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Link Load Prediction using Support Vector Regression and Optimization
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 24 - Number 7 |
| Year of Publication: 2011 |
| Authors: Debashree Priyadarshini, Milu Acharya, Ambika Prasad Mishra |
10.5120/2966-3964
|
Debashree Priyadarshini, Milu Acharya, Ambika Prasad Mishra . Link Load Prediction using Support Vector Regression and Optimization. International Journal of Computer Applications. 24, 7 ( June 2011), 22-25. DOI=10.5120/2966-3964
Abstract
Prediction techniques are an interesting challenge in many areas like weather, banking, and finance, healthcare and so on. They are also becoming a popular subject in networking domain. This topic explores link load prediction of a network using Support Vector Regression and Optimization techniques. Support Vector Regression(SVR) is robust to outliers and can be used to online and adaptive learning.SVR has been used in other problems of networking like TCP throughput prediction, latency prediction and dynamic bandwidth provisioning in non- stationary traffic.Here,SVR and Optimization technique has been used to assess the bandwidth of a network dynamically.
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