Self-Healing Distributed Scheduling Platform

Frîncu, Marc; Villegas, Norha M.; Petcu, Dana; Müller, Hausi A.; Rouvoy, Romain

doi:10.1109/ccgrid.2011.23

Cited by 12 publications

(7 citation statements)

References 18 publications

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“…Another approach is self-adaptive distributed scheduling platform composed of multiple agents implemented as intelligent feedback control loops to support policybased scheduling and expose self-healing capabilities [26,27]. While analyzing all of these approaches in parallel, we also tried to compare them so we could find the best solution, like the authors from [28].…”

Section: Related Workmentioning

confidence: 99%

Adaptive Resource Allocation in Cloud Computing Based on Agreement Protocols

Pop

Tutueanu

Barbieru

et al. 2015

Studies in Big Data

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In the last years there has been considerable interest in using distributed systems, especially Cloud Systems, in any domains. Resource management contributes to ensure quality of services for any type of application, especially when a system involves elements of heterogeneity characterized by a variety of resources that may or may not be coupled with specific platforms or environments. A problem very close to the industry is the capability to allocate resources in an efficient way and estimate costs, especially when switching from one provider to another. In this chapter we present an extended work oriented on agreement-based resource allocation and a scheduling algorithm, aimed to bring an adaptive fault tolerant distributed system. For the agreement protocol we describe and analyze a 3-Tier structure of resources (hosts and virtual machines). Then an adaptive mechanism for agreement establishment is described. The allocation method considers workload distribution, resources heterogeneity, transparency, adaptability and also the ease to extend by combining with other scheduling algorithms.

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Section: Related Workmentioning

confidence: 99%

Adaptive Resource Allocation in Cloud Computing Based on Agreement Protocols

Pop

Tutueanu

Barbieru

et al. 2015

Studies in Big Data

View full text Add to dashboard Cite

show abstract

“…14 The current version supports self-healing for modules built using the exposed API as well as for external software under the condition that it uses the framework's communication protocol. A detailed overview on its structure and some tests regarding the time to recover from errors is given in [18].…”

Section: Autonomous Framework For Rmsmentioning

confidence: 99%

Resource Management for HPC on the Cloud

Frîncu

Petcu

Jeannot³

et al. 2014

High‐Performance Computing on Complex Environments

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“…Frincu et al (Frincu et al, 2011) propose a selfadaptive distributed scheduling platform composed of MAS implemented as an intelligent feedback control loops supporting defined policies and exposing self-healing capabilities. To face the challenge of building an autonomous self-healing system, an adaptive inter-provider MAS was proposed.…”

Section: Related Workmentioning

confidence: 99%

A Multi-Agent based Architecture for Cloud Infrastructure Auto-adaptation

Chihi¹,

Chainbi²,

Ghédira³

2013

Proceedings of the 3rd International Conference on Cloud Computing and Services Science

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Cloud computing including hardware, software, communication and networks are growing towards an ever increasing scale and heterogeneity, becoming overly complex. To manage such growing complexity, autonomic computing focuses on self-adaptable computing systems to the maximum extent possible without human intervention or guidance. In this paper, we design a multi-agent-based architecture for Cloud infrastructure auto-adaptation. This model is based on distributed multi-agent systems which collaborate to enrich the Cloud with self-* capabilities. The proposed model represents an effective method to reduce servers' power consumption while achieving the required performance and providing trusted Cloud. A Multi-Agent based Architecture for Cloud Infrastructure Auto-adaptation.

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Self-Healing Distributed Scheduling Platform

Abstract: Abstract

Cited by 12 publications

References 18 publications

Adaptive Resource Allocation in Cloud Computing Based on Agreement Protocols

Adaptive Resource Allocation in Cloud Computing Based on Agreement Protocols

Resource Management for HPC on the Cloud

A Multi-Agent based Architecture for Cloud Infrastructure Auto-adaptation

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