Scheduling real-time traffic with deadlines over a wireless channel
Wireless Networks
Algorithmic Game Theory
eBay in the Sky: strategy-proof wireless spectrum auctions
Proceedings of the 14th ACM international conference on Mobile computing and networking
Revenue generation for truthful spectrum auction in dynamic spectrum access
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
Utility maximization for delay constrained QoS in wireless
INFOCOM'10 Proceedings of the 29th conference on Information communications
Scheduling heterogeneous real-time traffic over fading wireless channels
INFOCOM'10 Proceedings of the 29th conference on Information communications
Opportunistic transmission scheduling with resource-sharing constraints in wireless networks
IEEE Journal on Selected Areas in Communications
Queueing Systems: Theory and Applications
On the performance of largest-deficit-first for scheduling real-time traffic in wireless networks
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing
Optimal scheduling and power allocation in cooperate-to-join cognitive radio networks
IEEE/ACM Transactions on Networking (TON)
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Clients in wireless networks may have per-packet delay constraints on their traffic. Further, in contrast to wireline networks, the wireless medium is subject to fading. In such a time-varying environment, we consider the system problem of maximizing the total utility of clients, where the utilities are determined by their long-term average rates of being served within their delay constraints. We also allow for the additional fairness requirement that each client may require a certain minimum service rate. This overall model can be applied to a wide range of applications, including delay-constrained networks, mobile cellular networks, and dynamic spectrum allocation. We address this problem through convex programming. We propose an on-line scheduling policy and prove that it is utility-optimal. Surprisingly, this policy does not need to know the probability distribution of system states. We also design an auction mechanism where clients are scheduled and charged according to their bids. We prove that the auction mechanism restricts any selfish client from improving its utility by faking its utility function. We also show that the auction mechanism schedules clients in the same way as that done by the on-line scheduling policy. Thus, the auction mechanism is both truthful and utility-optimal. Finally, we design specific algorithms that implement the auction mechanism for a variety of applications.