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Optimal flow control of an M/M/1 queue with a balanced budget

机译:具有平衡预算的M / M / 1队列的最佳流控制

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摘要

The following problem is considered. There are several users who send jobs to an M/M/1 queue and have privately observed information relating to their benefits from the rate of job submissions and their costs due to waiting in the queue. Each user's benefits and costs are unknown to the queue manager and to other users. The manager's objective is to achieve “optimal” flow control, where the optimality depends on arriving at an appropriate trade-off between delay and the job arrival rate assigned to each user: the allocations should be such that no user can be made better off by a reallocation without hurting at least one other user. Since the optimality calculation requires knowledge of the users' private information, we propose an algorithm that converges to the optimum, while inducing users to reveal information relating to their benefits and costs truthfully, and balances the manager's budget. Earlier work on this problem has produced a flow control algorithm that requires the queue manager to incur a potentially huge deficit; this leads to several theoretical and practical problems
机译:考虑以下问题。有几个用户将作业发送到M / M / 1队列,并私下观察到有关其从作业提交率中受益的信息以及由于在队列中等待而导致的成本的信息。队列管理器和其他用户都不知道每个用户的收益和成本。经理的目标是实现“最佳”流程控制,其中最优性取决于在延迟和分配给每个用户的工作到达率之间达成适当的权衡:分配应确保没有用户可以通过以下方式而变得更好重新分配而不会伤害至少一个其他用户。由于最优计算需要了解用户的私人信息,因此我们提出了一种收敛到最优的算法,同时诱使用户如实披露与他们的收益和成本有关的信息,并平衡经理的预算。关于此问题的早期工作已经产生了一种流控制算法,该算法要求队列管理器产生潜在的巨大赤字。这导致了一些理论和实践问题

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