Modeling and Analyzing Gap-Utilized Handover in Wireless Networks

Handover interruption as a critical issue has long been studied in wireless networks towards a seamless and lossless target. This paper proposes a model for gap-utilized handover, using traffic-pattern learning based on HMM, and presents the analytic details regarding to the QoS performance. The handover exploiting traffic gaps, i.e., periods of no packet transferred, can reduce packet loss/delay and hence increase user´s experience. Our model supports a large portion of traffics/applications and distinguishes different loss in association with different hidden states. We further study two representatives of real-time applications - online gaming and voice conversation -having them involved in simulations for validation. Result has proved the effectiveness of the gap-utilized handover as well as the correctness of our model.