Queuing with future information.

study an admissions control problem, where a queue with service rate 1 - p receives incoming jobs at rate lambda epsilon (1 - p, 1), and the decision maker is allowed to redirect away jobs up to a rate of p, with the objective of minimizing the time-average queue length. We show that the amount of information about the future has a significant impact on system performance, in the heavy-traffic regime. When the future is unknown, the optimal average queue length diverges at rate similar to log(1)/(1-p) 1/1-lambda, as lambda -> 1. In sharp contrast, when all future arrival and service times are revealed beforehand, the optimal average queue length converges to a finite constant, (1 - p)/p, as lambda -> 1. We further show that the finite limit of (1 - p)/ p can be achieved using only a finite lookahead window starting from the current time frame, whose length scales asO (log 1/1-lambda), as lambda -> 1. This leads to the conjecture of an interesting duality between queuing delay and the amount of information about the future.