Admission Control for ATM High-Speed Networks

ATM ATM（异步传输模式）高速网络承载着各种类型的业务，如数字化语音、电影、编码视频和数据等。近年来，许多研究者发现ATM高速网络中的业务具有自相似性和长时相关性等复杂特性。此外，作为衡量服务质量的标准，（服务质量），由于缓冲器溢出而导致的分组丢失概率需要控制在非常小的水平以下，例如，在10^的数量级<-9>。因此，确定罕见事件概率和执行接纳控制变得非常重要，以便为ATM高速网络提供QoS要求的保证。在本研究中，我们考虑了由两个并行队列组成的ATM高速网络，它们通常用于建模具有两种不同类型的业务的通信系统：实时流量（如语音和视频）和非实时流量 ...更多信息 数据（Data）。我们分析了系统在不同到达过程下的尾部行为。利用大偏差技术推导出了缓冲区溢出概率的上、下界，并给出了相应的接纳控制算法。利用有限缓冲区排队模型和保护信道对无线移动的网络进行了性能分析。具体来说，我们分析了以下几个系统。（一）（1）两类单服务器的离散时间轮询系统。到达过程是马尔可夫调制过程，服务时间表是伯努利过程。（2）两类多服务器的离散时间轮询系统。到达过程是一般的，服务时间表是马尔可夫的。对于这两种轮询系统，我们推导了丢包率的大偏差上、下界，并给出了相应的接纳控制算法。（2）针对马尔可夫轮询系统，推导了丢包率的大偏差上、下界，并将结果应用于无线移动的网络。（3）采用有限缓冲区排队模型对无线移动的网络进行建模，并利用递归算法推导出稳态分布。少

ATM(Asynchronous Transfer Mode) high-speed networks accommodate various types of traffic such as digitized voice, movie, encoded video and data, etc. Recently, it has been reported by many researchers that traffics in ATM high-speed networks have many complicated properties-self-similarity and long-terms dependence, etc. Furthermore, as the criterion for evaluating QoS(quality of service) of such ATM networks, the packet loss probabilities due to the buffer overflow are required to control below very small level, e.g., in the order of 10^<-9>. Thus, determining the rare event probability and performing the admission control become very important in order to provide the guarantee of QoS requirements for ATM high-speed networks.In the present study, we have considered ATM high-speed networks consisting of two-parallel queues, which are generally used in modeling communication systems with two different types of the traffics : real-time traffic(such as voice and video) and non-real-time t … More raffic(such as data). We analyzed the tail behavior of the systems under various arrival processes. Then, we derived the upper and lower bounds of the buffer overflow probabilities using the large deviations techniques, and provided the admission control algorithms. We also carried out the performance analysis for wireless mobile networks by using the finite buffer queueing models with the guard channels. Concretely, we have analyzed the following systems.(I)(1)the discrete-time polling system with two classes and a single server. The arrival processes are Markov-modulated processes and the service schedule is Bernoulli. (2)the discrete-time polling system with two classes and multiple servers. The arrival processes are general and the service schedule is Markovian. For those two polling systems, we derived the large deviations upper and lower bounds of the packet loss probabilities and presented the admission control algorithm.(II)For Markovian polling systems, we derived the large deviations upper and lower bounds of the packet loss probabilities, and applied the results to wireless mobile networks.(III)We modeled wireless mobile networks by using finite buffer queueing models, and derived the steady-state distributions using recursive algorithm approach. Less