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122
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 (30 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.
Distributed interference compensation for wireless networks
 IEEE Journal on Selected Areas in Communications
, 2006
"... Abstract—We consider a distributed power control scheme for wireless ad hoc networks, in which each user announces a price that reflects compensation paid by other users for their interference. We present an asynchronous distributed algorithm for updating power levels and prices. By relating this al ..."
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Cited by 168 (32 self)
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Abstract—We consider a distributed power control scheme for wireless ad hoc networks, in which each user announces a price that reflects compensation paid by other users for their interference. We present an asynchronous distributed algorithm for updating power levels and prices. By relating this algorithm to myopic best response updates in a fictitious game, we are able to characterize convergence using supermodular game theory. Extensions of this algorithm to a multichannel network are also presented, in which users can allocate their power across multiple frequency bands. Index Terms—Distributed algorithms, game theory, power control, pricing. I.
Stability and Performance Analysis of Networks Supporting Elastic Services
 IEEE/ACM Transactions on Networking
, 2001
"... AbstractWe consider the stability and performance of a model for networks supporting services that adapt their transmission to the available bandwidth. Not unlike real networks, in our model, connection arrivals are stochastic, each has a random amount of data to send, and the number of ongoing co ..."
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Cited by 120 (6 self)
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AbstractWe consider the stability and performance of a model for networks supporting services that adapt their transmission to the available bandwidth. Not unlike real networks, in our model, connection arrivals are stochastic, each has a random amount of data to send, and the number of ongoing connections in the system changes over time. Consequently, the bandwidth allocated to, or throughput achieved by, a given connection may change during its lifetime as feedback control mechanisms react to network loads. Ideally, if there were a fixed number of ongoing connections, such feedback mechanisms would reach an equilibrium bandwidth allocation typically characterized in terms of its &quot;fairness &quot; to users, e.g., maxmin or proportionally fair. In this paper we prove the stability of such networks when the offered load on each link does not exceed its capacity. We use simulation to investigate performance, in terms of average connection delays, for various fairness criteria. Finally, we pose an architectural problem in TCP/IPs decoupling of the transport and network layer from the point of view of guaranteeing connectionlevel stability, which we claim may explain congestion phenomena on the Internet. Index TermsABR service, bandwidth allocation, Lyapunov functions, performance analysis, proportional fairness, rate control, stability, TCP/IP, weighted maxmin fairness. F I.
A utilitybased powercontrol scheme in wireless cellular systems
 IEEE/ACM TRANS. ON NETWORKING
, 2003
"... Distributed powercontrol algorithms for systems with hard signaltointerference ratio (SIR) constraints may diverge when infeasibility arises. In this paper, we present a powercontrol framework called utilitybased power control (UBPC) by reformulating the problem using a softened SIR requirement ..."
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Cited by 102 (3 self)
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Distributed powercontrol algorithms for systems with hard signaltointerference ratio (SIR) constraints may diverge when infeasibility arises. In this paper, we present a powercontrol framework called utilitybased power control (UBPC) by reformulating the problem using a softened SIR requirement (utility) and adding a penalty on power consumption (cost). Under this framework, the goal is to maximize the net utility, defined as utility minus cost. Although UBPC is still noncooperative and distributed in nature, some degree of cooperation emerges: a user will automatically decrease its target SIR (and may even turn off transmission) when it senses that traffic congestion is building up. This framework enables us to improve system convergence and to satisfy heterogeneous service requirements (such as delay and bit error rate) for integrated networks with both voice users and data users. Fairness, adaptiveness, and a high degree of flexibility can be achieved by properly tuning parameters in UBPC.
A Unifying Passivity Framework for Network Flow Control
 IEEE Transactions on Automatic Control
, 2002
"... Network flow control regulates the traffic between sources and links based on congestion, and plays a critical role in ensuring satisfactory performance. In recent studies, global stability has been shown for several flow control schemes. By using a passivity approach, this paper presents a unifying ..."
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Cited by 79 (13 self)
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Network flow control regulates the traffic between sources and links based on congestion, and plays a critical role in ensuring satisfactory performance. In recent studies, global stability has been shown for several flow control schemes. By using a passivity approach, this paper presents a unifying framework which encompasses these stability results as special cases. In addition, the new approach significantly expands the current classes of stable flow controllers by augmenting the source and link update laws with passive dynamic systems. This generality offers the possibility of optimizing the controllers, for example, to improve robustness and performance with respect to time delay, unmodeled flows, and capacity variation.
NonConvex Optimization and Rate Control for MultiClass Services in the Internet
 IEEE/ACM Transactions on Networking
, 2005
"... In this paper, we investigate the problem of distributively allocating transmission data rates to users in the Internet. We allow users to have concave as well as sigmoidal utility functions as appropriate for different applications. In the literature, for simplicity, most works have dealt only with ..."
