An extended SNMP based IoT context-aware model for dynamic adaptability of embedded systems software

Jaggernauth, Camille; Gubbe, Douglas

doi:10.1109/icin.2017.7899413

Cited by 2 publications

(1 citation statement)

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“…Selfconfigurable (or self-adaptive) systems aim to adapt their various artifacts autonomously as well as change their configuration dynamically in response to changes in the operating environment (i.e. context changes) without human interaction [7], [12], [10]. Dynamic adaptive systems are used in different domains of application such as natural catastrophe prevention (e.g.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable service-based architecture based on variability description

Adjoyan

Seriai

2017

Proceedings of the Symposium on Applied Computing

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Self-adaptive systems evolve during system's execution against changes in operating environment. Such evolution and reconfiguration can be specified at architecture level using a syntactical expressive language such as Architecture Description Languages (ADLs). Variability modeling is an excellent instrument to model variations of software artifacts and their behavior within a self-adaptive system. However, existing ADLs that support dynamic reconfiguration do not explicitly model variation points on which the reconfiguration is based. This constitutes a barrier for a flexible management of reconfiguration at architecture level as well as traceability issues between a dynamic description given at architectural level and its counterpart at other abstraction levels. In this paper, we propose a variant-rich service-oriented ADL that enables system to reconfigure itself at runtime in response to a context change. To this end, our modular ADL, called Dynamic Service-Oriented Product Lines Architecture Description Language (DSOPL-ADL), specifies dynamic reconfigurations at architecture level besides specifying structural, variability and context information. Among several specified variable configurations at architecture level, one concrete configuration is generated at runtime triggered by a context value. Furthermore, an implementation code can be automatically generated from the architectural description.

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Section: Introductionmentioning

confidence: 99%