.png){kind=icon}
返回
An Upper Bound Solution for Homogeneous Fork/Join Queuing Systems
.png){kind=icon}
PRE
AI
DOI：10.1109/TPDS.2010.168.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, we use dynamic-bubblesort technology [4] to analyze general first-in-first-out K-queue homogenous fork/join queuing (HFJ) systems for any K >= 2. Jobs arrive with a mean rate lambda and a general arrival distribution. Upon arrival, a job forks into K tasks. Task k, k = 1,2, ..., K, is assigned to the kth queuing system, which is a first-in-first-out server with a general service distribution and an infinite capacity queue. A job leaves the HFJ system as soon as all its tasks complete their service. We mathematically prove an upper bound solution for the mean response time that we denote by T-K. The upper bound solution of general K-queue HFJ systems for any K >= 2 is very simple and practical-one only needs to simulate a small number of queues (e. g., 16 queues). The tightness is evaluated by comparing with the simulation of thousands of queues for three different HFJ cases. The maximum offset for our upper bounds over all the simulations is less than 5 percent. The corresponding source codes (reusable) are offered on our website for others to use.
Keyword:
Modeling and prediction
queuing theory
performance evaluation
parallel simulation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6
论文数:
5.2K
被引数:
1.1W
机构
暂无机构信息
引用论文
Mechanism of BDNF modulation in GABAergic synaptic transmission in healthy and disease brains.png)
IF0
PREAI
分享收藏Cortical feedback signals generalise across different spatial frequencies of feedforward inputsNeuroImage
OAAI
NeuroImageIF0
OAAI分享收藏
查看更多内容