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Cited by 59 (4 self)
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In this paper, we investigate the problem of distributively allocating transmission data rates to users in the Internet. We allow users to have concave as well as sigmoidal utility functions as appropriate for different applications. In the literature, for simplicity, most works have dealt only with the concave utility function. However, we show that applying rate control algorithms developed for concave utility functions in a more realistic setting (with both concave and sigmoidal types of utility functions) could lead to instability and high network congestion. We show that a pricing based mechanism that solves the dual formulation can be developed based on the theory of subdifferentials with the property that the prices “selfregulate ” the users to access the resources based on the net utility. We discuss convergence issues and show that an algorithm can be developed that is efficient in the sense of achieving the global optimum when there are many users. I.
Utilityoptimal randomaccess control
 IEEE Trans. on Wireless Communications
, 2007
"... Abstract — This paper designs medium access control (MAC) protocols for wireless networks through the network utility maximization (NUM) framework. A networkwide utility maximization problem is formulated, using a collision/persistenceprobabilistic model and aligning selfish utility with total soci ..."
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Cited by 51 (10 self)
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Abstract — This paper designs medium access control (MAC) protocols for wireless networks through the network utility maximization (NUM) framework. A networkwide utility maximization problem is formulated, using a collision/persistenceprobabilistic model and aligning selfish utility with total social welfare. By adjusting the parameters in the utility objective functions of the NUM problem, we can also control the tradeoff between efficiency and fairness of radio resource allocation. We develop two distributed algorithms to solve the utilityoptimal randomaccess control problem, which lead to random access protocols that have slightly more message passing overhead than the current exponentialbackoff protocols, but significant potential for efficiency and fairness improvement. We provide readilyverifiable sufficient conditions under which convergence of the proposed algorithms to a global optimality of network utility can be guaranteed, and numerical experiments that illustrate the value of the NUM approach to the complexityperformance tradeoff in MAC design. Index Terms — Wireless network, medium access control (MAC), mathematical programming/optimization, network utility maximization, network control by pricing.
Linkstate routing with hopbyhop forwarding can achieve optimal traffic engineering
 In INFOCOM
, 2008
"... Abstract — Linkstate routing with hopbyhop forwarding is widely used in the Internet today. The current versions of these protocols, like OSPF, split traffic evenly over shortest paths based on link weights. However, optimizing the link weights for OSPF to the offered traffic is an NPhard proble ..."
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Cited by 43 (4 self)
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Abstract — Linkstate routing with hopbyhop forwarding is widely used in the Internet today. The current versions of these protocols, like OSPF, split traffic evenly over shortest paths based on link weights. However, optimizing the link weights for OSPF to the offered traffic is an NPhard problem, and even the best setting of the weights can deviate significantly from an optimal distribution of the traffic. In this paper, we propose a new linkstate routing protocol, PEFT, that splits traffic over multiple paths with an exponential penalty on longer paths. Unlike its predecessor, DEFT [1], our new protocol provably achieves optimal traffic engineering while retaining the simplicity of hopbyhop forwarding. A gain of 15 % in capacity utilization over OSPF is demonstrated using the Abilene topology and traffic traces. The new protocol also leads to significant reduction in the time needed to compute the best link weights. Both the protocol and the computational methods are developed in a new conceptual framework, called Network Entropy Maximization, where a specific notion of entropy is used to identify the traffic distributions that are not only optimal but also realizable by linkstate routing.
Approximation algorithms for budgeted learning problems
 In Proc. ACM Symp. on Theory of Computing
, 2007
"... We present the first approximation algorithms for a large class of budgeted learning problems. One classic example of the above is the budgeted multiarmed bandit problem. In this problem each arm of the bandit has an unknown reward distribution on which a prior is specified as input. The knowledge ..."
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Cited by 31 (8 self)
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We present the first approximation algorithms for a large class of budgeted learning problems. One classic example of the above is the budgeted multiarmed bandit problem. In this problem each arm of the bandit has an unknown reward distribution on which a prior is specified as input. The knowledge about the underlying distribution can be refined in the exploration phase by playing the arm and observing the rewards. However, there is a budget on the total number of plays allowed during exploration. After this exploration phase, the arm with the highest (posterior) expected reward is chosen for exploitation. The goal is to design the adaptive exploration phase subject to a budget constraint on the number of plays, in order to maximize the expected reward of the arm chosen for exploitation. While this problem is reasonably well understood in the infinite horizon setting or regret bounds, the budgeted version of the problem is NPHard. For this problem, and several generalizations, we provide approximate policies that achieve a reward within constant factor of the reward optimal policy. Our algorithms use a novel linear program rounding technique based on stochastic packing.