serwerów opisano zarówno właściwości serwerów, jak i środowisk uruchomieniowych niezbędnych do poprawnego działania komponentów. Model zakończony jest sformułowaniem zadania optymalizacji i kryteriów oceny.

Słowa kluczowe

EN

SOA deployment; mathematical model; system architecture optimization

PL

wdrożenie systemów typu SOA; model matematyczny; optymalizacja architektury systemów

• Wydawca: Institute of Computer and Information Systems, Faculty of Cybernetics, Military University of Technology
• Czasopismo: Computer Science and Mathematical Modelling
• Rocznik: 2019
• Tom: No. 9
• Strony: 33--44
• Opis fizyczny: Bibliogr. 30 poz., schem.

Twórcy

autor

Woźniak Adrian

• Military University of Technology, Faculty of Cybernetics, Institute of Computer and Information Systems, Kaliskiego 2, 01-489 Warsaw, Poland

autor

Nowicki Tadeusz

• Military University of Technology, Faculty of Cybernetics, Institute of Computer and Information Systems, Kaliskiego 2, 01-489 Warsaw, Poland

Bibliografia

• [1] Dumas M., Rosa M., Mendling J., Reijers H., Fundamentals of Business Process Management, Springer London, 1988.
• [2] Hammer M., Champy J., Reengineering the Corporation, HarperCollins Publishers Inc., 1993.
• [3] Gawin B., Marcinkowski B., Symulacja Procesów Biznesowych, Helion, 2013.
• [4] Erl T., Service Oriented Architecture: Concepts: Concepts, Technology and Design, HarperCollins Publishers, 2005.
• [5] Erl T., SOA Principles of Service Design, Prentice Hall, 2007.
• [6] Roshen W., SOA-Based enterprise integration, Mc Graw Hill, 2009.
• [7] Czarnul P., “Modelling, optimization and execution of workflow applications with data distribution, service selection and budget constraints in BeesyCluster”, Computer Science and Information Technology (IMCSIT), 2010.
• [8] Xiang C., Zhao W., Tian C., Nie J., Zhang J., “QoS-aware, Optimal and Automated Service Composition with Users’ Constraints”, IEEE 8th International Conference, 2011.
• [9] Liu Y., Wu L., Liu S., “A Novel QoS-Aware Service Composition Approach Based on Path Decomposition”, Services Computing Conference (APSCC), IEEE Asia-Pacific, 2012.
• [10] Syu Y., FanJiang Y., Kuo J., Ma S., “Towards a Genetic Algorithm Approach to Automating Workflow Composition for Web Services with Transactional and QoS-Awareness”, IEEE World Congress, 2011.
• [11] Ludwig S., “Clonal selection based genetic algorithm for workflow service selection”, Evolutionary Computation (CEC), IEEE Congress, 2012.
• [12] Mohammed M., Chikh M., Fethallah H., “QoS-aware web service selection based on harmony search”, ISKO-Maghreb: Concepts and Tools for knowledge Management, 4th International Symposium, 2014.
• [13] Esfahani P., Habibi J., Varaee T., “Application of Social Harmony Search Algorithm on Composite Web Service Selection Based on Quality Attributes”, Genetic and Evolutionary Computing (ICGEC), Sixth International Conference, 2012.
• [14] Liu Z., Xu X., “S-ABC – A Service-Oriented Artificial Bee Colony Algorithm for Global Optimal Services Selection in Concurrent Requests Environment”, Web Services (ICWS), IEEE International Conference, 2014.
• [15] Zhang Y., Cui G., Wang Y., Guo X., Zhao S., “An optimization algorithm for service composition based on an improved FOA”, Tsinghua Science and Technology, 20(1):90–99 (2015).
• [16] Hashmi K., AlJafar H., Malik Z., Alhosban A., “A bat algorithm based approach of QoS optimization for long term business pattern”, 7th International Conference on Information and Communication Systems (ICICS), 2016.
• [17] Oh M., Baik J., Kang S., Choi H., “An Efficient Approach for QoS-Aware Service Selection Based on a Tree-Based Algorithm”, Computer and Information Science, Seventh IEEE/ACIS International Conference, 2008.
• [18] Wang Z., Xu F., Xu X., “A Cost-Effective Service Composition Method for Mass Customized QoS Requirements”, IEEE Ninth International Conference, 2012.
• [19] Zhang G., Wang Z., “A QoS-Aware Service Composition Optimization Based on Logical Structure”, CiSE International Conference, 2009.
• [20] Pan S., Mao Q., “Semantic Web Service Composition Planner Agent with a QoS-Aware Selection Model”, Web Information Systems and Mining, 2009.
• [21] Luo Y., Qi Y., Shen L., Hou, D., Sapa C., Chen Y., “An Improved Heuristic for QoS-Aware Service Composition Framework”, High Performance Computing and Communications, 10th IEEE International Conference, 2008.
• [22] Wang C., Wang S., Chen H., Huang C., “A Reliability-Aware Approach for Web Services Execution Planning”, Services, IEEE Congress, 2007.
• [23] Dyachuk D., Deters R., “Service Level Agreement Aware Workflow Scheduling”, Services Computing, IEEE International Conference, 2007.
• [24] Dyachuk D., Deters R., “Ensuring Service Level Agreements for Service Workflows”, Services Computing, IEEE International Conference, 2008.
• [25] Zhang C., Chang R., Perng C., So E., Tang C., Tao T., “An Optimal Capacity Planning Algorithm for Provisioning Cluster-Based Failure-Resilient Composite Services”, Services Computing, IEEE International Conference, 2009.
• [26] Xie L., Luo J., Qiu J., Pershing J., Li Y., Chen Y., “Availability weak point analysis over an SOA deployment framework”, Network Operations and Management Symposium, 2008.
• [27] Mennes R., Spinnewyn B., Latré S., Botero J., “GRECO: A Distributed Genetic Algorithm for Reliable Application Placement in Hybrid Clouds”, 5th IEEE International Conference on Cloud Networking, 2016.
• [28] Schmid M., “An approach for autonomic performance management in SOA workflows”, Integrated Network Management, IFIP/IEEE International Symposium, 2011.
• [29] Almeida J., Almeida V., Ardagna D., Francalanci C., Trubian M., “Resource Management in the Autonomic Service-Oriented Architecture”, Autonomic Computing, IEEE International Conference, 2006.
• [30] Huang K., Lu Y., Tsai M., Wu Y., Chang H., “Performance-Efficient Service Deployment and Scheduling Methods for Composite Cloud Services”, IEEE/ACM 9th International Conference on Utility and Cloud Computing, 2016.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).