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254
Fairness and optimal stochastic control for heterogeneous networks
 Proc. IEEE INFOCOM, March 2005. TRANSACTIONS ON NETWORKING, VOL
, 2008
"... Abstract — 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 capaci ..."
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Cited by 266 (63 self)
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Abstract — 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 control, routing, and resource allocation, and allows each user to make decisions independent of the actions of others. The combined strategy is shown to yield data rates that are arbitrarily close to the optimal operating point achieved when all network controllers are coordinated and have perfect knowledge of future events. The cost of approaching this fair operating point is an endtoend delay increase for data that is served by the network.
A tutorial on crosslayer optimization in wireless networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 2006
"... This tutorial paper overviews recent developments in optimization based approaches for resource allocation problems in wireless systems. We begin by overviewing important results in the area of opportunistic (channelaware) scheduling for cellular (singlehop) networks, where easily implementable my ..."
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Cited by 248 (29 self)
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This tutorial paper overviews recent developments in optimization based approaches for resource allocation problems in wireless systems. We begin by overviewing important results in the area of opportunistic (channelaware) scheduling for cellular (singlehop) networks, where easily implementable myopic policies are shown to optimize system performance. We then describe key lessons learned and the main obstacles in extending the work to general resource allocation problems for multihop wireless networks. Towards this end, we show that a cleanslate optimization based approach to the multihop resource allocation problem naturally results in a “loosely coupled” crosslayer solution. That is, the algorithms obtained map to different layers (transport, network, and MAC/PHY) of the protocol stack are coupled through a limited amount of information being passed back and forth. It turns out that the optimal scheduling component at the MAC layer is very complex and thus needs simpler (potentially imperfect) distributed solutions. We demonstrate how to use imperfect scheduling in the crosslayer framework and describe recently developed distributed algorithms along these lines. We conclude by describing a set of open research problems.
Maximizing Queueing Network Utility Subject to Stability: Greedy Primaldual algorithm
 Queueing Systems
, 2005
"... We study a model of controlled queueing network, which operates and makes control decisions in discrete time. An underlying random network mode determines the set of available controls in each time slot. Each control decision \produces " a certain vector of \commodities"; it also has assoc ..."
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Cited by 204 (9 self)
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We study a model of controlled queueing network, which operates and makes control decisions in discrete time. An underlying random network mode determines the set of available controls in each time slot. Each control decision \produces " a certain vector of \commodities"; it also has associated \traditional " queueing control eect, i.e., it determines traÆc (customer) arrival rates, service rates at the nodes, and random routing of processed customers among the nodes. The problem is to nd a dynamic control strategy which maximizes a concave utility function H(X), where X is the average value of commodity vector, subject to the constraint that network queues remain stable. We introduce a dynamic control algorithm, which we call Greedy PrimalDual (GPD) algorithm, and prove its asymptotic optimality. We show that our network model and GPD algorithm accommodate a wide range of applications. As one example, we consider the problem of congestion control of networks where both traÆc sources and network processing nodes may be randomly timevarying and interdependent. We also discuss a variety of resource allocation problems in wireless networks, which in particular involve average power consumption constraints and/or optimization, as well as traÆc rate constraints.
Energy optimal control for time varying wireless networks
 IEEE Trans. Inform. Theory
, 2006
"... Abstract — We develop a dynamic control strategy for minimizing energy expenditure in a time varying wireless network with adaptive transmission rates. The algorithm operates without knowledge of traffic rates or channel statistics, and yields average power that is arbitrarily close to the minimum p ..."
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Cited by 184 (50 self)
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Abstract — We develop a dynamic control strategy for minimizing energy expenditure in a time varying wireless network with adaptive transmission rates. The algorithm operates without knowledge of traffic rates or channel statistics, and yields average power that is arbitrarily close to the minimum possible value achieved by an algorithm optimized with complete knowledge of future events. Proximity to this optimal solution is shown to be inversely proportional to network delay. We then present a similar algorithm that solves the related problem of maximizing network throughput subject to peak and average power constraints. The techniques used in this paper are novel and establish a foundation for stochastic network optimization.
A framework for opportunistic scheduling in wireless networks,”
 Computer Networks,
, 2003
"... AbstractScheduling has been extensively studied in various disciplines in operations research and wireline networking. However, the unique characteristics of wireless communication systems namely, timingvarying channel conditions and multiuser diversity means that new scheduling solutions need ..."
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Cited by 167 (8 self)
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AbstractScheduling has been extensively studied in various disciplines in operations research and wireline networking. However, the unique characteristics of wireless communication systems namely, timingvarying channel conditions and multiuser diversity means that new scheduling solutions need to be developed that are specifically tailored for this environment. In this paper, we summarize various opportunistic scheduling schemes that exploit the timevarying nature of the radio environment to improve the spectrum efficiency while maintaining a certain level of satisfaction for each user. We also discuss the advantages and costs associated with opportunistic scheduling, and identify possible future research directions.
Opportunistic Fair Scheduling over Multiple Wireless Channels
, 2003
"... Emerging spread spectrum highspeed data networks utilize multiple channels via orthogonal codes or frequencyhopping patterns such that multiple users can transmit concurrently. In this paper, we develop a framework for opportunistic scheduling over multiple wireless channels. With a realistic chan ..."
