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23
Adaptive network coding and scheduling for maximizing througput in wireless networks
 In Proceedings of ACM Mobicom
, 2007
"... Recently, network coding emerged as a promising technology that can provide significant improvements in throughput and energy efficiency of wireless networks, even for unicast communication. Often, network coding schemes are designed as an autonomous layer, independent of the underlying Phy and ..."
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Cited by 64 (1 self)
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Recently, network coding emerged as a promising technology that can provide significant improvements in throughput and energy efficiency of wireless networks, even for unicast communication. Often, network coding schemes are designed as an autonomous layer, independent of the underlying Phy and MAC capabilities and algorithms. Consequently, these schemes are greedy, in the sense that all opportunities of broadcasting combinations of packets are exploited. We demonstrate that this greedy design principle may in fact reduce the network throughput. This begets the need for adaptive network coding schemes. We further show that designing appropriate MAC scheduling algorithms is critical for achieving the throughput gains expected from network coding. In this paper, we propose a general framework to develop optimal and adaptive joint network coding and scheduling schemes. Optimality is shown for various Phy and MAC constraints. We apply this framework to two different network coding architectures: COPE, a scheme recently proposed in [7], and XORSym, a new scheme we present here. XORSym is designed to achieve a lower implementation complexity than that of COPE, and yet to provide similar throughput gains.
Complexity in wireless scheduling: Impact and tradeoffs
 in Proceedings of ACM Mobihoc, Hong Kong
, 2008
"... It has been an important research topic since 1992 to maximize stability region in constrained queueing systems, which includes the study of scheduling over wireless ad hoc networks. In this paper, we propose a framework to study a wide range of existing and future scheduling algorithms and characte ..."
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Cited by 22 (9 self)
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It has been an important research topic since 1992 to maximize stability region in constrained queueing systems, which includes the study of scheduling over wireless ad hoc networks. In this paper, we propose a framework to study a wide range of existing and future scheduling algorithms and characterize the achieved tradeoffs in stability, delay, and complexity. These characterizations reveal interesting properties hidden in the study of any one or two dimensions in isolation. For example, decreasing complexity from exponential to polynomial, while keeping stability region the same, generally comes at the expense of exponential growth of delays. Investigating tradeoffs in the 3dimensional space allows a designer to fix one dimension and vary the other two jointly. For example, incentives for using scheduling algorithms with only partial throughputguarantee can be quantified with regards to delay and complexity. Tradeoff analysis is then extended to systems with congestion control through utility maximization for nonstabilizable arrival inputs, where the complexityutilitydelay tradeoff is shown to be different from the complexitystabilitydelay tradeoff. Finally, we analyze more practical models with bounded message size, and consider “effective throughput” which reflects resource occupied by control messages. We show that effective throughput may degrade significantly in certain scheduling algorithms, and suggest a mechanism to avoid this problem in light of the 3D tradeoff framework.
Stochastic Network Utility Maximization A tribute to Kelly’s paper published in this journal a decade ago
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On Stability Region and Delay Performance of LinearMemory Randomized Scheduling for TimeVarying Networks
"... Abstract—Throughput optimal scheduling policies in general require the solution of a complex and often NPhard optimization problem. Related literature has shown that in the context of timevarying channels, randomized scheduling policies can be employed to reduce the complexity of the optimization ..."
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Cited by 6 (3 self)
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Abstract—Throughput optimal scheduling policies in general require the solution of a complex and often NPhard optimization problem. Related literature has shown that in the context of timevarying channels, randomized scheduling policies can be employed to reduce the complexity of the optimization problem but at the expense of a memory requirement that is exponential in the number of data flows. In this paper, we consider a LinearMemory Randomized Scheduling Policy (LMRSP) that is based on a pickandcompare principle in a timevarying network with N onehop data flows. For general ergodic channel processes, we study the performance of LMRSP in terms of its stability region and average delay. Specifically, we show that LMRSP can stabilize a fraction of the capacity region. Our analysis characterizes this fraction as well as the average delay as a function of channel variations and the efficiency of LMRSP in choosing an appropriate schedule vector. Applying these results to a class of Markovian channels, we provide explicit results on the stability region and delay performance of LMRSP. I.
1 Dynamic Power Allocation for Throughput Utility Maximization in InterferenceLimited Networks
"... Abstract—We present an algorithm to dynamically allocate transmission power to maximize the throughpututility in an interferencelimited network under an instantaneous sum power constraint with timevarying channels. We consider the equivalent problem of maximum admission with queue stability const ..."
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Cited by 5 (1 self)
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Abstract—We present an algorithm to dynamically allocate transmission power to maximize the throughpututility in an interferencelimited network under an instantaneous sum power constraint with timevarying channels. We consider the equivalent problem of maximum admission with queue stability constraint through Lyapunov optimization. The resultant nonconvex minimization problem is solved by an online algorithm consisting of two components: first, successive convex approximations to randomly choose a local minimum, and second, a modified pickandcompare method for lowcomplexity convergence to a global minimum. We prove the optimality of this approach, derive its tradeoff between throughpututility and delay, and demonstrate its performance advantage against existing methods. I.
