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An early prediction of resource utilization and its impacton system performance and reliability can reduce theoverall system cost, by allowing early correction of detectedproblems, or changes in development plans with minimizedoverhead. Nowadays, researchers are using both academicand commercial models to predict such attributes, by measuringthem at earliest stages of system development. Inthis paper, we give a short overview of existing predictionmodels for performance and reliability, targeting popularcomponent-based frameworks. Next, we describe our ownapproach for tackling such predictions, through an illustrationon a small example that deals with estimations of energyconsumption.

There is no clear distinction between service-orientedsystems (SOS) and component-based systems (CBS). However,there are several characteristics that could let one considerSOS as a step further from CBS. In this paper, we discussthe general features of CBS and SOS, while accountingfor behavioral modeling in the language called REMES.First, we present REMES in the context of CBS modeling,and then we show how it can become suitable for SOS. Wealso discuss the relation between our model and the currentstate of the art.

Service-oriented systems have recently emerged as context-independent component-based systems. Unlike components, services can be created, invoked, composed, and destroyed at run-time. Consequently, all services need a way of advertising their capabilities to the entities that will use them, and serviceoriented modeling should cater for various kinds of service composition. In this paper, we show how services can be formally described by the resource-aware timed behavioral language REMES, which we extend with service-specific information, such as type, capacity, time-to-serve, etc., as well as boolean constraints on inputs, and output guarantees. Assuming a Hoare-triple model of service correctness, we show how to check it by using the strongest postcondition semantics. To provide means for connecting REMES services, we propose a hierarchical language for service composition, which allows for verifying the latter's correctness. The approach is applied on an abstracted version of an intelligent shuttle system.