Proceedings ArticleDOI
Topsis based delay sensitive network selection for wireless body area networks
R. Latha,P. Vetrivelan +1 more
- pp 736-739
TLDR
TOPSIS method is used for taking decision in delay sensitive network selection for achieving reliability of network selection with Wireless Body Area Network (WBAN) parameters; viz. end-to-end-delay, network lifetime and throughput.Abstract:
Multi Criteria Decision Making (MCDM) is useful for choosing a possible objective. The objective is to investigate how far TOPSIS method of MCDM can be utilized for delay sensitive network selection problem. In this paper, TOPSIS method is used for taking decision in delay sensitive network selection for achieving reliability of network selection with Wireless Body Area Network (WBAN) parameters; viz. end-to-end-delay, network lifetime and throughput. The best solution for selecting a network model is ranked using this method. MCDM uses infinite number of alternatives for analysis. TOPSIS compares the attributes of each alternative, normalizes each attribute and also calculates the distance of each alternative from the ideal solution.read more
Citations
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Journal ArticleDOI
Adaptive Multiservice Heterogeneous Network Selection Scheme in Mobile Edge Computing
TL;DR: Compared with commonly used simple additive weighting (SAW), random access selection (RAS), and price-based and QoS-based network selection scheme, this scheme has better performance in improving average user satisfaction and reducing access failures.
Book ChapterDOI
A Framework for Selecting Machine Learning Models Using TOPSIS
Maikel Yelandi Leyva Vazquezl,Luis Andy Briones Peñafiel,Steven Xavier Sanchez Muñoz,Miguel Angel Quiroz Martinez +3 more
TL;DR: The deductive method and the scanning research technique were applied to study a case study on the Wisconsin Breast Cancer dataset, which seeks to evaluate and compare the performance and effectiveness of machine learning models using the TOPSIS.
Proceedings ArticleDOI
i5GAccess: Nash Q-learning Based Multi-Service Edge Users Access in 5G Heterogeneous Networks
Anqi Zhu,Songtao Guo,Mingfang Ma +2 more
TL;DR: The network selection problem for edge users is formulated as a discrete-time Markov model, and a Nash Q-learning based intelligent network access algorithm for multi-agent system, named MAQNS is proposed.
References
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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