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71
Distributed link scheduling with constant overhead
 In Proceedings of ACM Sigmetrics
, 2007
"... This paper proposes a new class of simple, distributed algorithms for scheduling in wireless networks. The algorithms generate new schedules in a distributed manner via simple local changes to existing schedules. The class is parameterized by integers k ≥ 1. We show that algorithm k of our class ach ..."
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Cited by 101 (3 self)
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This paper proposes a new class of simple, distributed algorithms for scheduling in wireless networks. The algorithms generate new schedules in a distributed manner via simple local changes to existing schedules. The class is parameterized by integers k ≥ 1. We show that algorithm k of our class achieves k/(k +2) of the capacity region, for every k ≥ 1. The algorithms have small and constant worstcase overheads: in particular, algorithm k generates a new schedule using (a) time less than 4k + 2 roundtrip times between neighboring nodes in the network, and (b) at most three control transmissions by any given node, for any k. The control signals are explicitly specified, and face the same interference effects as normal data transmissions. Our class of distributed wireless scheduling algorithms are the first ones guaranteed to achieve any fixed fraction of the capacity region while using small and constant overheads that do not scale with network size. The parameter k explicitly captures the tradeoff between control overhead and scheduler throughput performance and provides a tuning knob protocol designers can use to harness this tradeoff in practice. 1.
Lowcomplexity distributed scheduling algorithms for wireless networks
 IEEE/ACM Trans. on Netw
"... Abstract — We consider the problem of distributed scheduling in wireless networks. We present two different algorithms whose performance is arbitrarily close to that of maximal schedules, but which require low complexity due to the fact that they do not necessarily attempt to find maximal schedules. ..."
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Cited by 81 (6 self)
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Abstract — We consider the problem of distributed scheduling in wireless networks. We present two different algorithms whose performance is arbitrarily close to that of maximal schedules, but which require low complexity due to the fact that they do not necessarily attempt to find maximal schedules. The first algorithm requires each link to collect local queuelength information in its neighborhood, and its complexity is independent of the size and topology of the network. The second algorithm is presented for the nodeexclusive interference model, does not require nodes to collect queuelength information even in their local neighborhoods, and its complexity depends only on the maximum node degree in the network. I.
Throughput of random access without message passing
 in CISS, 2008
"... Abstract—We develop distributed scheduling schemes that are based on simple random access algorithms and that have no message passing. In spite of their simplicity, these schemes are shown to provide high throughput performance: they achieve the same performance as that of some maximal scheduling al ..."
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Cited by 29 (8 self)
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Abstract—We develop distributed scheduling schemes that are based on simple random access algorithms and that have no message passing. In spite of their simplicity, these schemes are shown to provide high throughput performance: they achieve the same performance as that of some maximal scheduling algorithms, e.g. Maximum Size scheduling algorithms.
LongestQueueFirst scheduling under SINR interference model
 In Proc. ACM MobiHoc’10
, 2010
"... We investigate the performance of longestqueuefirst(LQF) scheduling(i.e., greedymaximal scheduling)for wireless networks under the SINR interference model. This interference model takes network geometry and the cumulative interference effect into account, which, therefore, capture the wireless int ..."
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Cited by 29 (5 self)
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We investigate the performance of longestqueuefirst(LQF) scheduling(i.e., greedymaximal scheduling)for wireless networks under the SINR interference model. This interference model takes network geometry and the cumulative interference effect into account, which, therefore, capture the wireless interference more precisely than binary interference models. By employing the ρlocal pooling technique, we show that LQF scheduling achieves zero throughput in the worst case. We then propose a novel techniquetolocalize interference which enables us to decentralize the LQF scheduling while preventing it from having vanishing throughput in all network topologies. We characterize the maximum throughputregionunderinterferencelocalization andpresent a distributed LQF scheduling algorithm. Finally, we present numerical results to illustrate the usefulness and to validate the theory developed in the paper.
Maximizing Utility via Random Access Without Message Passing
, 2008
"... It has been an intensively soughtafter goal to achieve high throughput and fairness in wireless scheduling through simple and distributed algorithms. Many recent papers on the topic have relied on various types of message passing among the nodes. The following question remains open: can scheduling ..."
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Cited by 27 (4 self)
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It has been an intensively soughtafter goal to achieve high throughput and fairness in wireless scheduling through simple and distributed algorithms. Many recent papers on the topic have relied on various types of message passing among the nodes. The following question remains open: can scheduling without any message passing guarantee throughputoptimality and fairness? Over the last year, it has been suggested in three papers [1]–[3] that random access without message passing may be designed and proved to be optimal in terms of throughput and utility. In this paper, we first extend the algorithm in [2] and provide a rigorous proof of utilityoptimality for random access without message passing for Poisson clock model. Then we turn to the more difficult discrete contention and backoff model with collisions, study its optimality properties, and control a tradeoff between longterm efficiency and shortterm fairness that emerges in this model.
Supplement for Joint Congestion Control and Distributed Scheduling for Throughput Guarantees in Wireless Networks
, 2009
"... We consider the problem of throughputoptimal crosslayer design of wireless networks. We propose a joint congestion control and scheduling algorithm that achieves a fraction 1/dI(G) of the capacity region, where dI(G) depends on certain structural properties of the underlying connectivity graph G o ..."
