Abstract

Software deployment is executed according a deployment architecture which describes the allocation of software components to its hardware hosts. In this paper, we tackle the issue of constructing correct deployment architectures for large distributed systems. Actually, such architectures should satisfy various constraints related to the software components and the target environment such as the hierarchical description of components , their connections and the resource constraints. We present a formal method for constructing deployment architectures using a formal language called BRS (Bigraphical Reactive System). This method provides a correct by design approach based on multi-scale modeling ensuring the correctness of the obtained deployment architectures. Following our approach, the designer starts by modeling the first scale architecture which is refined automatically by successively adding smaller scale components until obtaining the last scale deployment architecture.

Highlights

  • We have been witnessing how various applications are being integrated more deeply into daily users [6]

  • We have considered context analysis. we have proposed an analysis approach for context change detection in pervasive environments

  • We have proposed a context classification based on context parameter evolution

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Summary

Introduction

We have been witnessing how various applications are being integrated more deeply into daily users [6] These technological advances are providing the hardware infrastructure necessary to achieve the pervasive computing paradigm [14]. Pervasive computing and ubiquitous applications need to be aware of their environment in order to adapt to changing contexts and provide correct services [1]. Applications on top of pervasive environments need to be context aware so that they can adapt themselves to the changing context and the execution environments. The context parameters are analyzed and changes are detected by comparing the context parameter values and the computed threshold values. We detail the threshold calculation step that allows to analyze context and detect changes. The last section concludes the paper and gives some directions for future work

Related work
Case study
The proposed approach
Context parameter classification step
Threshold calculation step
Illustrative scenario
Conclusion
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