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51
Dynamic Power Allocation and Routing for Time Varying Wireless Networks
 IEEE Journal on Selected Areas in Communications
, 2003
"... We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be tran ..."
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Cited by 210 (48 self)
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We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be transmitted through the network to their destinations. We establish the capacity region of all rate matrices (# ij ) that the system can stably supportwhere (# ij ) represents the rate of traffic originating at node i and destined for node j. A joint routing and power allocation policy is developed which stabilizes the system and provides bounded average delay guarantees whenever the input rates are within this capacity region. Such performance holds for general arrival and channel state processes, even if these processes are unknown to the network controller. We then apply this control algorithm to an adhoc wireless network where channel variations are due to user mobility, and compare its performance with the GrossglauserTse relay model developed in [13].
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 149 (27 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.
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 89 (30 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.
Optimal Power Control, Scheduling and Routing in UWB Networks
"... UltraWide Band (UWB) is an emerging wireless physical layer technology that uses a very large bandwidth. We are interested in finding the design objectives of the medium access (MAC, namely, power control and scheduling) and routing protocols of a multihop, besteffort, UWB network. Our objective ..."
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Cited by 61 (5 self)
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UltraWide Band (UWB) is an emerging wireless physical layer technology that uses a very large bandwidth. We are interested in finding the design objectives of the medium access (MAC, namely, power control and scheduling) and routing protocols of a multihop, besteffort, UWB network. Our objective is to maximize flow rates (more precisely, logutility of flow rates) given node power constraints. The specificity of UWB is expressed by the linear dependence between rate and signaltonoise ratio at the receiver. It is known that, in wireless networks, different routing strategies can imply differences in MAC protocol design. Hence we search for the jointly optimal routing, scheduling and power control.
Rate performance objectives of multihop wireless networks
 IEEE TRANS. MOB. COMPUT
, 2004
"... We consider the question of what performance metric to maximize when designing ad hoc wireless network protocols such as routing or MAC. We focus on maximizing rates under batterylifetime and power constraints. Commonly used metrics are total capacity (in the case of cellular networks) and transpo ..."
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Cited by 54 (1 self)
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We consider the question of what performance metric to maximize when designing ad hoc wireless network protocols such as routing or MAC. We focus on maximizing rates under batterylifetime and power constraints. Commonly used metrics are total capacity (in the case of cellular networks) and transport capacity (in the case of ad hoc networks). However, it is known in traditional wired networking that maximizing total capacity conflicts with fairness, and this is why fairnessoriented rate allocations, such as maxmin fairness, are often used. We review this issue for wireless ad hoc networks. Indeed, the mathematical model for wireless networks has a specificity that makes some of the findings different. It has been reported in the literature on Ultra Wide Band that gross unfairness occurs when maximizing total capacity or transport capacity, and we confirm by a theoretical analysis that this is a fundamental shortcoming of these metrics in wireless ad hoc networks, as it is for wired networks. The story is different for maxmin fairness. Although it is perfectly viable for a wired network, it is much less so in our setting. We show that, in the limit of long battery lifetimes, the maxmin allocation of rates always leads to strictly equal rates, regardless of the MAC layer, network topology, channel variations, or choice of routes and power constraints. This is due to the “solidarity” property of the set of feasible rates. This results in all flows receiving the rate of the worst flow, and leads to severe inefficiency. We show numerically that the problem persists when batterylifetime constraints are finite. This generalizes the observation reported in the literature that, in heterogeneous settings, 802.11 allocates the worst rate to all stations, and shows that this is inherent to any protocol that implements maxmin fairness. Utility fairness is an alternative to maxmin fairness, which approximates rate allocation performed by TCP in the Internet. We analyze by numerical
To Layer or Not To Layer: Balancing Transport and Physical Layers in Wireless Multihop Networks
, 2004
"... In a wireless ad hoc network with multihop transmissions and interferencelimited link rates, can we balance power control in the physical layer and congestion control in the transport layer to enhance the overall network performance, while maintaining the stability, robustness, and architectural mo ..."
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Cited by 48 (1 self)
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In a wireless ad hoc network with multihop transmissions and interferencelimited link rates, can we balance power control in the physical layer and congestion control in the transport layer to enhance the overall network performance, while maintaining the stability, robustness, and architectural modularity of the network? We present a distributive power control algorithm that couples with the original TCP protocols to increase the endtoend throughput and energy efficiency of the network. Under the rigorous framework of nonlinearly constrained optimization, we prove the convergence of this coupled system to the global optimum of joint power control and congestion control, for both synchronized and asynchronous implementations. The rate of convergence is geometric and a desirable modularity between the transport and physical layers is maintained. In particular, when the congestion control mechanism is TCP Vegas, that a simple utilization in the physical layer of the router buffer occupancy information suffices to achieve the joint optimum of this cross layer design. Both analytic results and simulations illustrate other desirable properties of the proposed algorithm, including robustness to channel outage and to path loss estimation errors, and flexibility in tradingoff performance optimality for implementation simplicity.
