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Conference Paper
Dynamic Network Selection using Kernels
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- Authors
- Eric van den Berg, Praveen Gopalakrishnan, Byung Suk Kim, Bryan Lyles, Won-Ik Kim, Yeon Seung Shin, Yeong Jin Kim
- Issue Date
- 2007-06
- Citation
- International Conference on Communications (ICC) 2007, pp.6049-6054
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- We present a new algorithm for vertical handover and dynamic network selection, based on a combination of multi-attribute utility theory, kernel learning and stochastic gradient descent We show that this new method is able to improve network selection in a non-stationary mobile environment. Furthermore, since the kernel employed is based on the utility functions for attributes such as Availability, Quality and Cost, the kernel regression in fact gives interpretable results. We present simulation results that demonstrate our algorithm being able to dynamically learn utilities and efficiently select networks. © 2007 IEEE.
- KSP Keywords
- Dynamic Network, Kernel Learning, Kernel regression, Multi-attribute utility theory, Network selection, Non-Stationary, Stochastic Gradient Descent, mobile environment, new algorithm, new method, simulation results