Study On Overload Control And Convergence In Intelligent Network

Intelligence Network(IN) separates the control function from the switch function with its open frame for service and it can generate the new service rapidly, expediently, agilely, economically and effectively. As the platform of the value-added service, IN has become the necessary topic to study in the domain of mobile communication. The concentration of service control brings immense service traffic and high load to Service Control Point(SCP), so overload control in SCP becomes a sixty-four-dollar question, and overload control algorithms become an intensive focus. Meanwhile the service upgrade in wireless intelligent network(WIN), which converges with Location Based Service(LBS) and Next Generation Network(NGN), is very important for future mobile communication system.This dissertation has been on studying overload control algorithms and convergence technique. Author presents some new overload control algorithms with considering the architecture feature and service traffic characteristic of mobile intelligent network. At the same time, according to service request of WIN and the characteristic of future mobile network, corresponding solution of location based charge(LBC) is presented, and resolvent of interaction is designed between WIN and Softswitch.The results of study and main idea in the paper are given as follows:(1) studying on robustness of the token bucket algorithm between different token banks under a p rate. According to the data current velocity and wave characteristic, which are used to control the velocity of token bucket, a fuzzy control algorithm is given. The results of simulation prove that this algorithm not only has robustness of token bucket algorithm, but improves the data processing speed and effectively reduces the lost data. To some extent, it keeps network from congestion and also alleviate high burden of SCP.(2) studying on three typical algorithms for overload control in intelligent...