Self-Assessment and Reconfiguration Methods for Autonomous Cloud-based Network Systems

A system that is highly dependable under hostile conditions but whose dependability cannot be easily evaluated prior to the deployment of applications is less desirable than a system with lower but predictable dependability. This is because a decision-making on the deployment of high assurance syste...

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Bibliographic Details
Published in:2013 IEEE/ACM 17th International Symposium on Distributed Simulation and Real Time Applications pp. 87 - 94
Main Author: Ravindran, Kaliappa
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2013
Subjects:
Adaptation models
Computational modeling
data replication service
Fault tolerance
Fault tolerant systems
feedback control techniques
Frequency modulation
QoS adaptation
Quality of service
Servers
system dependability assessment
ISSN:1550-6525
Online Access:Get full text
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Summary:A system that is highly dependable under hostile conditions but whose dependability cannot be easily evaluated prior to the deployment of applications is less desirable than a system with lower but predictable dependability. This is because a decision-making on the deployment of high assurance systems is often based on a risk analysis of application failures. For systems implemented on a cloud, the problem of system certification assumes added importance because of third-party control of cloud resources and the attendant problems of faults, QoS degradations, and security violations. In this light, our paper focuses on: i) formulating metrics to quantify the dependability of cloud-based applications; and ii) identifying techniques to measure these metrics prior to deployment of applications.The paper treats system dependability as an application-level QoS for management purposes, and advocates a probabilistic evaluation of dependability. Our approach is corroborated by measurements on system-level prototypes and simulation analysis of system models in the face of hostile environment conditions. A case study of replicated data service anchored on cloud infrastructures is also described.
ISSN:1550-6525
DOI:10.1109/DS-RT.2013.37