Open Collections

Adaptive threshhold-based scheduling for real-time and non-real-time tasks

University of British Columbia

This thesis documents our study on scheduling mixed real-time and non-real-time tasks with different performance metrics. The work is motivated by the need to provide satisfactory performance trade-offs in a dynamic environment where the arrival rates and proportions of the real-time and non-real-time tasks vary with time. We first examine two threshold-based schemes, Queue Length Threshold and Minimum Laxity Threshold, and propose the corresponding adaptive schemes based on our results from approximate analysis and simulation. The idea is to improve performance by adjusting trade-off points adaptively as the arrival rates change. We 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 algorithm. Some implementation issues are also discussed. We conclude that by setting appropriate threshold functions in accordance to the requirements of applications, we can achieve satisfactory bounded loss ratio for real-time tasks and acceptably low average delay for non-real-time tasks in a wide range of workload conditions.

Text

2010-11-10

For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.

http://hdl.handle.net/2429/29913

Computer Science

University of British Columbia

Graduate