<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Safar, M.</style></author><author><style face="normal" font="default" size="100%">Habib, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sensitivity analysis of server placement on enterprise network topology through soft computing</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Digital Information Management</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">Edge-server placement</style></keyword><keyword><style  face="normal" font="default" size="100%">Network topology</style></keyword><keyword><style  face="normal" font="default" size="100%">Optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">Soft computing</style></keyword><keyword><style  face="normal" font="default" size="100%">Web structure analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2007</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.scopus.com/inward/record.url?eid=2-s2.0-33947320448&amp;partnerID=40&amp;md5=62ced3281abb66c04e4ac8f00c808c7b</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">1 - 7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We analyze the consequences when both the server placement problem and network topology problem are solved concurrently through soft computing. Both problems are formulated as a combined optimization problem, subject to a set of design and performance constraints while minimizing the enterprise network cost. We have coded the combined optimization problem within a soft computing methodology, which is based on a probabilistic genetic program for automatically searching the design space for good network topologies. The experimental results for synthesizing and optimizing 3-level enterprise network (65 user nodes) for an edge-server placement has demonstrated the effectiveness of our methodology in finding good solutions with a static workload in less than five minutes.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><notes><style face="normal" font="default" size="100%">Export Date: 10 July 2014</style></notes></record></records></xml>