AbstractsMathematics

Next Generation of Wireless Networks (NGWNs) are heterogeneous and consist of several Radio Access Technologies (RATs) that coexist in the same geographical area. This heterogeneity of wireless networks is supposed to support multiple mobile terminal calls coming simultaneously to the RATs. NGWNs have to handle the Quality of Services (QoS) of any incoming user calls and manage the in ow of calls into the RATs. Congestion problem arises wherever there are multiple incoming user calls; especially during peak hours of the day. Several attempts have been made, as extracted from literature, to control this problem. This research is also a study that seeks to proffer solutions to improve congestion control in Heterogeneous Wireless Networks (HWN). Recent techniques for solving the congestion control problem are the application of the dynamic pricing and the Joint Call Admission Control (JCAC) algorithm. Dynamic pricing proposes incentives to users by increasing or decreasing the price of calls to encourage users to make calls during the off peak period while discouraging users from making calls during the peak period in a day. The Service Class-based JCAC (SCJCAC) algorithm is a technique that admits calls into a suitable RAT, based on the classes of services in such a way that different RATs are optimized in order to support the different classes of services. These two methods are used together to reduce congestion in the HWN. In this research, two recent dynamic pricing for congestion control are investigated, these schemes are compared and furthermore, a SCJCAC algorithm is proposed and modelled by using the multi-dimensional Markov process model for controlling congestion during the peak hours of the day in the HWNs. The simulation evaluates the performance of the proposed SCJCAC algorithm, while the two dynamic pricing schemes are also compared to the at-pricing scheme during the peak hours.