Reliable Vertical Handoff Technique Based on Probabilistic Classification Model
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The Next Generation wireless network framework has introduced cooperative communication philosophy to provide better service to the clients. Vertical Handoff is one such cooperative technique, which switches the client’s network from the current to another in-order to continue providing requested Quality of Service (QoS). There are multiple parameters that need to be considered for achieving vertical handoff such as-service cost, data rate, mobile device speed, network latency, interference ratio, device battery level, Received Signal Strength Information (RSSI) etc.
Until now, vertical hand off schemes have targeted to achieve effective selection of suitable alternate networks in providing required connection transfer. Many classification schemes based on Neural Networks, Support Vector Machine were utilized in designing vertical handoff techniques. These techniques do a good job in choosing suitable alternate networks, but, once the handoff is made, there is no guarantee that, the new network will continuously provide the requested QoS. The client might require new handoff if the recently migrated network is not able to deliver the specified QoS. Frequent handoff’s can be expensive and inefficient for the client. Ideally, when making the first handoff, it is important to consider the reliability of new networks in continuously providing the requested QoS. In the existing literature, this problem has not been properly addressed.
In this work, new vertical handoff scheme is proposed, which addresses the reliability issue. This proposed vertical handoff scheme is built over probabilistic classification model. Empirical results obtained through simulation, reveal the excellent effectiveness of the proposed vertical handoff scheme.
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