基于测量的自相似接纳控制算法研究

Call Admission Control Algorithm Based on Measurement in Network with Self-similar Traffic

传统的接纳控制算法中,基于参数的接纳控制提供严格的QoS保证但带宽利用率和接纳率低,基于测量的接纳控制具有较好的动态特征和适应性但对模型有较严格的要求,并且未考虑网络流量的自相似特性.本文根据网络流量自相似特性,将基于参数的接纳控制与基于测量的接纳控制方法相结合,提出了基于测量的自相似接纳控制算法和基于自相似测量的自适应接纳控制算法.仿真结果表明,该算法能够提高自相似网络流量环境下的接纳率和平均带宽利用率.

Self-similarity is not considered in the traditional Call Admission control Algorithms, such as Admission Control based on parameters and Admission Control based on measurement. Admission Control based on parameters often provides the strictest QoS gurantee with lowest admission ratio and worst bandwidth usage. Admission Control based on measurement considers the dynamic changes of network traffic with better admission ratio and bandwidth usage. Taking advantage of the self-similarity character, and combining the admission control algorithm based on parameters with that based on measurement, the admission control algorithms based on measurement with self-similarity character and the adaptive admission control algorithm based measurement were proposed. The extensive simulations have shown that the algorithms can improve admission ratio and average bandwidth usage.