| With the rapid development of communication and transmission technology, it's obvious that next generation networks have the capability to undertake voice, data and multimedia services simultaneously. More and more people are taking advantage of networks in work, study, entertainment. So, the Quality of Service (QoS) are becoming more concerned by subscribers and network owners, for subscribers will not like their charged Qos to be damaged and network owners want their profit to be maximized. The research on network QoS always accompanies the development of network. Because the application type, network capacity and structure continue to evolve, which in turn leads to the change of traffic and subscriber's requirement, the algorithms on providing QoS also need to change. So, QoS was, is and will always be the hot problem for networks to be researched.QoS problem is not a self-existent problem, but has close relationship with resource management problems. Resource management problems usually described as solving an optimal problem restricted to some QoS conditions. Call Admission Control (CAC) which is an aspect of resource management has the same model. The research in this paper includes two parts. One is fundamental research on traffic model error, traffic model and mobility model. The other is application research on dynamic bandwidth allocation for multi-service.First, the error of traditional traffic model applied to time-division system was analyzed. Traffic model is the foundation that the resource management researches rely on. In traditional traffic model, calls were assumed to be accepted at the moment they arrived. However, it's not true in real system because in real system time was slotted. However, how the difference between model and reality made effect was neglected by traffic model researchers. According to author, the related papers were not found till now. In this paper, this effect was studied and uncovered from mathematical root. Besides, based on Interrupt Poisson Process (IPP) traffic model, the mean traffic formula of slotted IPP and error approximate formulas of traditional IPP were derived and given. Simulation results showed the high consistence of mean traffic of slotted IPP with experiments, which indicated the slotted IPP had more precision than traditional IPP traffic model. The error approximation formula of traditional IPP model was also verified through experiments. It explicitly demonstrated that the traditional traffic model will be precise enough as long as the time slot is little enough. This conclusion provided a theoretic support for the easy using of traditional traffic model due to the trifle time slot in real system. Thus, the traffic model error will not be considered again in the future traffic model researches.On the execution of CAC, one must know the network traffic. The network traffic usually attained through two methods. One is from traffic model and the other is by measurement. There were five commonly used traffic models for CAC. They had different benefits and disadvantage each. However, there is a lack of such a traffic model which can describe the dynamic network traffic and has relatively simple calculation complexity. In this paper, a new traffic model, called enhanced ON/OFF traffic model, was put forward. Basing on traditional ON/OFF traffic model, it modified the assumed constant rate in traditional model into stochastic rate, the constant transition probability into persistence time distribution of state ON, and added burst arrival time distribution as known condition. As a result, it overcame the defect in traditional ON/OFF traffic model that the dynamic traffic couldn't be described. The dynamic traffic distribution and mean traffic formula of enhanced ON/OFF traffic model were derived and given. Besides, based on the widely used Poisson process model for bursts arrival and exponential distribution model for call persisting time, the dynamic traffic distribution and mean traffic formulas were derived and given. And simplified formulas for probability calculations in above formulas were provided. Simulations to the mean traffic showed the validity of theoretic results.In cellular communication system, the mobility of subscribers has great effect on the performance of a cell. Many models had been built for the mobility of subscribers. However, owing to too many factors'affection, the mobility models were very complex, and the results may not applicable for real system. In this pater, a general mobility model was proposed for cellular communication system. The proposed mobility model assumed directly that the channel holding time distribution was known by beforehand measurements. It divided the calls in a cell into three types, namely local calls, calls which will hand off to neighbor cells, calls handed over from neighbors. When the channel holding time distribution of these three type calls were known, the occupied bandwidth of a cell can be predicted from the results of enhanced ON/OFF traffic model in chapter three. By using this general mobility model, the defect which existed in many previous models that the bandwidth allocation unit was not bytes but channels, which was not suitable for packet switching system, was overcome. Based on this general mobility model, a CAC scheme which accepts calls at a given probability was put forward, and the corresponding optimization equations were given. Simulations were conducted and results were analyzed on this CAC scheme in the end.In order to solve the QoS problem for all services sharing system bandwidth, the Differentiated Service QoS model was proposed by IETF, which partitions the system bandwidth into sub-bandwidths for different services. The defect of many previous bandwidth allocation algorithms was that the allocation unit was channel but not byte, so the partition granularity was too large and meaningless for packet switch network. In this chapter, a new bandwidth allocation scheme was put forward which had very small granularity for partition. It took advantage of a CAC formula based on effective bandwidth. The formula gave an equation for maximum users and system capacity under the restriction of bandwidth overflow probability. On the precondition that the minimum allocated bandwidth satisfied the current user number, the scheme tried to attain the quotas of all services'bandwidth by searching method. The object of the scheme was to maximize the sum of all effective bandwidths of all services under those bandwidth quotas. The partition granularity depended on the length of searching step, so it was controllable. As an example, and for the need of simulation, a group of concrete optimal equations were derived and given when the service bandwidth obeys to exponential distribution. Based on this, simulations of bandwidth allocation between two services were conducted.
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