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A tutorial on crosslayer optimization in wireless networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 2006
"... This tutorial paper overviews recent developments in optimization based approaches for resource allocation problems in wireless systems. We begin by overviewing important results in the area of opportunistic (channelaware) scheduling for cellular (singlehop) networks, where easily implementable my ..."
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Cited by 248 (29 self)
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This tutorial paper overviews recent developments in optimization based approaches for resource allocation problems in wireless systems. We begin by overviewing important results in the area of opportunistic (channelaware) scheduling for cellular (singlehop) networks, where easily implementable myopic policies are shown to optimize system performance. We then describe key lessons learned and the main obstacles in extending the work to general resource allocation problems for multihop wireless networks. Towards this end, we show that a cleanslate optimization based approach to the multihop resource allocation problem naturally results in a “loosely coupled” crosslayer solution. That is, the algorithms obtained map to different layers (transport, network, and MAC/PHY) of the protocol stack are coupled through a limited amount of information being passed back and forth. It turns out that the optimal scheduling component at the MAC layer is very complex and thus needs simpler (potentially imperfect) distributed solutions. We demonstrate how to use imperfect scheduling in the crosslayer framework and describe recently developed distributed algorithms along these lines. We conclude by describing a set of open research problems.
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.
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.
A Distributed Joint ChannelAssignment, Scheduling and Routing Algorithm for MultiChannel Ad Hoc Wireless Networks
 In Proceedings of IEEE INFOCOM
, 2007
"... Abstract — The capacity of ad hoc wireless networks can be substantially increased by equipping each network node with multiple radio interfaces that can operate on multiple nonoverlapping channels. However, new scheduling, channelassignment, and routing algorithms are required to fully utilize the ..."
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Cited by 81 (0 self)
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Abstract — The capacity of ad hoc wireless networks can be substantially increased by equipping each network node with multiple radio interfaces that can operate on multiple nonoverlapping channels. However, new scheduling, channelassignment, and routing algorithms are required to fully utilize the increased bandwidth in multichannel multiradio ad hoc networks. In this paper, we develop a fully distributed algorithm that jointly solves the channelassignment, scheduling and routing problem. Our algorithm is an online algorithm, i.e., it does not require prior information on the offered load to the network, and can adapt automatically to the changes in the network topology and offered load. We show that our algorithm is provably efficient. That is, even compared with the optimal centralized and offline algorithm, our proposed distributed algorithm can achieve a provable fraction of the maximum system capacity. Further, the achievable fraction that we can guarantee is larger than that of some other comparable algorithms in the literature. I.
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.
Arbitrary Throughput Versus Complexity Tradeoffs in Wireless Networks using Graph Partitioning
, 2007
"... Several policies have recently been proposed for attaining the maximum throughput region, or a guaranteed fraction thereof, through dynamic link scheduling. Among these policies, the ones that attain the maximum throughput region require a computation time which is linear in the network size, and t ..."
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Cited by 30 (7 self)
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Several policies have recently been proposed for attaining the maximum throughput region, or a guaranteed fraction thereof, through dynamic link scheduling. Among these policies, the ones that attain the maximum throughput region require a computation time which is linear in the network size, and the ones that require constant or logarithmic computation time attain only certain fractions of the maximum throughput region. In contrast, in this paper we propose policies that can attain any desirable fraction of the maximum throughput region using a computation time that is largely independent of the network size. First, using a combination of graph partitioning techniques and lyapunov arguments, we propose a simple policy for tree topologies under the primary interference model that requires each link to exchange only 1 bit information with its adjacent links and approximates the maximum throughput region using a computation time that depends only on the maximum degree of nodes and the approximation factor. Then we develop a framework for attaining arbitrary close approximations for the maximum throughput region in arbitrary networks, and use this framework to obtain any desired tradeoff between throughput guarantees and computation times for a large class of networks and interference models. Specifically, given any ɛ> 0, the maximum throughput region can be approximated in these networks within a factor of 1 − ɛ using a computation time that depends only on the maximum node degree and ɛ.
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 30 (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.
Multihop local pooling for distributed throughput maximization in wireless networks
 in IEEE INFOCOM
, 2008
"... Abstract—Efficient operation of wireless networks requires distributed routing and scheduling algorithms that take into account interference constraints. Recently, a few algorithms for networks with primary or secondaryinterference constraints have been developed. Due to their distributed operatio ..."
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Cited by 28 (4 self)
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Abstract—Efficient operation of wireless networks requires distributed routing and scheduling algorithms that take into account interference constraints. Recently, a few algorithms for networks with primary or secondaryinterference constraints have been developed. Due to their distributed operation, these algorithms can achieve only a guaranteed fraction of the maximum possible throughput. It was also recently shown that if a set of conditions (known as Local Pooling) is satisfied, simple distributed scheduling algorithms achieve 100 % throughput. However, previous work conditions and on networks with singlehop interference or singlehop traffic. In this paper, we identify several graph classes that satisfy the Local Pooling conditions, thereby enabling the use of such graphs in network design algorithms. Then, we study the multihop implications of Local Pooling. We show that in many cases, as the interference degree increases, the Local Pooling conditions are more likely to hold. Consequently, although increased interference reduces the maximum achievable throughput of the network, it tends to enable distributed algorithms to achieve 100 % of this throughput. Regarding multihop traffic, we show that if the network satisfies only the singlehop Local Pooling conditions, distributed joint routing and scheduling algorithms are not guaranteed to achieve maximum throughput. Therefore, we present new conditions for Multihop Local Pooling, under which distributed algorithms achieve 100 % throughout. Finally, we identify network topologies in which the conditions hold and discuss the algorithmic implications of the results.