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Context Awareness and Class of Service Satisfaction for Modeling Handover Decision-Making

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 47 - Number 20
Year of Publication: 2012
Sassi Maaloul
Afif Mériem
Sami Tabbane

Sassi Maaloul, Afif Mriem and Sami Tabbane. Article: Context Awareness and Class of Service Satisfaction for Modeling Handover Decision-Making. International Journal of Computer Applications 47(20):6-15, June 2012. Full text available. BibTeX

	author = {Sassi Maaloul and Afif Mriem and Sami Tabbane},
	title = {Article: Context Awareness and Class of Service Satisfaction for Modeling Handover Decision-Making},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {47},
	number = {20},
	pages = {6-15},
	month = {June},
	note = {Full text available}


The next generation mobile system is expected to support the continuous increase of users requirements. Through the high flow rates of these networks, new applications constraints are more complex and may be change dynamically and rapidly for wireless systems. The service heterogeneity provided by these applications has a great influence on system performance in terms of ability, availability and the context aware provided to make handover decision. To facilitate the negotiation process between the user and the network, we define some class of service that guarantees QoS for interworking between 3GPP and non-3GPP networks and the critical context criteria which influence the handover decision. In this context, our proposed approach supports the interaction between context-aware and class of service considering the use of the particular features of each class of service to make handover decision and providing the application required QoS. In this paper we conceive a new approach, called Enhance Simple Additive Weighting, for network selection that reduces computational complexity, the handover latency and eliminates networks which do not satisfy a minimum requirement compared to other existing approaches based on AHP strategy.


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