Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 491701
Title Supporting Performance Isolation in Software as a Service Systems with Rich Clients
Author(s) Oral, A.; Tekinerdogan, B.
Source In: Proceedings of the IEEE International Congress on Big Data. - IEEE - ISBN 9781467372770 - p. 297 - 304.
Event IEEE International Congress on Big Data, New York, USA, 2015-06-27/2015-07-02
DOI http://dx.doi.org/10.1109/BigDataCongress.2015.49
Department(s) WASS
Information Technology
Publication type Contribution in proceedings
Publication year 2015
Abstract In a non-isolated Software as a Service (SaaS) system, different clients can freely use the resources of the SaaS. Hereby, disruptive tenants who exceed their limits can easily cause degradation of performance of the provided services for other tenants. To ensure performance demands of the multiple tenants and meet fairness criteria various performance isolation approaches have been introduced including artificial delay, round robin, blacklist, and thread pool. Unfortunately, these approaches tend to be based on and assume SaaS systems with thin clients whereby all the tasks are handled by the SaaS. In this paper we propose a framework for supporting the design and realization of performance isolated SaaS systems by also considering the usage of resources of rich clients. We discuss the impact of the implication of rich clients for each of the identified performance isolation approach. To validate our novel performance isolation approach we have adopted a SaaS environment with an industrial case. We discuss the various different scenarios based on both thin and rich client types. Our study shows a substantial impact on the result of performance isolation approaches when considering rich clients.
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