A framework for dynamically adaptive applications in a self-organized mobile network environment

Mukhija, Arun; Glinz, Martin

doi:10.1109/icdcsw.2004.1284056

Cited by 14 publications

(4 citation statements)

References 11 publications

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“…Related approaches focus on formalism and modeling, mechanisms for adaptation, or distribution and decentralization of control. These include Darwin with π-calculus semantics to specify distributed systems [16], ArchWare with architectural reflection and dynamic co-evolution [17], Weaves for construction and analysis of data-flow systems [13], ArchStudio for selfadaptation of C2 hierarchical publish-subscribe systems [6], Plastik targeting performance properties [1], and CASA for resource availability concerns in mobile network environments [18]. These approaches share a few common characteristics: They generally apply a closed-loop control, use an architecture model for reasoning about the target system, assume certain structures in the target system, and adapt for a fixed set of quality attributes.…”

Section: Related Workmentioning

confidence: 99%

Improving Architecture-Based Self-Adaptation through Resource Prediction

Cheng

Poladian

Garlan

et al. 2009

Software Engineering for Self-Adaptive Systems

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Abstract. An increasingly important concern for modern systems design is how best to incorporate self-adaptation into systems so as to improve their ability to dynamically respond to faults, resource variation, and changing user needs. One promising approach is to use architectural models as a basis for monitoring, problem detection, and repair selection. While this approach has been shown to yield positive results, current systems use a reactive approach: they respond to problems only when they occur. In this paper we argue that self-adaptation can be improved by adopting an anticipatory approach in which predictions are used to inform adaptation strategies. We show how such an approach can be incorporated into an architecture-based adaptation framework and demonstrate the benefits of the approach.

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Section: Related Workmentioning

confidence: 99%

Improving Architecture-Based Self-Adaptation through Resource Prediction

Cheng

Poladian

Garlan

et al. 2009

Software Engineering for Self-Adaptive Systems

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show abstract

“…To date, many dynamic software architectures and architecture-based adaptation frameworks have been proposed and developed [8,9,10], often targeting specific architectural styles (e.g., Weaves for data-flow systems [20], ArchStudio for C2 hierarchical publish-subscribe systems [21], and [22] for managing robotics systems), and quality dimensions (e.g., Willow for survivability [23], Plastik for performance properties [24], and CASA for resource availability concerns in mobile network environments [25]). These related approaches on self-adaptive systems generally share a structure similar to the MAPE control cycle from IBM's Autonomic Computing initiative [6].…”

Section: Adaptation Frameworkmentioning

confidence: 99%

Stitch: A language for architecture-based self-adaptation

Cheng

Garlan

2012

Journal of Systems and Software

133

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Requirements for high availability in computing systems today demand that systems be self-adaptive to maintain expected qualities-of-service in the presence of system faults, variable environmental conditions, and changing user requirements. Autonomic computing tackles the challenge of automating tasks that humans would otherwise have to perform to achieve this goal. However, existing approaches to autonomic computing lack the ability to capture routine human repair tasks in a way that takes into account the business context that humans use in selecting an appropriate form of adaptation, while dealing with timing delays and uncertainties in outcome of repair actions. In this article, we present Stitch, a language for representing repair strategies within the context of an architecture-based self-adaptation framework. Stitch supports the explicit representation of repair decision trees together with the ability to express business objectives, allowing a self-adaptive system to select a strategy that has optimal utility in a given context, even in the presence of potential timing delays and outcome uncertainty.

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“…Related approaches focus on formalism and modeling, mechanisms of adaptation, or distribution and decentralization of control. These include Darwin with π-calculus semantics to specify distributed systems [17], ArchWare with architectural reflection and dynamic co-evolution [20], Weaves for construction and analysis of data-flow systems [9], Willow for survivable systems [27], ArchStudio for self-adaptation of C2 hierarchical publishsubscribe systems [5], Plastik targeting performance properties [2], CASA for resource availability concerns in mobile network environments [21], and CR-RIO for architectural reconfiguration using contracts [25]. These approaches share a few common characteristics: They generally apply closed-loop control and use an architecture model to reason about the target system.…”

Section: Related Workmentioning

confidence: 99%