Computer
Policy-Enabled Handoffs Across Heterogeneous Wireless Networks
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
A user-centric analysis of vertical handovers
Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots
An overview of vertical handover decision strategies in heterogeneous wireless networks
Computer Communications
Computer Networks: The International Journal of Computer and Telecommunications Networking
Towards autonomic handover decision management in 4g networks
MMNS'06 Proceedings of the 9th IFIP/IEEE international conference on Management of Multimedia and Mobile Networks and Services
IEEE Wireless Communications
Providing seamless mobility using the FOCALE autonomic architecture
NEW2AN'07 Proceedings of the 7th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking
An Autonomic QoS-centric Architecture for Integrated Heterogeneous Wireless Networks
Mobile Networks and Applications
Proceedings of the 14th Communications and Networking Symposium
Analysis of Ongoing SIP Session with Resource Reservation in Vertical Handover Scenario
Wireless Personal Communications: An International Journal
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In this paper, we present an autonomic management method to provide personalized handover decisions for customized mobility management in heterogeneous wireless networks. A handover decision is a significant problem, especially in a heterogeneous network environment. This is exacerbated when the goal is to provide personalized services for mobile users. Personalized handover decisions should not only consider received signal strength, which is a traditional handover decision factor, but also context information, user preferences, user profiles, and other non-functional requirements. We present two metrics for evaluating access points: access point acceptance value and access point satisfaction value. Our algorithm uses a combination of functional and non-functional metrics to select the access point that has the maximum satisfaction value. In our simulation study, we show that our decision algorithm is better than other decision algorithms in terms of end user satisfaction.