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Understanding the capacity region of the greedy maximal scheduling algorithm in multihop wireless networks
 Proc. of IEEE INFOCOM
, 2008
"... Abstract—In this paper, we characterize the performance of an important class of scheduling schemes, called Greedy Maximal Scheduling (GMS), for multihop wireless networks. While a lower bound on the throughput performance of GMS is relatively wellknown in the simple nodeexclusive interference mo ..."
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Cited by 125 (9 self)
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Abstract—In this paper, we characterize the performance of an important class of scheduling schemes, called Greedy Maximal Scheduling (GMS), for multihop wireless networks. While a lower bound on the throughput performance of GMS is relatively wellknown in the simple nodeexclusive interference model, it has not been thoroughly explored in the more general Khop interference model. Moreover, empirical observations suggest that the known bounds are quite loose, and that the performance of GMS is often close to optimal. In this paper, we provide a number of new analytic results characterizing the performance limits of GMS. We first provide an equivalent characterization of the efficiency ratio of GMS through a topological property called the localpooling factor of the network graph. We then develop an iterative procedure to estimate the localpooling factor under a large class of network topologies and interference models. We use these results to study the worstcase efficiency ratio of GMS on two classes of network topologies. First, we show how these results can be applied to tree networks to prove that GMS achieves the full capacity region in tree networks under theKhop interference model. Second, we show that the worstcase efficiency ratio of GMS in geometric network graphs is between 1 6
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.
Performance of Random Access Scheduling Schemes in Multihop Wireless Networks
"... The scheduling problem in multihop wireless networks has been extensively investigated. Although throughput optimal scheduling solutions have been developed in the literature, they are unsuitable for multihop wireless systems because they are usually centralized and have very high complexity. In ..."
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Cited by 74 (7 self)
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The scheduling problem in multihop wireless networks has been extensively investigated. Although throughput optimal scheduling solutions have been developed in the literature, they are unsuitable for multihop wireless systems because they are usually centralized and have very high complexity. In this paper, we develop a randomaccess based scheduling scheme that utilizes local information. The important features of this scheme include constanttime complexity, distributed operations, and a provable performance guarantee. Analytical results show that it guarantees a larger fraction of the optimal throughput performance than the stateoftheart. Through simulations with both singlehop and multihop traffics, we observe that the scheme provides high throughput, close to that of a wellknown highlyefficient centralized greedy solution called the Greedy Maximal Scheduler.
On Combining ShortestPath and BackPressure Routing Over Multihop Wireless Networks
, 2008
"... Abstract—Backpressure based algorithms based on the algorithm by Tassiulas and Ephremides have recently received much attention for jointly routing and scheduling over multihop wireless networks. However a significant weakness of this approach has been in routing, because the traditional backpress ..."
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Cited by 65 (5 self)
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Abstract—Backpressure based algorithms based on the algorithm by Tassiulas and Ephremides have recently received much attention for jointly routing and scheduling over multihop wireless networks. However a significant weakness of this approach has been in routing, because the traditional backpressure algorithm explores and exploits all feasible paths between each source and destination. While this extensive exploration is essential in order to maintain stability when the network is heavily loaded, under light or moderate loads, packets may be sent over unnecessarily long routes and the algorithm could be very inefficient in terms of endtoend delay and routing convergence times. This paper proposes new routing/scheduling backpressure algorithms that not only guarantees network stability (throughput optimality), but also adaptively selects a set of optimal routes based on shortestpath information in order to minimize average pathlengths between each source and destination pair. Our results indicate that under the traditional backpressure algorithm, the endtoend packet delay first decreases and then increases as a function of the network load (arrival rate). This surprising lowload behavior is explained due to the fact that the traditional backpressure algorithm exploits all paths (including very long ones) even when the traffic load is light. On the otherhand, the proposed algorithm adaptively selects a set of routes according to the traffic load so that long paths are used only when necessary, thus resulting in much smaller endtoend packet delays as compared to the traditional backpressure algorithm. I.
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.
Cell Association and Interference Coordination in Heterogeneous LTEA Cellular Networks
"... Abstract—Embedding pico/femto basestations and relay nodes in a macrocellular network is a promising method for achieving substantial gains in coverage and capacity compared to macroonly networks. These new types of basestations can operate on the same wireless channel as the macrocellular netwo ..."
