SIAM Journal on Control and Optimization
An invariance principle for semimartingale reflecting Brownian motions in an orthant
Queueing Systems: Theory and Applications
State space collapse with application to heavy traffic limits for multiclass queueing networks
Queueing Systems: Theory and Applications
Maximizing throughput in wireless networks via gossiping
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Distributed link scheduling with constant overhead
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Complexity in wireless scheduling: impact and tradeoffs
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing
A Large Deviations Analysis of Scheduling in Wireless Networks
IEEE Transactions on Information Theory
Implementing utility-optimal CSMA
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
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Distributed scheduling algorithms for wireless ad hoc networks have received substantial attention over the last decade. The complexity levels of these algorithms span a wide spectrum, ranging from no message passing to constant/polynomial time complexity, or even exponential complexity. However, by and large it remains open to quantify the impact of message passing complexity on throughput and delay. In this paper, we study the effective throughput and delay performance in wireless scheduling by explicitly considering complexity through a vacation model, where signaling complexity is treated as "vacations" and data transmissions as "services," with a focus on delay analysis in heavy traffic regimes. We analyze delay performance in two regimes of vacation models, depending on the relative lengths of data transmission and vacation periods. State space collapse properties proved here enable a significant dimensionality reduction in the challenging problem of delay characterization. We then explore engineering implications and quantify intuitions based on the heavy traffic analysis.