1. 40% des investissements dans les technologies de l'information sont utilisés juste pour l'intégration des différentes technologies utilisées un sein d'un même système [7]. 2. La littérature anglo-saxonne qualifie ces propriétés de « self-star » ou « self-* » [9].
a lIre laboratory, Constantine 2 university-abdelhamid mehri, Constantine, algeria; b lIuPPa laboratory, university of Pau, Pau, france
ABSTRACTThe few recent years have witnessed the appearance of a new kind of selfadaptive systems called cloud based-elastic systems. These systems are particularly appealing for their ability to maintain a decent quality of service and reduce a system's operating cost at the same time. They achieve this by dynamically adjusting resources allocation in terms of elasticity. Meanwhile, complexity of structural and behavioural aspects related to cloud-based elastic systems increase the difficulty of designing and developing such systems. In this paper, we address this challenge by proposing a formal approach based on bigraphical reactive systems for modelling both structural and behavioural aspects of cloud-based elastic systems. In particular, we represent their behaviour in terms of client/application interactions and elasticity methods at different levels using bigraphical reaction rules. The feasibility of the proposed approach is illustrated through a motivating example running on the top of an Amazon Elastic Compute Cloud (EC2) infrastructure.Modelling cloud-based elastic systems using bigraphical reactive systems
Elasticity property allows cloud systems to adapt to their input workload by provisioning and deprovisioning resources as the demand grows and drops. However, due to the unpredictable nature of workload, providing accurate action plans to manage a cloud system's elasticity is a particularly challenging task. In this paper, we propose a BRS (short for Bigraphical Reactive Systems) based approach to provide a formal modeling of cloud systems' structure using bigraphs, and their elastic behaviors using bigraphical reaction rules. We introduce elasticity strategies to describe cloud systems' autoadaptation behaviors. One step further, we encode the bigraphical specifications into Maude language to enable an autonomic executability of the elastic behaviors and verify their correctness. Finally, we propose a queuing-based approach to discuss and analyze elasticity strategies in cloud systems through different simulated scenarios.
Sequence Diagrams (SDs) are one of the most popular elements of the UML notation to model the dynamics of systems. However, the graphical representation of basic SDs suffers from an inherent ambiguity that has led to different definitions in UML 1.x and in UML 2.0. This ambiguity paves the way for the consideration of several semantics for basic SDs. The paper studies four of these semantics and shows to what extent their differences for a given SD (that is the amount of ambiguity of this diagram) comes from its structural properties (linearity, local control and local causality). The fulfilment of these properties can serve as a measure of the ambiguity of a SD, and thus the attention to be paid at its validation.
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