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ThinkMind // International Journal On Advances in Networks and Services, volume 6, numbers 3 and 4, 2013 // View article netser_v6_n34_2013_5


Integrated Fuzzy Solution for Network Selection using MIH in Heterogeneous Environment

Authors:
Ahmad Rahil
Nader Mbarek
Olivier Togni
Mirna Atieh

Keywords: seamless vertical handover; QoS parameters; IEEE 802.21 MIH; fuzzy logic modeling

Abstract:
Seamless handover between networks in heterogeneous environment is essential to guarantee end-to-end QoS for mobile users. A key requirement is the ability to select seamlessly the next best network. Currently, the implementation of the selection algorithm of the IEEE 802.21 standard by National Institute of Standards and Technology considers only the signal strength as a parameter to select the best destination network. In this paper, we improve the implementation of the existing selection algorithm by proposing an integrated solution to select the best destination network. Our proposed solution consists of proposing a Multi Criteria Selection Algorithm that modifies the current implemented algorithm by including additional parameters such as available bandwidth, mobile node speed and type of network. This first solution is complemented with a fuzzy logic model, which includes a new controller entity where parameters such as signal strength, signal quality and available bandwidth of the destination networks are considered as inputs. The inference rules for the controller entity are derived from a detailed analysis made on a large number of data retrieved from the servers of Alfa mobile telecommunications company. The results, initially obtained using Network Simulator, show that there is a need for a new framework taking into account additional parameters to guide network selection process during handover in order to provide mobile users with better QoS. They were then complemented with a model that qualified each candidate network in the vicinity of the mobile based on a scale of 0 (the least advisable network) and 1 (the most recommended network). This will lead to the mobile node choosing the network that has the maximum likelihood estimation between a set of recommended networks.

Pages: 175 to 187

Copyright: Copyright (c) to authors, 2013. Used with permission.

Publication date: December 31, 2013

Published in: journal

ISSN: 1942-2644

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