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Self-optimising data farming for web applications

Self-optimising data farming for web applications

Burnell, D., Al-Zobaidie, A., Windall, G. and Butler, A. (2004) Self-optimising data farming for web applications. In: Proceedings: 15th International Workshop on Database and Expert Systems (DEXA 2004). IEEE Computer Society, Los Alamitos, California, USA, pp. 436-440. ISBN 0769521959 ISSN 1529-4188 (doi:10.1109/DEXA.2004.1333513)

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Abstract

Many Web applications walk the thin line between the need for dynamic data and the need to meet user performance expectations. In environments where funds are not available to constantly upgrade hardware inline with user demand, alternative approaches need to be considered. This paper introduces a ‘Data farming’ model whereby dynamic data, which is ‘grown’ in operational applications, is ‘harvested’ and ‘packaged’ for various consumer markets. Like any well managed agricultural operation, crops are harvested according to historical and perceived demand as inferred by a self-optimising process. This approach aims to make enhanced use of available resources through better utlilisation of system downtime - thereby improving application performance and increasing the availability of key business data.

Item Type: Conference Proceedings
Title of Proceedings: Proceedings: 15th International Workshop on Database and Expert Systems (DEXA 2004)
Additional Information: [1] This paper was first presented at the 15th International Workshop on Database and Expert Systems (DEXA 2004) held from 30 August – 3 September 2004 in Zaragoza, Spain.
Uncontrolled Keywords: internet, data mining, electronic commerce, web applications, consumer markets, data harvesting, key business data, self-optimising data farming model, application software, availability, computer science, databases, flexible structures, HTML, hardware, Moore's Law, XML
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Computer & Computational Science Research Group
School of Computing & Mathematical Sciences > Department of Computer Science
Related URLs:
Last Modified: 14 Oct 2016 09:02
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/850

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