Abstract
The correct deployment of software objects over the computational resources has a significant impact on the software performance. Achieving the optimal deployment manually is a tedious work as there are many different alternative solutions. In this paper a heuristic algorithm for optimizing the deployment of software objects is proposed which evaluates each deployment in the search space, considering its communicational and computational delays. In order to estimate these delays for an object deployment, our algorithm takes into account both the resource capacities and the execution load of the software for a given input-workload. The execution load of the software is measured by simulating the software use-case scenarios using the Finite State Process (FSP) models. From the simulation, the values of some metrics such as utilization, population and mean response times corresponding to the objects and threads participating in software use-case scenarios are recorded as the execution load indicators. These recorded simulation results are subsequently applied to estimate the goodness of a deployment in the search space.
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References
Woodside, M., Franks, G., Petriu, D.: The Future of Software Performance Engineering. In: Future of Software Engineering (FOSE 2007), pp. 171–187. IEEE Press, Minneapolis (2007)
Balsamo, S., Dimarco, A., Inverardi, P., Simeoni, A.: Model-Based Performance Prediction in Software Development. J. IEEE Trans. on Soft. Eng. 30(1), 295–310 (2004)
Balsamo, S., Marzolla, M.: Performance Evaluation of UML Software Architectures with Multi-Class Queuing Network Models. In: 5th Int. workshop on Software and Performance, pp. 37–42. ACM, Palma (2005)
Bennett, A.J., Field, A.J.: Performance Engineering with the UML Profile for Schedulability, Performance and Time: a Case-Study. In: 12th Annual Int. Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, pp. 67–75. IEEE Press, Los Alamitos (2004)
Object Management Group, http://www.omg.org/technology/documents/profile_catalog.htm
Chih-Chieh, H., Devetsikiotis, M.: An Automatic Framework for Efficient Software Performance Evaluation and Optimization. In: 40th Annual Simulation Symposium, pp. 99–105. IEEE Press, Norfolk (2007)
Woodside, M., Monforton, G.: Fast Allocation of Processes in Distributed and Parallel Systems. J. IEEE Trans. on Parallel and Distributed Sys. 4(2), 164–174 (1993)
Bastarrica, M., Caballero, R., Demurjian, A., Shvartsman, A.: Two Optimization Techniques for Component-Based Systems Deployment. In: 13th Int. Conference on Software Eng. and Knowledge Eng. p. 153–162. Buenos Aires, Argentina (2001)
Boone, B., Truck, F., Dhoedt, B.: Automated Deployment of Distributed Software Components with Fault Tolerance Guarantees. In: 6th Int. Conference on Software Engineering Research, Management and Applications, pp. 21–27. IEEE Press, Parague (2008)
Deb, D., Fuad, M., Oudshoom, M.J.: Towards Autonomic Distribution of Existing Object-Oriented Programs. In: Conference on Autonomic and Autonomous Systems, pp. 17–23. IEEE Press, Silicon (2006)
Aleti, A., Bjornander, S., Grunske, L., Meedeniya, I.: Archeopterix: An Extendable Tool for Architecture Optimization of AADL Models. In: International Workshop on Model-based Methodologies for Pervasive and Embeded Software, pp. 61–71. IEEE Press, Vancouver (2009)
Martens, A., Koziolek, H., Becker, S., Reussner, R.: Automatically Improve Software Architecture Models for Performance, Reliability and Cost Using Evolutionary Algorithms. In: The First Joint WOSP/SIPEW International Conference on Performance engineering, San Jose, CA (2010)
Ayles, T., Field, A.J., Magee, J.N.: Adding Performance Evaluation to the LTSA Tool. In: Kemper, P., Sanders, W.H. (eds.) TOOLS 2003. LNCS, vol. 2794, pp. 291–307. Springer, Heidelberg (2003)
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Bushehrian, O. (2011). The Application of FSP Models in Automatic Optimization of Software Deployment. In: Al-Begain, K., Balsamo, S., Fiems, D., Marin, A. (eds) Analytical and Stochastic Modeling Techniques and Applications. ASMTA 2011. Lecture Notes in Computer Science, vol 6751. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21713-5_4
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DOI: https://doi.org/10.1007/978-3-642-21713-5_4
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