An Adaptive Measurement-Based Admission Control Algorithm
Ma Xiao · Chinese Journal of Computers · 2001
In contrast to traditional admission control mechanisms, the most attractive feature of Measurement Based Admission Control (MBAC) is that it does not require an apriori traffic model, because it is very difficult or even impossible for the user or application to come up with a tight traffic model before establishing a flow. Other advantages of MBAC include that an overly conservative specification does not result in an over allocation of resources for the entire duration of the session, and it can adapt to the changing traffic load dynamically, so it improves the network utilization while offering quality of service to users.This paper first studies how MBAC works. Existing MBACs adopt the fixed length Time window Measurement Mechanism to estimate the network traffic load L CL . There are two important parameters (measurement window T and sampling window S ) that impact the estimation of L CL . Because S has smaller impact than T , in this paper, we only consider T . In MBAC, small T means more adaptability and higher resource utilization, but larger T results in greater stability and lower resource utilization. Hence, to select an appropriate T is very important for MBAC. To solve this problem, we propose an Adaptive Measurement Based Admission Control (AMBAC) algorithm. In AMBAC, we set two thresholds: L T max and L T min . When the measured traffic load L CL is larger than L T max , our algorithm enlarges T automatically, which makes AMBAC more conservative and hence decreases the network's admission ability. When L CL is smaller than L T min , our algorithm shrinks T , which improves the network's admission ability. When L CL is between L T max and L T min , our algorithm does not alter T . By altering T , AMBAC makes the network adapt to the changing traffic load dynamically, so the network utilization is improved. To evaluate AMBAC we implemented our algorithm on FreeBSD. We test it under different traffic scenarios and compare it with the traditional MBAC. Our simulation results show AMBAC can get lower packet loss while achieving a high level of utilization.