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177
Joint Channel Assignment and Routing for Throughput Optimization in Multiradio Wireless Mesh Networks
, 2005
"... Multihop infrastructure wireless mesh networks offer increased reliability, coverage and reduced equipment costs over their singlehop counterpart, wireless LANs. Equipping wireless routers with multiple radios further improves the capacity by transmitting over multiple radios simultaneously using o ..."
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Cited by 434 (0 self)
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Multihop infrastructure wireless mesh networks offer increased reliability, coverage and reduced equipment costs over their singlehop counterpart, wireless LANs. Equipping wireless routers with multiple radios further improves the capacity by transmitting over multiple radios simultaneously using orthogonal channels. Efficient channel assignment and routing is essential for throughput optimization of mesh clients. Efficient channel assignment schemes can greatly relieve the interference effect of closeby transmissions; effective routing schemes can alleviate potential congestion on any gateways to the Internet, thereby improving perclient throughput. Unlike previous heuristic approaches, we mathematically formulate the joint channel assignment and routing problem, taking into account the interference constraints, the number of channels in the network and the number of radios available at each mesh router. We then use this formulation to develop a solution for our problem that optimizes the overall network throughput subject to fairness constraints on allocation of scarce wireless capacity among mobile clients. We show that the performance of our algorithms is within a constant factor of that of any optimal algorithm for the joint channel assignment and routing problem. Our evaluation demonstrates that our algorithm can effectively exploit the increased number of channels and radios, and it performs much better than the theoretical worst case bounds.
Characterizing the capacity region in multiradio multichannel wireless mesh networks
 in ACM MobiCom
, 2005
"... Next generation fixed wireless broadband networks are being increasingly deployed as mesh networks in order to provide and extend access to the internet. These networks are characterized by the use of multiple orthogonal channels and nodes with the ability to simultaneously communicate with many nei ..."
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Cited by 241 (0 self)
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Next generation fixed wireless broadband networks are being increasingly deployed as mesh networks in order to provide and extend access to the internet. These networks are characterized by the use of multiple orthogonal channels and nodes with the ability to simultaneously communicate with many neighbors using multiple radios (interfaces) over orthogonal channels. Networks based on the IEEE 802.11a/b/g and 802.16 standards are examples of these systems. However, due to the limited number of available orthogonal channels, interference is still a factor in such networks. In this paper, we propose a network model that captures the key practical aspects of such systems and characterize the constraints binding their behavior. We provide necessary conditions to verify the feasibility of rate vectors in these networks, and use them to derive upper bounds on the capacity in terms of achievable throughput, using a fast primaldual algorithm. We then develop two link channel assignment schemes, one static and the other dynamic, in order to derive lower bounds on the achievable throughput. We demonstrate through simulations that the dynamic link channel assignment scheme performs close to optimal on the average, while the static link channel assignment algorithm also performs very well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives.
MinimumCost Multicast over Coded Packet Networks
 IEEE TRANS. ON INF. THE
, 2006
"... We consider the problem of establishing minimumcost multicast connections over coded packet networks, i.e., packet networks where the contents of outgoing packets are arbitrary, causal functions of the contents of received packets. We consider both wireline and wireless packet networks as well as b ..."
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Cited by 162 (28 self)
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We consider the problem of establishing minimumcost multicast connections over coded packet networks, i.e., packet networks where the contents of outgoing packets are arbitrary, causal functions of the contents of received packets. We consider both wireline and wireless packet networks as well as both static multicast (where membership of the multicast group remains constant for the duration of the connection) and dynamic multicast (where membership of the multicast group changes in time, with nodes joining and leaving the group). For static multicast, we reduce the problem to a polynomialtime solvable optimization problem, ... and we present decentralized algorithms for solving it. These algorithms, when coupled with existing decentralized schemes for constructing network codes, yield a fully decentralized approach for achieving minimumcost multicast. By contrast, establishing minimumcost static multicast connections over routed packet networks is a very difficult problem even using centralized computation, except in the special cases of unicast and broadcast connections. For dynamic multicast, we reduce the problem to a dynamic programming problem and apply the theory of dynamic programming to suggest how it may be solved.
Hopbyhop Congestion Control over a Wireless MultiHop Network
, 2004
"... This paper focuses on congestion control over multihop, wireless networks. In a wireless network, an important constraint that arises is that due to the MAC (Media Access Control) layer. Many wireless MACs use a timedivision strategy for channel access, where, at any point in space, the physical ch ..."
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Cited by 136 (1 self)
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This paper focuses on congestion control over multihop, wireless networks. In a wireless network, an important constraint that arises is that due to the MAC (Media Access Control) layer. Many wireless MACs use a timedivision strategy for channel access, where, at any point in space, the physical channel can be accessed by a single user at each instant of time. In this paper, we develop a fair hopbyhop congestion control algorithm with the MAC constraint being imposed in the form of a channel access time constraint, using an optimization based framework. In the absence of delay, we show that this algorithm are globally stable using a Lyapunov function based approach. Next, in the presence of delay, we show that the hopbyhop control algorithm has the property of spatial spreading. In other words, focused loads at a particular spatial location in the network get "smoothed" over space. We derive bounds on the "peak load" at a node, both with hopbyhop control, as well as with endtoend control, show that significant gains are to be had with the hopbyhop scheme, and validate the analytical results with simulation.
Network Planning in Wireless Ad hoc Networks: A CrossLayer Approach
, 2005
"... allocating information carrier supplies such that certain endtoend communication demands, as a collection of multicast sessions, are fulfilled. This formulation necessitates a crosslayer coupling. We aim at a computational characterization of the performance theoretically achievable with joint ..."
