Improving service availability via low-outage upgrades

Dislis, C.

doi:10.1109/cmpsac.2002.1045135

Cited by 5 publications

(3 citation statements)

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“…If a service is down randomly for one millisecond every hour, it has an availability of over 99.9 percent, but is still highly unreliable. Similarly, a service that never fails but is shut down for two weeks every August has a high reliability but only 96 percent availability [38]. The list of QoW S parameters mentioned above is not exhaustive and some readers may have different views regarding the definition / applicability of a few parameters.…”

Section: Parameters Reflecting the Quality Of Web Servicesmentioning

confidence: 99%

Trust Management for Service-Oriented Environments

Malik

Bouguettaya

2009

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Section: Parameters Reflecting the Quality Of Web Servicesmentioning

confidence: 99%

Trust Management for Service-Oriented Environments

Malik

Bouguettaya

2009

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“…Outage frequency is expressed on terms of MTBF, or Mean Time Between Failures, which is calculated as follows [15] …”

Section: Network Availabilitymentioning

confidence: 99%

Defining the Main Factors of Quality of Service in Mobile Telephony

Iacob

Bargh

2006

2006 International Conference on Wireless and Mobile Communications

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Due to the recent technological advances, many advanced mobile telephony services have been introduced. Thus the proper selection and the efficient service among various alternatives at hand are keys for selecting the best in the customer's point of view. The purpose of this study is to analyze the mobile telephony Quality of Service factors in the viewpoint of service selection. This study explores the factors to be considered by customers when choosing a telephony service. A hierarchical framework, supporting the mobile telephony Quality of Service, is presented. The framework is composed of a novel hierarchical structure of criteria and sub-criteria. We first describe the basics on Mobile Telephony Technology. The terms of Quality and Quality of Service are discussed from the viewpoint of end users (customers) satisfaction. Finally we analyse in deep each one of the factors, presented herein and we conclude with a discussion on our findings.

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“…Chan and Tortorella (2001) consider a simple probability model for sizing the spare inventory to meet an end-to-end service availability objective. Dislis (2002) describes some of the challenges in providing continuous service and the impact of upgrade related outages for mobile telephone networks. Reinecke et al (2004) treat a restart policy to speed up the completion of service as a representative application-level service dependability technique.…”

Section: Introductionmentioning

confidence: 99%

Availability and performability analysis for a service degradation process with condition-based preventive maintenance I - formulation and optimisation

Dohi

2014

IJSEAM

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The preventive maintenance is very useful to improve effectively the service availability for software systems with service degradation. In this paper, we present a stochastic model to describe an operational software system, which consists of one operating system and multiple applications and provides a service in continuous time. Two kinds of rejuvenation strategies are taken, namely reconfiguration of applications as a corrective maintenance and reinstallation of an operating system as a preventive maintenance. We derive the optimal preventive rejuvenation schedules maximising the steady-state service availability and maximising the expected reward per unit time, by means of semi-Markov decision processes. Illustrative numerical examples are presented to give decision tables on the optimal software rejuvenation policies.

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Improving service availability via low-outage upgrades

Cited by 5 publications

References 0 publications

Trust Management for Service-Oriented Environments

Trust Management for Service-Oriented Environments

Defining the Main Factors of Quality of Service in Mobile Telephony

Availability and performability analysis for a service degradation process with condition-based preventive maintenance I - formulation and optimisation

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