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30
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 102 (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.
Improved bounds on the throughput efficiency of greedy maximal scheduling in wireless networks
 in Proc. ACM MOBIHOC’09
, 2009
"... Due to its low complexity, Greedy Maximal Scheduling (GMS), also known as Longest Queue First (LQF), has been studied extensively for wireless networks. However, GMS can result in degraded throughput performance in general wireless networks. In this paper, we prove that GMS achieves 100 % throughput ..."
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Cited by 45 (8 self)
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Due to its low complexity, Greedy Maximal Scheduling (GMS), also known as Longest Queue First (LQF), has been studied extensively for wireless networks. However, GMS can result in degraded throughput performance in general wireless networks. In this paper, we prove that GMS achieves 100 % throughput in all networks with eight nodes or less, under the twohop interference model. Further, we obtain performance bounds that improve upon previous results for larger networks up to a certain size. We also provide a simple proof to show that GMS can be implemented using only local neighborhood information in networks of any size.
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.
Stable scheduling policies for maximizing throughput in generalized constrained queueing systems
 IN PROCEEDINGS OF IEEE INFOCOM
, 2006
"... We consider a class of queueing networks referred to as “generalized constrained queueing networks” which form the basis of several different communication networks and information systems. These networks consist of a collection of queues such that only certain sets of queues can be concurrently ser ..."
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Cited by 24 (11 self)
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We consider a class of queueing networks referred to as “generalized constrained queueing networks” which form the basis of several different communication networks and information systems. These networks consist of a collection of queues such that only certain sets of queues can be concurrently served. Whenever a queue is served, the system receives a certain reward. Different rewards are obtained for serving different queues, and furthermore, the reward obtained for serving a queue depends on the set of concurrently served queues. We demonstrate that the dependence of the rewards on the schedules alter fundamental relations between performance metrics like throughput and stability. Specifically, maximizing the throughput is no longer equivalent to maximizing the stability region; we therefore need to maximize one subject to certain constraints on the other. Since stability is critical for bounding packet delays and buffer overflow, we focus on maximizing the throughput subject to stabilizing the system. We design provably optimal scheduling strategies that attain this goal by scheduling the queues for service based on the queue lengths and the rewards provided by different selections. The proposed scheduling strategies are however computationally complex. We subsequently develop techniques to reduce the complexity and yet attain the same throughput and stability region. We demonstrate that our framework is general enough to accommodate random rewards and random scheduling constraints.
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.
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.
Stochastic Network Utility Maximization A tribute to Kelly’s paper published in this journal a decade ago
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Opportunistic Routing with Congestion Diversity in Wireless Multihop Networks
 in Proceedings of the 29th IEEE International Conference on Computer Communication (INFOCOM). Piscataway
, 2010
"... AbstractThis paper considers the problem of routing packets across a multihop network consisting of multiple sources of traffic and wireless links with stochastic reliability while ensuring bounded expected delay. Each packet transmission can be overheard by a random subset of receiver nodes amon ..."
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Cited by 12 (2 self)
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AbstractThis paper considers the problem of routing packets across a multihop network consisting of multiple sources of traffic and wireless links with stochastic reliability while ensuring bounded expected delay. Each packet transmission can be overheard by a random subset of receiver nodes among which the next relay/router is selected opportunistically. The main challenge in the design of minimumdelay routing policies is balancing the tradeoff between routing the packets along the shortest paths to the destination and controlling the congestion and distributing traffic uniformly across the network. Simple opportunistic variants of shortest path routing may, under heavy traffic scenarios, result in severe congestion and unbounded delay. While the opportunistic variants of backpressure, which ensure a bounded expected delay, are known to exhibit extremely poor delay performance at low to medium traffic conditions. Combining important aspects of shortest path routing with those of backpressure routing, this paper provides an opportunistic routing policy with congestion diversity (ORCD). ORCD uses a measure of draining time to opportunistically identify and route packets along the paths with an expected low overall congestion. Using a novel Lyapunov function construction, ORCD is proved to ensure a bounded expected delay for all networks and under any admissible traffic (without any knowledge of traffic statistics). Furthermore, the expected delay encountered by the packets in the network under ORCD is compared against known existing routing policies via simulations and substantial improvements are observed. Finally, the paper proposes practical implementations and discusses criticality of various assumptions in the analysis.
Wireless scheduling algorithms with O(1) complexity for Mhop interference model
, 2007
"... Abstract—We develop a family of distributed wireless scheduling algorithms that requires only O(1) complexity for Mhop interference model, for any finite M. The recent technology advances and heterogeneity in wireless networks lead to various interference patterns. Thus, a scheduling algorithm gear ..."
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Cited by 10 (0 self)
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Abstract—We develop a family of distributed wireless scheduling algorithms that requires only O(1) complexity for Mhop interference model, for any finite M. The recent technology advances and heterogeneity in wireless networks lead to various interference patterns. Thus, a scheduling algorithm geared into a specific interference model (typically onehop or twohop in literature) may be limited in its applicability. In this paper, we tackle this problem, and develop a family of scheduling algorithms (which guarantees throughput and delay performance) for Mhop interference models. To achieve such a goal, we use the concept of vertex augmentation, and for a given M, the family of parameterized algorithms are proposed and the tradeoffs among throughput, complexity, and delay are studied.