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Cited by 24 (3 self)
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We consider the problem of throughputoptimal crosslayer design of wireless networks. We propose a joint congestion control and scheduling algorithm that achieves a fraction 1/dI(G) of the capacity region, where dI(G) depends on certain structural properties of the underlying connectivity graph G of the wireless network, and also on the type of interference constraints. For a wide range of wireless networks, dI(G) can be upper bounded by a constant, independent of the number of nodes in the network. The scheduling element of our algorithm is the maximal scheduling policy. Although this scheduling policy has been considered in several previous works, the challenges underlying its practical implementation in a fully distributed manner while accounting for necessary message exchanges have not been addressed in the literature. In this paper, we propose two algorithms for the distributed implementation of the maximal scheduling policy accounting for message exchanges, and analytically show that they still can achieve the performance guarantee under the 1hop and 2hop interference models. We also evaluate the performance of our crosslayer solutions in more realistic network settings with imperfect synchronization under the signaltointerferenceplusnoise ratio (SINR) interference model, and compare with the standard layered approaches such as TCP over IEEE 802.11b DCF networks.
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 21 (8 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.
Optimal Control of Wireless Networks with Finite Buffers
"... This paper considers network control for wireless networks with finite buffers. We investigate the performance of joint flow control, routing, and scheduling algorithms which achieve high network utility and deterministically bounded backlogs inside the network. Our algorithms guarantee that buffers ..."
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Cited by 21 (2 self)
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This paper considers network control for wireless networks with finite buffers. We investigate the performance of joint flow control, routing, and scheduling algorithms which achieve high network utility and deterministically bounded backlogs inside the network. Our algorithms guarantee that buffers inside the network never overflow. We study the tradeoff between buffer size and network utility and show that if internal buffers have size (N − 1)/ɛ then a high fraction of the maximum utility can be achieved, where ɛ captures the loss in utility and N is the number of network nodes. The underlying scheduling/routing component of the considered control algorithms requires ingress queue length information (IQI) at all network nodes. However, we show that these algorithms can achieve the same utility performance with delayed ingress queue length information. Numerical results reveal that the considered algorithms achieve nearly optimal network utility with a significant reduction in queue backlog compared to the existing algorithm in the literature. Finally, we discuss extension of the algorithms to wireless networks with timevarying links.
Performance Limits of Greedy Maximal Matching in Multihop Wireless Networks
"... In this paper, we characterize the performance limits of an important class of scheduling schemes, called Greedy Maximal Matching (GMM), for multihop wireless networks. For simplicity, we focus on the wellestablished nodeexclusive interference model, although many of the stated results can be rea ..."
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Cited by 17 (1 self)
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In this paper, we characterize the performance limits of an important class of scheduling schemes, called Greedy Maximal Matching (GMM), for multihop wireless networks. For simplicity, we focus on the wellestablished nodeexclusive interference model, although many of the stated results can be readily extended to more general interference models. The study of the performance of GMM is intriguing because although a lower bound on its performance is well known, empirical observations suggest that this bound is quite loose, and that the performance of GMM is often close to optimal. In fact, recent results have shown that GMM achieves optimal performance under certain conditions. In this paper, we provide new analytic results that characterize the performance of GMM through the topological properties of the underlying graphs. To that end, we generalize a recently developed topological notion called the local pooling condition to a far weaker condition called the σlocal pooling. We then define the localpooling factor on a graph, as the supremum of all σ such that the graph satisfies σlocal pooling. We show that for a given graph, the efficiency ratio of GMM (i.e., the ratio of the throughput of GMM to that of the optimal) is equal to its localpooling factor. Further, we provide results on how to estimate the localpooling factor for arbitrary graphs and show that the efficiency ratio of GMM is no smaller than d ∗ /(2d ∗ −1) in a network topology of maximum nodedegree d ∗. We also identify specific network topologies for which the efficiency ratio of GMM is strictly less than 1. I.
Queue BackPressure Random Access in MultiHop Wireless Networks: Optimality and Stability
"... A model for wireless networks with random (slottedAlohatype) access and with multihop flow routes is considered. The goal is to devise distributed strategies for optimal utilitybased endtoend throughput allocation and queueing stability. A class of queue backpressure random access algorithms ..."
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Cited by 17 (5 self)
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A model for wireless networks with random (slottedAlohatype) access and with multihop flow routes is considered. The goal is to devise distributed strategies for optimal utilitybased endtoend throughput allocation and queueing stability. A class of queue backpressure random access algorithms (QBRA), in which actual queue lengths of the flows in each node’s close neighborhood are used to determine the nodes ’ channel access probabilities, is studied. This is in contrast to some previously proposed algorithms, which are purely optimizationbased and oblivious to actual queues. QBRA is also substantially different from the well studied “MaxWeight ” type scheduling algorithms, which also uses backpressure. For the model with infinite backlog at each flow source, it is shown that QBRA, combined with simple congestion control local to each source, leads to optimal endtoend throughput allocation, within the network saturation throughput region achievable by random access without endtoend message passing. This scheme is generalized to the case of additional, minimum flow rate constraints. For the model with stochastic exogenous arrivals, it is shown that QBRA ensures stability of the queues as long as nominal loads of the nodes are within the saturation throughput region. Simulation comparison of QBRA and the queue oblivious optimizationbased random access algorithms, shows that QBRA performs better in terms of endtoend delays.