A Formal Approach for Failure Detection in Large-Scale Distributed Systems Using Abstract State Machines

Buga, Andreea; Nemeş, Sorana Tania

doi:10.1007/978-3-319-64468-4_38

Cited by 3 publications

(1 citation statement)

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“…Code 2 contains the responsible rule. At the end of a collaborative diagnosis round, each of the monitors updates its confidence degree according to a function defined by [19]. This function takes into account the similarity of the information submitted by a monitor in comparison with the one provided by other monitors assigned to the same node.…”

Section: Specification Of the Monitoring Solutionmentioning

confidence: 99%

Addressing Client Needs for Cloud Computing using Formal Foundations

Buga¹,

Nemeş²,

Mashkoor³

2018

Preprint

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Cloud-enabled large-scale distributed systems orchestrate resources and services from various providers in order to deliver highquality software solutions to the end users. The space and structure created by such technological advancements are immense sources of information and impose a high complexity and heterogeneity, which might lead to unexpected failures. In this chapter, we present a model that coordinates the multi-cloud interaction through the specification, validation, and verification of a middleware exploiting monitoring and adaptation processes. The monitoring processes handle collecting meaningful data and assessing the state of components, while the adaptation processes restore the system as dictated by the evolution needs and sudden changes in the operating environment conditions. We employ Abstract State Machines to specify the models and we further make use of the ASMETA framework to simulate and validate them. Desired properties of the system are defined and analysed with the aid of the Computation Tree Logic.

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Section: Specification Of the Monitoring Solutionmentioning

confidence: 99%