大任务提前到来:从关键队列到随机图

Q1 Mathematics Stochastic Systems Pub Date : 2017-04-11 DOI:10.1287/stsy.2019.0057
G. Bet, R. van der Hofstad, J. V. van Leeuwaarden
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引用次数: 6

摘要

我们考虑一个只有有限的n个客户池才能到达的队列,有时取决于他们的服务需求。具有随机服务需求S的客户在指数分布时间后到达队列,其中一些客户的平均S-α[公式:见正文];因此,更大的服务需求促使客户更早地加入。这个有限池队列在两个先前研究的情况之间插值:α=0给出了所谓的[公式:见正文]队列,α=1与非齐次随机图的探索过程密切相关。我们考虑池大小n增长到无穷大的渐近状态,并建立了缩放队列长度过程收敛于具有负二次漂移的扩散过程。我们利用这一渐进结果来表征创造长期活动所需的领先优势。我们还描述了队列的第一个繁忙时段如何产生临界连接的随机林。
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Big Jobs Arrive Early: From Critical Queues to Random Graphs
We consider a queue to which only a finite pool of n customers can arrive, at times depending on their service requirement. A customer with stochastic service requirement S arrives to the queue after an exponentially distributed time with mean S-αfor some [Formula: see text]; therefore, larger service requirements trigger customers to join earlier. This finite-pool queue interpolates between two previously studied cases: α = 0 gives the so-called [Formula: see text] queue and α = 1 is closely related to the exploration process for inhomogeneous random graphs. We consider the asymptotic regime in which the pool size n grows to infinity and establish that the scaled queue-length process converges to a diffusion process with a negative quadratic drift. We leverage this asymptotic result to characterize the head start that is needed to create a long period of activity. We also describe how this first busy period of the queue gives rise to a critically connected random forest.
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来源期刊
Stochastic Systems
Stochastic Systems Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
3.70
自引率
0.00%
发文量
18
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