Adaptive threshold-based scheduling for real-time and non-real-time traffic

A study on scheduling mixed real-time and nonreal-time traffic is presented. The work is motivated by the need to provide satisfactory performance tradeoffs in a dynamic load condition where the arrival rates and proportions of the real-time and nonreal-time packets vary with time. The authors first examine two threshold-based schemes, queue length threshold and minimum early threshold, and propose the corresponding adaptive schemes based on results from approximate analysis and simulation. The idea is to improve performance by adjusting tradeoff points adaptively as the arrival rates change. The authors further discuss the idea of integrating the two thresholds. The new algorithm ADP, is evaluated by simulation under various load conditions and compared with other common scheduling disciplines as well as an optimal offline algorithm. It is concluded that, by setting appropriate threshold functions in accordance with the requirements of applications, one can achieve satisfactory bounded loss ratio for real-time packets and acceptably low average delay for nonreal-time packets in a wide range of workload conditions