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28
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
QCSMA: Queuelength based CSMA/CA algorithms for achieving maximum throughput and low delay in wireless networks
 IN IEEE INFOCOM
, 2010
"... Recently, it has been shown that CSMAtype random access algorithms can achieve the maximum possible throughput in wireless ad hoc networks. However, the delay performance of these algorithms can be quite bad. On the other hand, although some simple heuristics (such as distributed approximations of ..."
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Cited by 64 (6 self)
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Recently, it has been shown that CSMAtype random access algorithms can achieve the maximum possible throughput in wireless ad hoc networks. However, the delay performance of these algorithms can be quite bad. On the other hand, although some simple heuristics (such as distributed approximations of greedy maximal scheduling) can yield much better delay performance for a large set of arrival rates, they may only achieve a fraction of the capacity region in general. In this paper, we propose a discretetime version of the CSMAtype random access algorithm that allows us to incorporate simple heuristics which lead to very good delay performance while retaining the throughputoptimality property. Central to our results is a discretetime distributed randomized algorithm that generates data transmission schedules according to a productform distribution, a counterpart of similar results obtained earlier for continuoustime models under the perfect CSMA assumption where collisions can never occur. An appealing feature of this algorithm is that it explicitly takes collisions into account during the exchange of control packets.
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.
Distributed CSMA/CA algorithms for achieving maximum throughput in wireless networks
 in Proc. Inf. Theory Appl. Workshop
, 2009
"... Recently, it has been shown that CSMAtype random access algorithms can achieve the maximum throughput in wireless ad hoc networks. Central to these results is a distributed randomized algorithm which selects schedules according a productform distribution. The productform distribution is achieved ..."
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Cited by 35 (1 self)
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Recently, it has been shown that CSMAtype random access algorithms can achieve the maximum throughput in wireless ad hoc networks. Central to these results is a distributed randomized algorithm which selects schedules according a productform distribution. The productform distribution is achieved by considering a continuoustime Markov model of an idealized CSMA protocol under which collisions cannot occur. In this paper, we present an algorithm which achieves the same productform distribution in a discretetime setting where collision of data packets is avoided through the exchange of control messages (however, the control messages are allowed to collide as in the 802.11 suite of protocols). In our discretetime model, each time slot consists of a few control minislots followed by a data slot. We show that two control minislots are sufficient for our distributed scheduling algorithm to realize the same steadystate distribution as in the continuoustime case. Thus, the overhead can be as low as twice the ratio of a control minislot to a data slot. 1
Wireless Communication is in APX
 In Proc. 36th International Colloquium on Automata, Languages and Programming (ICALP
, 2009
"... Abstract. In this paper we address a common question in wireless communication: How long does it take to satisfy an arbitrary set of wireless communication requests? This problem is known as the wireless scheduling problem. Our main result proves that wireless scheduling is in APX. In addition we pr ..."
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Cited by 31 (5 self)
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Abstract. In this paper we address a common question in wireless communication: How long does it take to satisfy an arbitrary set of wireless communication requests? This problem is known as the wireless scheduling problem. Our main result proves that wireless scheduling is in APX. In addition we present a robustness result, showing that constant parameter and model changes will modify the result only by a constant. 1
Crosslayer optimization for wireless multihop networks with pairwise intersession network coding
 IEEE Journal on Selected Areas in Communications
, 2009
"... Abstract—For wireless multihop networks with unicast sessions, most coding opportunities involve only two or three sessions as coding across many sessions requires greater transmission power to broadcast the coded symbol to many receivers, which enhances interference. This work shows that with a ne ..."
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Cited by 29 (4 self)
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Abstract—For wireless multihop networks with unicast sessions, most coding opportunities involve only two or three sessions as coding across many sessions requires greater transmission power to broadcast the coded symbol to many receivers, which enhances interference. This work shows that with a new flowbased characterization of pairwise intersession network coding (coding across two unicast sessions), an optimal joint coding, scheduling, and ratecontrol scheme can be devised and implemented using only the binary XOR operation. The new scheduling/ratecontrol scheme demonstrates provably graceful throughput degradation with imperfect scheduling, which facilitates the design tradeoff between the throughput optimality and computational complexity of different scheduling schemes. Our results show that pairwise intersession network coding improves the throughput of noncoding solutions regardless of whether perfect/imperfect scheduling is used. Both the deterministic and stochastic packet arrivals and departures are considered. This work shows a striking resemblance between pairwise intersession network coding and noncoded solutions, and thus advocates extensions of noncoding wisdoms to their network coding counterpart. Index Terms—Network coding, pairwise intersession network coding, imperfect scheduling, crosslayer optimization. I.
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.
Analyzing the Performance of Greedy Maximal Scheduling via Local Pooling and Graph Theory
, 2010
"... Efficient operation of wireless networks and switches requires using simple (and in some cases distributed) scheduling algorithms. In general, simple greedy algorithms (known as Greedy Maximal Scheduling GMS) are guaranteed to achieve only a fraction of the maximum possible throughput (e.g., 50% t ..."
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Cited by 10 (1 self)
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Efficient operation of wireless networks and switches requires using simple (and in some cases distributed) scheduling algorithms. In general, simple greedy algorithms (known as Greedy Maximal Scheduling GMS) are guaranteed to achieve only a fraction of the maximum possible throughput (e.g., 50% throughput in switches). However, it was recently shown that in networks in which the Local Pooling conditions are satisfied, GMS achieves 100 % throughput. Moreover, in networks in which the σLocal Pooling conditions hold, GMS achieves σ % throughput. In this paper, we focus on identifying the specific network topologies that satisfy these conditions. In particular, we provide the first characterization of all the network graphs in which Local Pooling holds under primary interference constraints (in these networks GMS achieves 100 % throughput). This leads to a linear time algorithm for identifying Local Poolingsatisfying graphs. Moreover, by using similar graph theoretical methods, we show that in all bipartite graphs (i.e., inputqueued switches) of size up to 7×n, GMS is guaranteed to achieve 66 % throughput, thereby improving upon the previously known 50 % lower bound. Finally, we study the performance of GMS in interference graphs and show that in certain specific topologies its performance could be very bad. Overall, the paper demonstrates that using graph theoretical techniques can significantly contribute to our understanding of greedy scheduling algorithms.
Distributed Throughput Maximization in Wireless Networks via Random Power Allocation
"... Abstract—We consider throughputoptimal power allocation in multihop wireless networks. The study of this problem has been limited due to the nonconvexity of the underlying optimization problems, that prohibits an efficient solution even in a centralized setting. We take a randomization approach t ..."
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Cited by 9 (1 self)
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Abstract—We consider throughputoptimal power allocation in multihop wireless networks. The study of this problem has been limited due to the nonconvexity of the underlying optimization problems, that prohibits an efficient solution even in a centralized setting. We take a randomization approach to deal with this difficulty. To this end, we generalize the randomization framework originally proposed for input queued switches to an SINR ratebased interference model. Further, we develop distributed power allocation and comparison algorithms that satisfy these conditions, thereby achieving (nearly) 100% throughput. We illustrate the performance of our proposed power allocation solution through numerical investigation and present several extensions for the considered problem. Index Terms—Power allocation, wireless scheduling, capacity region, graphbased interference model, SINR interference model. I.