Abstract
Cloud Computing is a new distributed computing paradigm that consists in provisioning of infrastructure, software and platform resources as services. This paradigm is being increasingly used for the deployment and execution of service-based applications. To efficiently manage them according the autonomic computing approach, service-based applications can be associated with autonomic managers that monitor them, analyze monitoring data, plan and execute configuration action on them. Although, in these last years, autonomic management of cloud services has received an increasing attention, optimization of autonomic managers (AMs) assigned to cloud services and their placement in the cloud remain not well explored. In fact, almost all the existing solutions on autonomic computing have been interested in modeling and implementing of autonomic environments without paying attention on optimization. To address this issue, we present in this paper a novel approach to optimize autonomic management of service-based applications that consists in minimizing both the cost of allocated AMs while avoiding bottlenecks in management and the cost of their placement in the cloud (the inter-virtual machine communication cost). We propose two algorithms: (i) an algorithm that determines the optimal number of AMs to be assigned to services of a managed service-based application, and (ii) an algorithm that approximates the optimal placement of AMs in the cloud. Experiments conducted show the efficiency of our finding.
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
Similar content being viewed by others
References
An architectural blueprint for autonomic computing. Technical report, IBM (2005)
Belhaj, N., Lahmar, I.B., Mohamed, M., Belaïd, D.: Collaborative autonomic management of distributed component-based applications. In: On the Move to Meaningful Internet Systems: OTM Conferences (2015)
Booch, G., Rumbaugh, J., Jacobson, I.: Unified Modeling Language User Guide. Addison-Wesley Professional, Boston (2005)
Buyya, R., Calheiros, R.N., Li, X.: Autonomic cloud computing: open challenges and architectural elements. CoRR (2012)
Diaz-Montes, J., Zou, M., Rodero, I., Parashar, M.: Enabling autonomic computing on federated advanced cyberinfrastructures. In: Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference (2013)
Fahland, D., Favre, C., Koehler, J., Lohmann, N., Völzer, H., Wolf, K.: Analysis on demand: Instantaneous soundness checking of industrial business process models. Data Knowl. Eng. 70(5), 448–466 (2011)
Hadded, L., Charrada, F.B., Tata, S.: An efficient optimization algorithm of autonomic managers in service-based applications. In: On the Move to Meaningful Internet Systems: OTM Conferences (2015)
Hasan, M., Magana, E., Clemm, A., Tucker, L., Gudreddi, S.: Integrated and autonomic cloud resource scaling. In: Network Operations and Management Symposium (NOMS). IEEE (2012)
IBM: IBM CPLEX Optimizer. http://www.ilog.com/products/cplex/
Jamshidi, P., Ahmad, A., Pahl, C.: Autonomic resource provisioning for cloud-based software. In: Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (2014)
Juric, M.B.: Business Process Execution Language for Web Services BPEL and BPEL4WS, 2nd edn. Packt Publishing, Birmingham (2006)
Kurian, D., Chelliah, P.: An autonomic computing architecture for business applications. In: World Congress on Information and Communication Technologies (WICT) (2012)
Marino, J., Rowley, M.: Understanding SCA (Service Component Architecture). Addison-Wesley Professional, Reading (2009)
Mell, P.M., Grance, T.: The NIST definition of cloud computing. Technical report (2011)
Mohamed, M., Amziani, M., Belaid, D., Tata, S., Mellit, T.: An autonomic approach to manage elasticity of business processes in the cloud. Future Gener. Comp. Syst. 50, 49–61 (2015)
Mohamed, M., Belaid, D., Tata, S.: Extending OCCI for autonomic management in the cloud. J. Syst. Softw. (2016)
Mohamed, M., Megahed, A.: Optimal assignment of autonomic managers to cloud resources. In: IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) (2015)
de Oliveira, F., Ledoux, T., Sharrock, R.: A framework for the coordination of multiple autonomic managers in cloud environments. In: IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) (2013)
(OMG), O.M.G.: Business process model and notation (BPMN). Technical report (2011)
Redbooks, I., Organization, I.: A Practical Guide to the IBM Autonomic Computing Toolkit. IBM Corporation, International Technical Support Organization (2004)
Romero, D., Rouvoy, R., Seinturier, L., Chabridon, S., Conan, D., Pessemier, N.: Enabling context-aware web services: a middleware approach for ubiquitous environments. In: Enabling Context-Aware Web Services: Methods, Architectures, and Technologies (2010)
Ruz, C., Baude, F., Sauvan, B.: Flexible adaptation loop for component-based SOA applications. In: 7th International Conference on Autonomic and Autonomous Systems ICAS (2011)
Sahni, S.: Computationally related problems. SIAM J. Comput. 3(4), 262–279 (1974)
Tomás, L., Caminero, A.C., Rana, O., Carrión, C., Caminero, B.: A gridway-based autonomic network-aware metascheduler. Future Gener. Comput. Syst. 28(7), 1058–1069 (2012)
Wieczorek, M., Hoheisel, A., Prodan, R.: Taxonomies of the multi-criteria grid workflow scheduling problem. In: Grid Middleware and Services (2008)
Wu, B., Chi, C.H., Chen, Z., Gu, M., Sun, J.: Workflow-based resource allocation to optimize overall performance of composite services. Future Gener. Comput. Syst. 25(3), 199–212 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Hadded, L., Ben Charrada, F., Tata, S. (2016). Optimization and Approximate Placement of Autonomic Resources for the Management of Service-Based Applications in the Cloud. In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2016 Conferences. OTM 2016. Lecture Notes in Computer Science(), vol 10033. Springer, Cham. https://doi.org/10.1007/978-3-319-48472-3_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-48472-3_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-48471-6
Online ISBN: 978-3-319-48472-3
eBook Packages: Computer ScienceComputer Science (R0)