Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 188 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 29 tok/s Pro
GPT-5 High 27 tok/s Pro
GPT-4o 57 tok/s Pro
Kimi K2 192 tok/s Pro
GPT OSS 120B 431 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Effect of payload size on mean response time when message segmentations occur using $\rm{M}^{\rm X}/\rm{G}/1$ queueing model (1803.10553v1)

Published 28 Mar 2018 in cs.PF

Abstract: This paper proposes the $\rm{M}{\rm X}/\rm{G}/1$ queueing model to represent arrivals of segmented packets when message segmentations occur. This queueing model enables us to derive the closed form of mean response time, given payload size, message size distribution and message arrival rate. From a numerical result, we show that the mean response time is more convex in payload sizes if message arrival rate is larger in a scenario where Web objects are delivered over a physical link.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (1)

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.