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We consider optimal control for general networks with both wireless and wireline components and time varying channels. A dynamic strategy is developed to support all traffic whenever possible, and to make optimally fair decisions about which data to serve when inputs exceed network capacity. The strategy is decoupled into separate algorithms for flow(More)
—We consider optimizing average queueing delay and average power consumption in a nonpreemptive multi-class M/G/1 queue with dynamic power control that affects instantaneous service rates. Four problems are studied: (1) satisfying per-class average delay constraints; (2) minimizing a separable convex function of average delays subject to per-class delay(More)
— We investigate the combination of distributed geographic routing with transmission power control for energy efficient delivery of information in multihop wireless networks. Using realistic models for wireless channel fading as well as radio modulation and encoding, we first show that the optimal power control strategy over a given link should set the(More)
—We study throughput utility maximization in a multiuser network with partially observable Markovian channels. Here, instantaneous channel states are unavailable and all controls are based on partial channel information provided by ACK/NACK feedback from past transmissions. Equivalently, we formulate a restless multi-armed bandit problem in which we seek to(More)
— We consider a wireless base station serving L users through L time-varying channels. It is well known that opportunistic scheduling algorithms with full channel state information (CSI) can stabilize the system and achieve the full capacity region. However, opportunistic scheduling algorithms with full CSI may not be energy efficient when the cost of(More)
—We study the fundamental network capacity of a multiuser wireless downlink under two assumptions: (1) Channels are not explicitly measured and thus instantaneous states are unknown, (2) Channels are modeled as ON/OFF Markov chains. This is an important network model to explore because channel probing may be costly or infeasible in some contexts. In this(More)
—We study two convex optimization problems in a multi-class M/G/1 queue with adjustable service rates: minimizing convex functions of the average delay vector, and minimizing average service cost, both subject to per-class delay constraints. Using virtual queue techniques, we solve the two problems with variants of dynamic cµ rules. These algorithms(More)
—We consider the problem of transmitting multicast flows with hard deadlines over unreliable wireless channels. Every user in the network subscribes to several multicast flows, and requires a minimum throughput for each subscribed flow to meet the QoS constraints. The network controller schedules the transmissions of multicast traffic based on the instant(More)