网络随机分析的半下鞅方法
An Approach using Demisubmartingales for the Stochastic Analysis of Networks
摘要：
随机网络演算（英语：Stochastic network calculus）是网络演算的概率版本，它使用包络线来执行随机网络的概率分析。使用网络演算计算的概率性端到端延迟或积压边界的准确性一直是一个问题。在本文中，我们提出了新的端到端的概率界的基础上的下鞅不等式，改进了现有的边界的串联网络的GI/GI/1队列。特别是，我们表明，合理准确的界限是通过比较新的界限与现有的结果为网络的M/M/1队列。
英文摘要：
Stochastic network calculus is the probabilistic version of the network calculus, which uses envelopes to perform probabilistic analysis of queueing networks. The accuracy of probabilistic end-to-end delay or backlog bounds computed using network calculus has always been a concern. In this paper, we propose novel end-to-end probabilistic bounds based on demisubmartingale inequalities which improve the existing bounds for the tandem networks of GI/GI/1 queues. In particular, we show that reasonably accurate bounds are achieved by comparing the new bounds with the existing results for a network of M/M/1 queues.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