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Cited by 92 (7 self)
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allocating information carrier supplies such that certain endtoend communication demands, as a collection of multicast sessions, are fulfilled. This formulation necessitates a crosslayer coupling. We aim at a computational characterization of the performance theoretically achievable with joint optimizations spanning the network stack.
Crosslayer design for lifetime maximization in interferencelimited wireless sensor networks
, 2006
"... We consider the joint optimal design of the physical, medium access control (MAC), and routing layers to maximize the lifetime of energyconstrained wireless sensor networks. The problem of computing lifetimeoptimal routing flow, link schedule, and link transmission powers for all active time slots ..."
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Cited by 88 (6 self)
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We consider the joint optimal design of the physical, medium access control (MAC), and routing layers to maximize the lifetime of energyconstrained wireless sensor networks. The problem of computing lifetimeoptimal routing flow, link schedule, and link transmission powers for all active time slots is formulated as a nonlinear optimization problem. We first restrict the link schedules to the class of interferencefree time division multiple access (TDMA) schedules. In this special case, we formulate the optimization problem as a mixed integerconvex program, which can be solved using standard techniques. Moreover, when the slots lengths are variable, the optimization problem is convex and can be solved efficiently and exactly using interior point methods. For general nonorthogonal link schedules, we propose an iterative algorithm that alternates between adaptive link scheduling and computation of optimal link rates and transmission powers for a fixed link schedule. The performance of this algorithm is compared to other design approaches for several network topologies. The results illustrate the advantages of load balancing, multihop routing, frequency reuse, and interference mitigation in increasing the lifetime of energyconstrained networks. We also briefly discuss computational approaches to extend this algorithm to large networks.
Efficient InterferenceAware TDMA Link Scheduling for Static Wireless Networks
 In ACM MobiCom
, 2006
"... We study efficient link scheduling for a multihop wireless network to maximize its throughput. Efficient link scheduling can greatly reduce the interference effect of closeby transmissions. Unlike the previous studies that often assume a unit disk graph model, we assume that different terminals cou ..."
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Cited by 85 (12 self)
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We study efficient link scheduling for a multihop wireless network to maximize its throughput. Efficient link scheduling can greatly reduce the interference effect of closeby transmissions. Unlike the previous studies that often assume a unit disk graph model, we assume that different terminals could have different transmission ranges and different interference ranges. In our model, it is also possible that a communication link may not exist due to barriers or is not used by a predetermined routing protocol, while the transmission of a node always result interference to all nonintended receivers within its interference range. Using a mathematical formulation, we develop synchronized TDMA link schedulings that optimize the networking throughput. Specifically, by assuming known link capacities and link traffic loads, we study link scheduling under the RTS/CTS interference model and the protocol interference model with fixed transmission power. For both models, we present both efficient centralized and distributed algorithms that use time slots within a constant factor of the optimum. We also present efficient distributed algorithms whose performances are still comparable with optimum, but with much less communications. Our theoretical results are corroborated by extensive simulation studies.
Multicast capacity for large scale wireless ad hoc networks
 In ACM Mobicom
, 2007
"... In this paper, we study the capacity of a largescale random wireless network for multicast. Assume that n wireless nodes are randomly deployed in a square region with sidelength a and all nodes have the uniform transmission range r and uniform interference range R> r. We further assume that eac ..."
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Cited by 68 (23 self)
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In this paper, we study the capacity of a largescale random wireless network for multicast. Assume that n wireless nodes are randomly deployed in a square region with sidelength a and all nodes have the uniform transmission range r and uniform interference range R> r. We further assume that each wireless node can transmit/receive at W bits/second over a common wireless channel. For each node vi, we randomly pick k − 1 nodes from the other n − 1 nodes as the receivers of the multicast session rooted at node vi. The aggregated multicast capacity is defined as the total data rate of all multicast sessions in the network. In this paper we derive matching asymptotic upper bounds and lower bounds on multicast capacity of random wireless networks. We show that the total multicast capacity is Θ( � n log n · W √ k) when k = O ( n log n
Joint asynchronous congestion control and distributed scheduling for multihop wireless networks
 in the Proceedings IEEE Infocom
"... Abstract — We consider a multihop wireless network shared by many users. For an interference model that only constrains a node to either transmit or receive at a time, but not both, we propose an architecture for fair resource allocation that consists of a distributed scheduling algorithm operating ..."
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Cited by 60 (16 self)
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Abstract — We consider a multihop wireless network shared by many users. For an interference model that only constrains a node to either transmit or receive at a time, but not both, we propose an architecture for fair resource allocation that consists of a distributed scheduling algorithm operating in conjunction with an asynchronous congestion control algorithm. We show that the proposed joint congestion control and scheduling algorithm supports at least onethird of the throughput supportable by any other algorithm, including centralized algorithms. I.
Network coding for efficient wireless unicast
 in IEEE International Zurich Seminar on Communications
, 2006
"... Abstract — We consider the problem of establishing efficient unicast connections over wireless packet networks. We show how network coding, combined with distributed flow optimization, gives a practicable approach that promises to significantly outperform the present approach of endtoend or linkb ..."
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Cited by 53 (9 self)
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Abstract — We consider the problem of establishing efficient unicast connections over wireless packet networks. We show how network coding, combined with distributed flow optimization, gives a practicable approach that promises to significantly outperform the present approach of endtoend or linkbylink retransmission combined with route optimization, where performance may be measured in terms of energy consumption, congestion, or any other cost that increases with the number of transmissions made by each node. We present a specific coding scheme and specific distributed flow optimization techniques that may be used to form the basis of a protocol. I.