Channel and Multiuser Diversities in Wireless Systems: DelayEnergy Tradeoff
, 2008
"... We consider a communication system with multiaccess fading channel. Each user in the system requires certain rate guarantee. Our main contribution is to devise a scheduling scheme called “Opportunistic Superposition Coding” that satisfies the users ’ rate requirements. Using meanfield analysis, i ..."
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Cited by 4 (3 self)
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We consider a communication system with multiaccess fading channel. Each user in the system requires certain rate guarantee. Our main contribution is to devise a scheduling scheme called “Opportunistic Superposition Coding” that satisfies the users ’ rate requirements. Using meanfield analysis, i.e., when the number of users go to infinity, we analytically show that the energy required to guarantee the required user rate can be made as small as required at the cost of a higher delay (“delayenergy tradeoff”). We explicitly compute the delay under the proposed scheduling policy and discuss how delay differentiation can be achieved. We extend the results to multiband multiaccess channel. Finally, all the results can be generalized in a straightforward fashion to broadcast channel due to the AWGN multiaccessbroadcast duality.
Economy of Spectrum Access in Time Varying MultiChannel Networks
"... We consider a wireless network consisting of two classes of potentially mobile users: primary users and secondary users. Primary users license frequency channels and transmit in their respective bands as required. Secondary users resort to unlicensed access of channels that are not used by their pr ..."
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Cited by 3 (1 self)
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We consider a wireless network consisting of two classes of potentially mobile users: primary users and secondary users. Primary users license frequency channels and transmit in their respective bands as required. Secondary users resort to unlicensed access of channels that are not used by their primary users. Primaries impose access fees on the secondaries which depend on access durations and may be different for different primary channels and different available communication rates in the channels. The available rates to the secondaries change with time depending on the usage status of the primaries and the random access quality of channels. Secondary users seek to minimize their total access cost subject to stabilizing their queues whenever possible. Our first contribution is to present a dynamic link scheduling policy that attains this objective. The computation time of this policy, however, increases exponentially with the size of the network. We next present an approximate scheduling scheme based on graph partitioning that is distributed and attains arbitrary tradeoffs between aggregate access cost and computation times of the schedules, irrespective of the size of the network. Our performance guarantees hold for general arrival and primary usage statistics and multihop networks. Each secondary user is however primarily interested in minimizing the cost it incurs, rather than in minimizing the aggregate cost. Thus, it will schedule its transmissions so as to minimize the aggregate cost only if it perceives that the aggregate cost is shared among the users as per a fair cost sharing scheme. Using concepts from cooperative game theory, we develop a rational basis for sharing the aggregate cost amongst secondary sessions and present a cost sharing mechanism that conforms to the above basis.
Stochastic network utility maximisation  a tribute to Kelly’s paper published in this journal a decade ago
 EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS
, 2008
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Power optimal scheduling for guaranteed throughput in multiaccess fading channels
 in IEEE International Symposium on Information Theory (ISIT
, 2007
"... A power optimal scheduling algorithm that guarantees desired throughput and bounded delay to each user is developed for fading multiaccess multiband systems. The optimization is over the joint space of all rate allocation and coding strategies. The proposed scheduling assigns rates on each band ba ..."
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Cited by 3 (3 self)
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A power optimal scheduling algorithm that guarantees desired throughput and bounded delay to each user is developed for fading multiaccess multiband systems. The optimization is over the joint space of all rate allocation and coding strategies. The proposed scheduling assigns rates on each band based only on the current system state, and subsequently uses optimal multiuser signaling to achieve these rates. The scheduling is computationally simple, and hence scalable. Due to uplinkdownlink duality, all the results extend in straightforward fashion to the broadcast channels. Index Terms Power minimization, scheduling, stability, convex optimization, superposition encoding and
Spatial inefficiency of maxweight scheduling, Modeling and Optimization
 in Mobile, Ad Hoc and Wireless Networks (WiOpt), 2011 International Symposium on, IEEE, 2011
"... MaxWeight scheduling has gained enormous popularity as a powerful paradigm for achieving queue stability and maximum throughput in a wide variety of scenarios. The maximumstability guarantees however rely on the fundamental premise that the system consists of a fixed set of flows with stationary e ..."
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Cited by 2 (1 self)
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MaxWeight scheduling has gained enormous popularity as a powerful paradigm for achieving queue stability and maximum throughput in a wide variety of scenarios. The maximumstability guarantees however rely on the fundamental premise that the system consists of a fixed set of flows with stationary ergodic traffic processes. In the present paper we examine networks where the population of active flows varies over time, as flows eventually end while new flows occasionally start. We show that MaxWeight policies may fail to provide maximum stability due to persistent inefficient spatial reuse. The intuitive explanation is that these policies tend to serve flows with large backlogs, even when the resulting spatial reuse is not particularly efficient, and fail to exploit maximum spatial reuse patterns involving flows with smaller backlogs. These results indicate that instability of MaxWeight scheduling can occur due to spatial inefficiency in networks with fixed transmission rates, which is fundamentally different from the inability to fully exploit timevarying rates shown in prior work. We discuss how the potential instability effects can be countered by spatial traffic aggregation, and describe some of the associated challenges and performance tradeoffs. 1