Beyond VCG: Frugality of truthful mechanisms
 In Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
, 2005
"... We study truthful mechanisms for auctions in which the auctioneer is trying to hire a team of agents to perform a complex task, and paying them for their work. As common in the field of mechanism design, we assume that the agents are selfish and will act in such a way as to maximize their profit, wh ..."
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Cited by 44 (3 self)
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We study truthful mechanisms for auctions in which the auctioneer is trying to hire a team of agents to perform a complex task, and paying them for their work. As common in the field of mechanism design, we assume that the agents are selfish and will act in such a way as to maximize their profit, which in particular may include misrepresenting their true incurred cost. Our first contribution is a new and natural definition of the frugality ratio of a mechanism, measuring the amount by which a mechanism “overpays”, and extending previous definitions to all monopolyfree set systems. After reexamining several known results in light of this new definition, we proceed to study in detail shortest path auctions and “routofk sets ” auctions. We show that when individual set systems (e.g., graphs) are considered instead of worst cases over all instances, these problems exhibit a rich structure, and the performance of mechanisms may be vastly different. In particular, we show that the wellknown VCG mechanism may be far from optimal in these settings, and we propose and analyze a mechanism that is always within a constant factor of optimal. 1
Power control by geometric programming
 IEEE Trans. on Wireless Commun
, 2005
"... Abstract — In wireless cellular or ad hoc networks where Quality of Service (QoS) is interferencelimited, a variety of power control problems can be formulated as nonlinear optimization with a systemwide objective, e.g., maximizing the total system throughput or the worst user throughput, subject ..."
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Cited by 40 (5 self)
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Abstract — In wireless cellular or ad hoc networks where Quality of Service (QoS) is interferencelimited, a variety of power control problems can be formulated as nonlinear optimization with a systemwide objective, e.g., maximizing the total system throughput or the worst user throughput, subject to QoS constraints from individual users, e.g., on data rate, delay, and outage probability. We show that in the high SignaltoInterference Ratios (SIR) regime, these nonlinear and apparently difficult, nonconvex optimization problems can be transformed into convex optimization problems in the form of geometric programming; hence they can be very efficiently solved for global optimality even with a large number of users. In the medium to low SIR regime, some of these constrained nonlinear optimization of power control cannot be turned into tractable convex formulations, but a heuristic can be used to compute in most cases the optimal solution by solving a series of geometric programs through the approach of successive convex approximation. While efficient and robust algorithms have been extensively studied for centralized solutions of geometric programs, distributed algorithms have not been explored before. We present a systematic method of distributed algorithms for power control that is geometricprogrammingbased. These techniques for power control, together with their implications to admission control and pricing in wireless networks, are illustrated through several numerical examples. Index Terms — Convex optimization, CDMA power control, Distributed algorithms. I.
Optimal resource allocation in wireless ad hoc networks: A pricebased approach
 IEEE Transactions on Mobile Computing
, 2006
"... The sharedmedium multihop nature of wireless ad hoc networks poses fundamental challenges to the design of effective resource allocation algorithms that are optimal with respect to resource utilization and fair across different network flows. None of the existing resource allocation algorithms in ..."
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Cited by 36 (4 self)
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The sharedmedium multihop nature of wireless ad hoc networks poses fundamental challenges to the design of effective resource allocation algorithms that are optimal with respect to resource utilization and fair across different network flows. None of the existing resource allocation algorithms in wireless ad hoc networks have realistically considered endtoend flows spanning multiple hops. Moreover, strategies proposed in wireline networks are not applicable in the context of wireless ad hoc networks, due to their unique characteristics of locationdependent contention. In this paper, we propose a new pricebased resource allocation framework in wireless ad hoc networks to achieve optimal resource utilization and fairness among competing endtoend flows. We build our pricing framework on the notion of maximal cliques in wireless ad hoc networks, as compared to individual links in traditional widearea wireline networks. Based on such a pricebased theoretical framework, we present a twotier iterative algorithm. Distributed across wireless nodes, the algorithm converges to a global network optimum with respect to resource allocations. We further improve the algorithm towards asynchronous network settings, and prove its convergence. Extensive simulations under a variety of network environments have been conducted to validate our theoretical claims. ming
A queueing analysis of maxmin fairness, proportional fairness and balanced fairness. Queueing Systems: Theory and Applications
, 2006
"... We compare the performance of three usual allocations, namely maxmin fairness, proportional fairness and balanced fairness, in a communication network whose resources are shared by a random number of data flows. The model consists of a network of processorsharing queues. The vector of service rates ..."
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Cited by 36 (7 self)
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We compare the performance of three usual allocations, namely maxmin fairness, proportional fairness and balanced fairness, in a communication network whose resources are shared by a random number of data flows. The model consists of a network of processorsharing queues. The vector of service rates, which is constrained by some compact, convex capacity set representing the network resources, is a function of the number of customers in each queue. This function determines the way network resources are allocated. We show that this model is representative of a rich class of wired and wireless networks. We give in this general framework the stability condition of maxmin fairness, proportional fairness and balanced fairness and compare their performance on a number of toy networks.