Research On Key Technologies Of Content-Based Realtime Charging

The combination of the mobile communication networks and the Internet world leads to an unprecedented revolution in mobile services.This is a new challenging task for mobile charging and billing systems with the coming of varied services, expanding value chains, and competitive business models. Traditional extensive methods,such as flat-rate,time-based,and volume-based charging, have been unable to meet new requirements of data value-added services. People begin to seek for intensive charging models based on content and value. Therefore, content-based billing has become an important hotspot in support system researches for 3G and next generation networks.This dissertation mainly focuses on the two parts of the contented-based billing architecture and the key technologies of realtime charging. For the first part, a new policy-based charging billing architecture is proposed on the basis of the standard specifications. For the seconde part, related algorithms are provided to solve the technical problems of realtime charging for the contented-based billing from three aspects, which are content-based differentiated services, content-based load balancing, and account-sharing charging for multi-services. Furthermore, simulation experiments are implemented to verify the correctness and to analyze the performance of these algorithms.The principal contributions of the work presented in this dissertation are as follows:(1) For the research on the content-based billing architecture, an ePCC (enhanced Policy and Charging Control) structre is proposed based on the standard specifications of 3GPP for the UMTS (Universal Mobile Telecommunications System) charging and the FBC (Flow Based Charging) of IMS (IP Multimedia Subsystem).Unlike the FBC which only provides the policy and charging control for bearer level, the ePCC model extends the ability to all levels of the network and considers the data convergence of online charging and offline charging systems, which fully supports the functions of content-based billing, such as intelligent data acquisition, charging correlation, value-based charging, convergent billing, and revenue sharing of value chain. Furthermore, the design of the realtime charging system under the ePCC architecture is elaborated on.(2) For the research on the content-based differentiated services, the charging requests sent to State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications the OCS (Online Charging System) from different network elements are divided into different classes of queues based on the varied contents of requests.The Internet PDD (Proportional Delay Differentiation) model is used in OCS (Online Charging System) servers, which aims to maintain pre-specified mean system response-time delay ratios between different classes of requests, and it can achieve the content-based relative differentiated services. A novel algorithm of PSQLAR (Probabilistic scheduling based on System Queue Length and Arrival Rate) is proposed for the PDD model.The basic idea is that one of the requests from all classes of service queues is chosen with some priority probability which is based on the system queue-length, the request arrival rate, and the pre-assigned delay differentiation parameter. The experimental results show that, in considering request service delays, the PSQLAR algorithm always outperforms some other traditional PDD scheduling ones and the performance advantages are relatively greater when request service delays increase and vary greatly from each other. Furthermore, it can efficiently meet 6 QoS (Quality of Service) requirements proposed in content-based billing.(3) For the research on the content-based load balancing, the charging requests of varied contents are divided different classes and the load differences of each class are taken as the key points of consideration for load balancing strategies. Based on it, a LCMC (Least Common Multiple Capacity) load-balancing algorithm is proposed. This algorithm considers the difference between processing capacity of each server, the run-time load of each server, and especially the difference between various request load, distributing requests by the probability approach. Experimental results show that LCMC significantly outperforms some traditional load-balancing algorithms in the system of high heterogeneous cluster and high heterogeneous request load, and meets the unique characteristics of the OCS cluster in content-based billing.(4) For the research on the account-sharing charging for multi-services, it focuses on the rationality and effectiveness of resource allocation for concurrent charging requests of different contents on the same account. A new algorithm of 3R (resource Reservation, Reclamation, and Redistribution based on QoS) is proposed,which introduces resource reclamation and redistribution processes based on the resource reservation of 3GPP standard specifications and dynamically adjusts them according to the changes of QoS.Three performance indexes are investigated in the simulation experiments, which are average number of accommodated sessions, average number of completed sessions, and average number of iterations per accommodated session. The results show that 3R outperforms the same type of other algorithms in the normal QoS level, arid the performance advantages are much better when the QoS is poor.