Abstract
A new approach to service requests management in case of insufficient hardware resources is proposed. It is based on wide aspects of requests analysis and it assures reliable and fast access to priority services. Requests are analyzed for, among others, time of occurrence, category of user who made the request, type of service, current system load and hardware utilization. Deterministic but dynamic rules help to manage system load very effectively, especially in terms of dependability and reliability. The proposed solution was tested on Gdańsk University of Technology central system, followed by the discussion of the results.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Van den Bossche, R., Vanmechelen, K., Broeckhove, J.: Cost-optimal scheduling in hybrid IaaS clouds for deadline constrained workloads. In: 2010 IEEE 3rd International Conference on Cloud Computing, pp. 228–235 (2010)
Metawei, M.A., Ghoneim, S.A., Haggag, S.M., Nassar, S.M.: Load balancing in distributed multi-agent computing systems. Ain Shams Eng. J. 3(3), 237–249 (2012)
Gutierrez-Garcia, J.O., Ramirez-Nafarrate, A.: Agent-based load balancing in cloud data centers. Cluster Comput. 18(3), 1041–1062 (2015)
Qin, X., Jiang, H., Manzanares, A., Ruan, X., Yin, S.: Communication-aware load balancing for parallel applications on clusters. IEEE Trans. Comput. 59(1), 42–52 (2010)
Zomaya, A.Y., Teh, Y.-H.: Observations on using genetic algorithms for dynamic load-balancing. IEEE Trans. Parallel Distrib. Syst. 12(9), 899–911 (2001)
Lin, C.-C., Chin, H.-H., Deng, D.-J.: Dynamic multiservice load balancing in cloud-based multimedia system. IEEE Syst. J. 8(1), 225–234 (2014)
Ren, X., Lin, R., Zou, H.: A dynamic load balancing strategy for cloud computing platform based on exponential smoothing forecast. In: 2011 IEEE International Conference on Cloud Computing and Intelligence Systems, pp. 220–224 (2011)
Lubomski, P., Kalinowski, A., Krawczyk, H.: Multi-level virtualization and its impact on system performance in cloud computing. Commun. Comput. Inf. Sci. 608, 247–259 (2016)
Zenon, C., Venkatesh, M., Shahrzad, A.: Availability and load balancing in cloud computing. In: International Conference on Computer and Software Modeling, IPCSIT, September 2011, vol. 14, pp. 134–140. IACSIT Press, Singapore (2011)
Lubomski, P., Krawczyk, H.: Clustering context items into user trust levels. Adv. Intell. Syst. Comput. 470, 333–342 (2016)
Thones, J.: Microservices. IEEE Softw. 32(1), 116 (2015)
Balalaie, A., Heydarnoori, A., Jamshidi, P.: Microservices architecture enables DevOps: migration to a cloud-native architecture. IEEE Softw. 33(3), 42–52 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Lubomski, P., Pszczoliński, P., Krawczyk, H. (2018). Aspect-Oriented Management of Service Requests for Assurance of High Performance and Dependability. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds) Advances in Dependability Engineering of Complex Systems. DepCoS-RELCOMEX 2017. Advances in Intelligent Systems and Computing, vol 582. Springer, Cham. https://doi.org/10.1007/978-3-319-59415-6_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-59415-6_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59414-9
Online ISBN: 978-3-319-59415-6
eBook Packages: EngineeringEngineering (R0)