A genetic algorithm approach for multi-attribute vertical handover decision making in wireless networks

Ali F. Almutairi (), Mohannad Hamed (), Mohamed Adnan Landolsi () and Mishal Algharabally ()
Additional contact information
Ali F. Almutairi: College of Engineering and Petroleum, Kuwait University
Mohannad Hamed: College of Engineering and Petroleum, Kuwait University
Mohamed Adnan Landolsi: College of Engineering and Petroleum, Kuwait University
Mishal Algharabally: College of Engineering and Petroleum, Kuwait University

Telecommunication Systems: Modelling, Analysis, Design and Management, 2018, vol. 68, issue 2, No 2, 161 pages

Abstract: Abstract Mobile terminals can typically connect to multiple wireless networks which offer varying levels of suitability for different classes of service. Due to the changing dynamics of network attributes and mobile users’ traffic needs, vertical handovers across heterogeneous networks become highly desirable. Multiple attribute decision making (MADM) techniques offer an efficient approach for ranking competing networks and selecting the best one according to specific quality of service parameters. In this paper, a genetic algorithm (GA) is applied to optimize network attributes’ weighting by emphasizing ranking differences among candidate networks, thereby aiding correct decision making by reducing unnecessary handovers and ranking abnormalities. The performance of the proposed GA-based vertical handover is investigated with typical MADM techniques including Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The results show that the proposed GA-based weight determination approach reduces the abnormality observed in the conventional SAW and TOPSIS techniques substantially. The results of this paper will help ensuring the application of MADM methods to more dynamic and challenging decision making problems encountered in wireless network.

Keywords: Vertical handover; Multiple attribute decision making; Wireless networks; Genetic algorithm (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11235-017-0364-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:telsys:v:68:y:2018:i:2:d:10.1007_s11235-017-0364-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/11235

DOI: 10.1007/s11235-017-0364-6

Access Statistics for this article

Telecommunication Systems: Modelling, Analysis, Design and Management is currently edited by Muhammad Khan

More articles in Telecommunication Systems: Modelling, Analysis, Design and Management from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().