Achieving resilience in distributed software systems via self-reconfiguration

Pradhan, Subhav; Dubey, Abhishek; Levendovszky, Tihamér; Kumar, Pranav Srinivas; Emfinger, William; Balasubramanian, Daniel; Otte, William R.; Karsai, Gábor

doi:10.1016/j.jss.2016.05.038

Cited by 26 publications

(9 citation statements)

References 33 publications

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“…The presented approach is enabling a non-intrusive monitoring of IoT behavior at runtime. Pradhan et al (2016) described the work on improving runtime support for autonomous resilience via self-reconfiguration. A runtime infrastructure governs the self-reconfiguration mechanisms.…”

Section: Run-time Monitoring Of Operation Of Softwarementioning

confidence: 99%

From Validation of Medical Devices towards Validation of Adaptive Cyber-Physical Systems

Tavčar

Duhovnik

Horváth

2020

JID

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Conventionally, designing of a technical system is completed in the product development phase in terms of all details and aspects. This can be done if the expected behavior and the conditions of operation are known in advance and can be validated before the product is launched on the market. Validation is typically based on a predictive analysis or simulation of the designed operation. However, this contradicts with the case of smart systems, such as smart cyber-physical systems (CPSs), which self-manage their operation or at least a part of it. Being able to adapt at run-time and evolve over time, smart CPSs cannot be validated using conventional deterministic approaches. This is especially true for smart CPSs used as instrumentation in the medical field. This gave the stimulation of our background research, the results of which are concisely summarized and critically concluded in this paper. The literature has been found fairly narrow in terms of novel validation approaches for self-managing smart systems. The main finding is that the tasks of operational and behavioral validation should be shared among the system designers and the designed systems. Designers need prognostic approaches, while systems need to construct validation plans and execute them at run-time. This needs validation-specific functionalities and context dependent mechanisms such as run-time validation frameworks or meta-models, objective-sensitive self-monitoring mechanisms, self-constraining and self-supporting mechanisms, and other enablers. Extensive foundational research and system prototype testing are deemed to be indispensable. To make the first small step in this direction, this paper proposes a concept for validation of smart medical CPSs. This relies on the following hypothesis: If a system has freedom for self-adaptation, then it should also be equipped with selfcontrol mechanism, meta-knowledge and a supervisory controller. It all together enables a purpose-and context dependent semantic reasoning about the operational and behavioral objectives. The paper suggests a number of topics for future research towards a run-time validation engine.

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Section: Run-time Monitoring Of Operation Of Softwarementioning

confidence: 99%

From Validation of Medical Devices towards Validation of Adaptive Cyber-Physical Systems

Tavčar

Duhovnik

Horváth

2020

JID

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“…GoalD can augment this approach by handling variability as a deployment problem and explicitly captures and caters for the different settings of the hosting environment. Pradhan et al [45] propose a goal-based solution to achieve resilience in mobile cyber-physical systems via self-configuration and autonomous deployment. Although such approach does benefit from a goal-based solution as well, there is no seamless integration between requirements, strategies and configurations/context conditions.…”

Section: Related Workmentioning

confidence: 99%

“…Ali et al [46] Yes No No Angelopoulos et al [30] Yes No No Casquina et al [15] No Yes No Bencomo et al [47] No Yes No Mizouni et al [48] No Yes Yes Pradhan et al [45] No Yes Yes Gunalp et al [54] No Yes Yes GoalD Yes Yes Yes Table 5: Comparison between GoalD and most related approaches…”

Section: Work By Goal Oriented Handle Heterogeneity Autonomous Deploymentioning

confidence: 99%

GoalD: A Goal-Driven deployment framework for dynamic and heterogeneous computing environments

Rodrigues

Guimarães²,

Rodrigues

et al. 2019

Information and Software Technology

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Context: Emerging paradigms like Internet of Things and Smart Cities utilize advanced sensing and communication infrastructures, where heterogeneity is an inherited feature. Applications targeting such environments require adaptability and context-sensitivity to uncertain availability and failures in resources and their ad-hoc networks. Such heterogeneity is often hard to predict, making the deployment process a challenging task. Objective: This paper proposes GoalD as a goal-driven framework to support autonomous deployment of heterogeneous computational resources to fulfill requirements, seen as goals, and their correlated components on one hand, and the variability space of the hosting computing and sensing environment on the other hand. Method: GoalD comprises an offline and an online stage to fulfill autonomous deployment by leveraging the use of goals. Deployment configuration strategies arise from the variability structure of the Contextual Goal Model as an underlying structure to guide autonomous planning by selecting available as well as suitable resources at runtime. Results: We evaluate GoalD on an existing exemplar from the selfadaptive systems community -the Tele Assistance Service provided by Weyns and Calinescu [1]. Furthermore, we evaluate the scalability of GoalD on a repository consisting of 430,500 artifacts. The evaluation results demonstrate the usefulness and scalability of GoalD in planning the deployment of a system with thousands of components in a few milliseconds.Corresponding author -Postal Address: Dept. de Ciência da Computação -Campus Darcy Ribeiro, Edifício CIC/EST, Asa Norte, Brasília -DF -Brasil, Postal Code: 70910-900. Conclusions:GoalD is a framework to systematically tackle autonomous deployment in highly heterogeneous computing environments, partially unknown at design-time following a goal-oriented approach to achieve the user goals in a target environment. GoalD has demonstrated itself able to scale for deployment planning dealing with thousands of components in a few milliseconds.

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“…The work of Pradhan et al (2016) proposes an integrated design tool suite for model-based development of component-based applications. Based on the design, a run-time system was developed to provide the information about the ability to meet the operational deadlines and required network quality-of-service, the schedulability of all the application tasks, and the feedback about the resilience of the system.…”

Section: Article In Pressmentioning

confidence: 99%