Using Genetic Algorithms to Optimize Web Caching in Multimedia-Integrated e-Learning Content

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dc.contributor.authorKipruto, Cheruiyot W.
dc.contributor.authorTan, Guan Z.
dc.contributor.authorMusau, Felix
dc.contributor.authorMushi, Joseph C.
dc.date.accessioned2016-07-25T16:45:00Z
dc.date.available2016-07-25T16:45:00Z
dc.date.issued2011
dc.description.abstractThe evolution of e-learning as a new information technology built around the use of internet has originated new possibilities to develop pedagogical methodologies that provide the necessary knowledge and skills in the higher education environment. This has in effect given rise to a large number of learners who desire to access the educational resources provided by the new technology. But for many institutions of higher learning, the users often experiences poor performance when they try to access contents or download e-learning files. The main reasons for such are often performance problems concerning network infrastructure and the fact that many people tend to access the same piece of information repetitively. This paper uses web caching scheme and genetic algorithm optimization to effectively lessen this service bottleneck, diminish the user access latency and reduce the network traffic.en_US
dc.identifier.citationKipruto, C.W., Tan, G.Z., Musau, F. and Mushi, J.C., 2011. Using genetic algorithms to optimize web caching in multimedia-integrated e-learning content. International Journal of Digital Content Technology and its applications, 5(8).en_US
dc.identifier.doi10.4156/jdcta.vol5.issue8.7
dc.identifier.urihttp://hdl.handle.net/20.500.11810/3426
dc.language.isoenen_US
dc.subjectMultimedia Integrated E-learningen_US
dc.subjectWeb Cacheen_US
dc.subjectGenetic algorithmsen_US
dc.titleUsing Genetic Algorithms to Optimize Web Caching in Multimedia-Integrated e-Learning Contenten_US
dc.typeJournal Article, Peer Revieweden_US
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