Abstract
We study the convexity of loss probability in communications and networking optimization problems that involve finite buffers, where the arrival process has a general distribution. Examples of such problems include scheduling, energy management and revenue, and cost optimization problems. To achieve a computationally tractable optimization framework, we propose to adjust an existing nonconvex loss probability formula for G/D/1 queues to present a convex and even more accurate loss probability model. We then use empirical data and computer simulations to examine the performance of the proposed design.
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.
