We consider a multi-class G/G/1 queue with a finite shared buffer. There is task admission and server scheduling control which aims to minimize the cost which consists of holding and rejection components. We construct a policy that is asymptotically optimal in the heavy traffic limit. The policy stems from solution to Harrison-Taksar (HT) free boundary problem and is expressed by a single free boundary point. We show that the HT problem solution translated into the queuelength processes follows a specific {\it triangular} form. This form implies the queuelength control policy which is different from the known $c\mu$ priority rule and has a novel structure. We exemplify that the probabilistic methods we exploit can be successfully applied to solving scheduling and admission problems in cloud computing.
翻译:我们考虑的是带有有限共享缓冲的多级 G/G/1 队列。 有任务接收和服务器调度, 目的是将持有和拒绝部分构成的成本降到最低。 我们设计的政策在沉重的交通限制方面是无处不在的优化的。 该政策源于对哈里森- 塔克萨尔(HT) 自由边界问题的解决方案, 并以单一的自由边界点表示。 我们显示, 转换成队列长过程的 HT 问题解决方案遵循特定的 ~it三角} 形式。 此形式意味着队列控制政策, 它不同于已知的$c\ mu$优先规则, 并且具有新的结构。 我们举例说明, 我们所利用的概率方法可以成功用于解决云计算中的排程和录入问题 。