Throughput Optimal and Fast Near-Optimal Scheduling with Heterogeneously Delayed Network-State Information (Extended Version)

We consider the problem of distributed schedulingin wireless networks where heterogeneously delayed informationabout queue lengths and channel states of all links are availableat all the transmitters. In an earlier work (by Reddy et al. inQueueing Systems, 2012), a throughput optimal scheduling policy(which we refer to henceforth as the R policy) for this setting wasproposed. We study the R policy, and examine its two drawbacks– (i) its huge computational complexity, and (ii) its non-optimalaverage per-packet queueing delay. We show that the R policyunnecessarily constrains itself to work with information that ismore delayed than that afforded by the system. We propose a newpolicy that fully exploits the commonly available information,thereby greatly improving upon the computational complexityand the delay performance of the R policy. We show that ourpolicy is throughput optimal. Our main contribution in this workis the design of two fast and near-throughput-optimal policies forthis setting, whose explicit throughput and runtime performanceswe characterize analytically. While the R policy takes a fewmilliseconds to several tens of seconds to compute the scheduleonce (for varying number of links in the network), the runningtimes of the proposed near-throughput-optimal algorithms rangefrom a few microseconds to only a few hundred microseconds,and are thus suitable for practical implementation in networkswith heterogeneously delayed information.