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Cited by 45 (0 self)
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Abstract—Embedding pico/femto basestations and relay nodes in a macrocellular network is a promising method for achieving substantial gains in coverage and capacity compared to macroonly networks. These new types of basestations can operate on the same wireless channel as the macrocellular network, providing higher spatial reuse via cell splitting. However, these basestations are deployed in an unplanned manner, can have very different transmit powers, and may not have traffic aggregation among many users. This could potentially result in much higher interference magnitude and variability. Hence, such deployments require the use of innovative cell association and intercell interference coordination techniques in order to realize the promised capacity and coverage gains. In this paper, we describe new paradigms for design and operation of such heterogeneous cellular networks. Specifically, we focus on cell splitting, range expansion, semistatic resource negotiation on thirdparty backhaul connections, and fast dynamic interference management for QoS via overtheair signaling. Notably, our methodologies and algorithms are simple, lightweight, and incur extremely low overhead. Numerical studies show that they provide large gains over currently used methods for cellular networks. Index Terms—Intercell interference management, femtocells I.
Lowcomplexity and distributed energy minimization in multihop wireless networks
 Purdue University, Tech. Rep., 2006, available on http://web.ics.purdue.edu/ ∼ llin/paper/ tech06.pdf
, 2007
"... Abstract — In this work, we study the problem of minimizing the total power consumption in a multihop wireless network subject to a given offered load. It is wellknown that the total power consumption of multihop wireless networks can be substantially reduced by jointly optimizing power control, ..."
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Cited by 20 (2 self)
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Abstract — In this work, we study the problem of minimizing the total power consumption in a multihop wireless network subject to a given offered load. It is wellknown that the total power consumption of multihop wireless networks can be substantially reduced by jointly optimizing power control, link scheduling, and routing. However, the known optimal crosslayer solution to this problem is centralized, and with high computational complexity. In this paper, we develop a lowcomplexity and distributed algorithm that is provably powerefficient. In particular, under the node exclusive interference model, we can show that the total power consumption of our algorithm is at most twice as large as the power consumption of the optimal (but centralized and complex) algorithm. Our algorithm is not only the first such distributed solution with provable performance bound, but its powerefficiency ratio is also tighter than that of another suboptimal centralized algorithm in the literature.
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.
On Throughput Optimality with Delayed NetworkState Information
, 2008
"... We study the problem of routing/scheduling in a wireless network with partial/delayed Network (channel and queue) State Information (NSI). We consider two cases: (i) centralized routing/scheduling, where a central controller obtains heterogeneous delayed information from each of the nodes (thus, the ..."
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Cited by 17 (2 self)
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We study the problem of routing/scheduling in a wireless network with partial/delayed Network (channel and queue) State Information (NSI). We consider two cases: (i) centralized routing/scheduling, where a central controller obtains heterogeneous delayed information from each of the nodes (thus, the controller has NSI with different delays from different nodes), and makes the routing/scheduling decisions; (ii) decentralized routing/scheduling, where each node makes a decision based on its current channel and queue states along with homogeneous delayed NSI from other nodes. For each of the cases (with additional flow restrictions for the decentralized routing/scheduling case), we first characterize the optimal network throughput regions under the above described NSI models and show that the throughput regions shrinks with the increase of delay. Further, we propose channel and queue length based routing/scheduling algorithms that achieve the above throughput regions.
Delay Analysis for Wireless Networks with Single Hop Traffic and General Interference Constraints
"... We consider a class of wireless networks with general interference constraints on the set of links that can be served simultaneously at any given time. We restrict the traffic to be singlehop, but allow for simultaneous transmissions as long as they satisfy the underlying interference constraints. ..."
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Cited by 15 (2 self)
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We consider a class of wireless networks with general interference constraints on the set of links that can be served simultaneously at any given time. We restrict the traffic to be singlehop, but allow for simultaneous transmissions as long as they satisfy the underlying interference constraints. We begin by proving a lower bound on the delay performance of any scheduling scheme for this system. We then analyze a large class of throughput optimal policies which have been studied extensively in the literature. The delay analysis of these systems has been limited to asymptotic behavior in the heavy traffic regime and order results. We obtain a tighter upper bound on the delay performance for these systems. We use the insights gained by the upper and lower bound analysis to develop an estimate for the expected delay of wireless networks with mutually independent arrival streams operating under the wellknown Maximum Weighted Matching (MWM) scheduling policy. We show via simulations that the delay performance of the MWM policy is often close to the lower bound, which means that it is not only throughput optimal, but also provides excellent delay performance.