Predictive and adaptive bandwidth reservation for hand-offs in QoS-sensitive cellular networks
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
A New Adaptive Channel Reservation Scheme for Handoff Calls in Wireless Cellular Networks
NETWORKING '02 Proceedings of the Second International IFIP-TC6 Networking Conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; and Mobile and Wireless Communications
Next-generation wireless communications concepts and technologies
IEEE Communications Magazine
QoS provisioning in cellular networks based on mobility prediction techniques
IEEE Communications Magazine
Distributed call admission control in mobile/wireless networks
IEEE Journal on Selected Areas in Communications
Predictive schemes for handoff prioritization in cellular networks based on mobile positioning
IEEE Journal on Selected Areas in Communications
Local predictive resource reservation for handoff in multimedia wireless IP networks
IEEE Journal on Selected Areas in Communications
Toward an all-IP-based UMTS system architecture
IEEE Network: The Magazine of Global Internetworking
Location prediction model based on Bayesian network theory
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Qos provisioning in mobile networks based on aggregate bandwidth reservation
ISPA'07 Proceedings of the 5th international conference on Parallel and Distributed Processing and Applications
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This paper proposes a novel call admission control (CAC) scheme for wireless and mobile networks. Our proposal avoids per-user reservation signaling overhead and takes into account the expected bandwidth to be used by calls handed off from neighboring cells based only on local information stored into the current cell where user is seeking admission. To this end, we propose the use of two time series-based models for predicting handoff load: the Trigg and Leach (TL), which is an adaptive exponential smoothing technique, and ARIMA (Autoregressive Integrated Moving Average) that uses the Box & Jenkins methodology. These methods are executed locally by each base station or access router and forecast how much bandwidth should be reserved on a periodic time window basis. The two prediction methods are compared through simulations in terms of new call blocking probability and handoff dropping probability. Despite the TL method simplicity, it can achieve similar levels of call blocking probability and handoff dropping probability than those of the computational demanding ARIMA models. In addition, depending on the schemes settings, the prediction methods can grant an upper bound on handoff dropping probability even under very high load scenarios.