Abstract
We study two convex optimization problems in a multi-class M/G/1 queue with adjustable service rates: minimizing convex functions of the average delay vector, and minimizing average service cost, both subject to per-class delay constraints. Using virtual queue techniques, we solve the two problems with variants of dynamic cμ rules. These algorithms adaptively choose a strict priority policy, in response to past observed delays in all job classes, in every busy period. Our policies require limited or no statistics of the queue. Their optimal performance is proved by Lyapunov drift analysis and validated through simulations.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