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Cited by 111 (4 self)
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Emerging spread spectrum highspeed data networks utilize multiple channels via orthogonal codes or frequencyhopping patterns such that multiple users can transmit concurrently. In this paper, we develop a framework for opportunistic scheduling over multiple wireless channels. With a realistic channel model, any subset of users can be selected for data transmission at any time, albeit with different throughputs and system resource requirements. We first transform selection of the best users and rates from a complex general optimization problem into a decoupled and tractable formulation: a multiuser scheduling problem that maximizes total system throughput and a controlupdate problem that ensures longterm deterministic or probabilistic fairness constraints. We then design and evaluate practical schedulers that approximate these objectives.
A CrossLayer Scheduling Algorithm With QoS Support in Wireless Networks
 IEEE Transactions On Vehicular Technology
, 2006
"... Abstract—Scheduling plays an important role in providing quality of service (QoS) support to multimedia communications in various kinds of wireless networks, including cellular networks, mobile ad hoc networks, and wireless sensor networks. The authors propose a scheduling algorithm at the medium ac ..."
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Cited by 64 (1 self)
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Abstract—Scheduling plays an important role in providing quality of service (QoS) support to multimedia communications in various kinds of wireless networks, including cellular networks, mobile ad hoc networks, and wireless sensor networks. The authors propose a scheduling algorithm at the medium access control (MAC) layer for multiple connections with diverse QoS requirements, where each connection employs adaptive modulation and coding (AMC) scheme at the physical (PHY) layer over wireless fading channels. Each connection is assigned a priority, which is updated dynamically based on its channel and service status; the connection with the highest priority is scheduled each time. The authors ’ scheduler provides diverse QoS guarantees, uses the wireless bandwidth efficiently, and enjoys flexibility, scalability, and low implementation complexity. Its performance is evaluated via simulations. Index Terms—Adaptive modulation and coding (AMC), crosslayer design, IEEE 802.16, quality of service (QoS), scheduling algorithm, wireless networks, Worldwide Interoperability for Microwave Access (WiMAX). I.
Optimal energy and delay tradeoffs for multiuser wireless downlinks
 Proc. IEEE INFOCOM
, 2006
"... Abstract — We consider the fundamental delay tradeoffs for minimizing energy expenditure in a multiuser wireless downlink with randomly varying channels. First, we extend the BerryGallager bound to a multiuser context, demonstrating that any algorithm that yields average power within O(1/V) of th ..."
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Cited by 64 (17 self)
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Abstract — We consider the fundamental delay tradeoffs for minimizing energy expenditure in a multiuser wireless downlink with randomly varying channels. First, we extend the BerryGallager bound to a multiuser context, demonstrating that any algorithm that yields average power within O(1/V) of the minimum power required for network stability must also have an average queueing delay greater than or equal to Ω ( √ V). We then develop a class of algorithms, parameterized by V, that come within a logarithmic factor of achieving this fundamental tradeoff. The algorithms overcome an exponential state space explosion, and can be implemented in real time without apriori knowledge of traffic rates or channel statistics. Further, we discover a “superfast ” scheduling mode that beats the BerryGallager bound in the exceptional case when power functions are piecewise linear. Index Terms — queueing analysis, stability, optimization, stochastic control, asymptotic tradeoffs
Downlink scheduling and resource allocation for OFDM systems
 IN CISS
, 2006
"... Abstract—We consider scheduling and resource allocation for the downlink of a cellular OFDM system, with various practical considerations including integer carrier allocations, different subchannelization schemes, a maximum SNR constraint per tone, and “selfnoise ” due to channel estimation errors ..."
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Cited by 60 (14 self)
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Abstract—We consider scheduling and resource allocation for the downlink of a cellular OFDM system, with various practical considerations including integer carrier allocations, different subchannelization schemes, a maximum SNR constraint per tone, and “selfnoise ” due to channel estimation errors and phase noise. During each timeslot a subset of users must be scheduled for transmission, and the available tones and transmission power must be allocated among the selected users. Employing a gradientbased scheduling scheme presented in earlier papers reduces this to an optimization problem to be solved in each timeslot. Using dual decomposition techniques, we give an optimal algorithm for this problem when multiple users can timeshare each carrier. We then give several low complexity heuristics that enforce an integer constraint on the carrier allocation. Simulations show that the algorithms presented all achieve similar performance under a wide range of scenarios, and that the performance gap between the optimal and suboptimal algorithms widens when per user SNR constraints or channel estimation errors are considered. I.
Optimal Backpressure Routing for Wireless Networks with MultiReceiver Diversity
, 2006
"... We consider the problem of optimal scheduling and routing in an adhoc wireless network with multiple traffic streams and time varying channel reliability. Each packet transmission can be overheard by a subset of receiver nodes, with a transmission success probability that may vary from receiver t ..."
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Cited by 60 (8 self)
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We consider the problem of optimal scheduling and routing in an adhoc wireless network with multiple traffic streams and time varying channel reliability. Each packet transmission can be overheard by a subset of receiver nodes, with a transmission success probability that may vary from receiver to receiver and may also vary with time. We develop a simple backpressure routing algorithm that maximizes network throughput and expends an average power that can be pushed arbitrarily close to the minimum average power required for network stability, with a corresponding tradeoff in network delay. The algorithm can be implemented in a distributed manner using only local link error probability information, and supports a “blind transmission” mode (where error probabilities are not required) in special cases when the power metric is neglected and when there is only a single destination for all traffic streams.