Modelling and simulation of cloud computing solutions
2012
Krasons, E., Rezekne Higher Education Institution (Latvia) | Teilans, A., Rezekne Higher Education Institution (Latvia) | Meirans, I., Rezekne Higher Education Institution (Latvia) | Kleins, A., Riga Technical Univ. (Latvia). Faculty of Computer Science and Information Technology. Dept. of Modelling and Simulation
Nowadays, the designing of cloud computing systems is actual approach which is developing very quickly. The cloud computing platform can be useful in any economy domain. Using of cloud computing can increase effectiveness of rural sector through cost savings of monitoring, practically unlimited data capacity for calculating of statistic values and industry values used by domain managers and decision makers. Usually cloud computing requires reengineering of legacy software systems. It means reengineering of currently operated information systems and applications used by domain enterprises and adapting these systems for cloud platform. Solving this problem causes necessity for architecture and functionality modelling of current systems or modelling newly designed systems. Domain owners expect clearly defined vision of system deployment and operation in cloud. An architectural solution of Cloud Computing systems has its own technical peculiarities and it is necessary to precisely describe and gauge them. Behaviour of Cloud systems depends on large number of stochastic factors. For estimation of operational behaviour of such systems determined mathematical expressions usually are insufficient. This kind of systems research tasks could be effectively implemented by stochastic simulation. This paper focuses on design of UML based Domain specific language for modelling and simulation of Cloud Computing systems. Initial Design of Unified Modelling Language (UML) based Domain Specific language (DSL) described in this paper achieves synergy from in IT industry widely used UML modelling technique and the domain specific Cloud Computing extensions. As a novelty for UML modelling, especially for simulation purposes, the presented DSL is enriched by a set of stochastic attributes of modelled activities. Such stochastic attributes are usable for further implementation of discrete-event system simulators.
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