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131
A Unified Framework and Algorithm for Channel Assignment
 in Wireless Networks”, Wireless Networks, Volume 5, Issue 2
, 1999
"... Channel assignment problems in the time, frequency and code domains have thus far been studied separately. Exploiting the similarity of constraints that characterize assignments within and across these domains, we introduce the first unified framework for the study of assignment problems. Our framew ..."
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Cited by 114 (0 self)
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Channel assignment problems in the time, frequency and code domains have thus far been studied separately. Exploiting the similarity of constraints that characterize assignments within and across these domains, we introduce the first unified framework for the study of assignment problems. Our framework identifies eleven atomic constraints underlying most current and potential assignment problems, and characterizes a problem as a combination of these constraints. Based on this framework, we present a unified algorithm for efficient (T/F/C)DMA channel assignments to network nodes or to internodal links in a (multihop) wireless network. The algorithm is parametrized to allow for tradeoffselectable use as three different variants called RAND, MNF, and PMNF. We provide comprehensive theoretical analysis characterizing the worstcase performance of our algorithm for several classes of problems. In particular, we show that the assignments produced by the PMNF variant are proportional to the thickness of the network. For most typical multihop networks, the thickness can be bounded by a small constant, and hence this represents a significant theoretical result. We also experimentally study the relative performance of the variants for one node and one link assignment problem. We observe that the PMNF variant performs the best, and that a large percentage of unidirectional links is detrimental to the performance in general. 1.
Simultaneous Routing and Resource Allocation via Dual Decomposition
, 2004
"... In wireless data networks the optimal routing of data depends on the link capacities which, in turn, are determined by the allocation of communications resources (such as transmit powers and bandwidths) to the links. The optimal performance of the network can only be achieved by simultaneous optimi ..."
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Cited by 107 (4 self)
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In wireless data networks the optimal routing of data depends on the link capacities which, in turn, are determined by the allocation of communications resources (such as transmit powers and bandwidths) to the links. The optimal performance of the network can only be achieved by simultaneous optimization of routing and resource allocation. In this paper, we formulate the simultaneous routing and resource allocation problem and exploit problem structure to derive ef£cient solution methods. We use a capacitated multicommodity flow model to describe the data ¤ows in the network. We assume that the capacity of a wireless link is a concave and increasing function of the communications resources allocated to the link, and the communications resources for groups of links are limited. These assumptions allow us to formulate the simultaneous routing and resource allocation problem as a convex optimization problem over the network flow variables and the communications variables. These two sets of variables are coupled only through the link capacity constraints. We exploit this separable structure by dual decomposition. The resulting solution method attains the optimal coordination of data routing in the network layer and resource allocation in the radio control layer via pricing on the link capacities.
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 96 (0 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.
Crosslayer congestion control, routing and scheduling design in ad hoc wireless networks
 Proc. IEEE Infocom
, 2006
"... Abstract — This paper considers jointly optimal design of crosslayer congestion control, routing and scheduling for ad hoc wireless networks. We first formulate the rate constraint and scheduling constraint using multicommodity flow variables, and formulate resource allocation in networks with fixed ..."
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Cited by 95 (11 self)
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Abstract — This paper considers jointly optimal design of crosslayer congestion control, routing and scheduling for ad hoc wireless networks. We first formulate the rate constraint and scheduling constraint using multicommodity flow variables, and formulate resource allocation in networks with fixed wireless channels (or singlerate wireless devices that can mask channel variations) as a utility maximization problem with these constraints. By dual decomposition, the resource allocation problem naturally decomposes into three subproblems: congestion control, routing and scheduling that interact through congestion price. The global convergence property of this algorithm is proved. We next extend the dual algorithm to handle networks with timevarying channels and adaptive multirate devices. The stability of the resulting system is established, and its performance is characterized with respect to an ideal reference system which has the best feasible rate region at link layer. We then generalize the aforementioned results to a general model of queueing network served by a set of interdependent parallel servers with timevarying service capabilities, which models many design problems in communication networks. We show that for a general convex optimization problem where a subset of variables lie in a polytope and the rest in a convex set, the dualbased algorithm remains stable and optimal when the constraint set is modulated by an irreducible finitestate Markov chain. This paper thus presents a step toward a systematic way to carry out crosslayer design in the framework of “layering as optimization decomposition ” for timevarying channel models. I.
Maxmin Fair Scheduling in Wireless Networks
, 2002
"... We consider scheduling policies for maxmin fair allocation of bandwidth in wireless adhoc networks. We formalize the maxmin fair objective under wireless scheduling constraints. We propose a fair scheduling which assigns dynamic weights to the flows such that the weights depend on the congestion in ..."
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Cited by 82 (4 self)
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We consider scheduling policies for maxmin fair allocation of bandwidth in wireless adhoc networks. We formalize the maxmin fair objective under wireless scheduling constraints. We propose a fair scheduling which assigns dynamic weights to the flows such that the weights depend on the congestion in the neighborhood and schedule the flows which constitute a maximum weighted matching. It is possible to analytically prove that this policy attains both short term and long term fairness. We consider more generalized fairness notions, and suggest mechanisms to attain these objectives. I.
Joint Congestion Control and Media Access Control Design for Ad Hoc Wireless Networks
 In Proc. IEEE INFOCOM
, 2005
"... Abstract—We present a model for the joint design of congestion control and media access control (MAC) for ad hoc wireless networks. Using contention graph and contention matrix, we formulate resource allocation in the network as a utility maximization problem with constraints that arise from content ..."
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Cited by 79 (5 self)
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Abstract—We present a model for the joint design of congestion control and media access control (MAC) for ad hoc wireless networks. Using contention graph and contention matrix, we formulate resource allocation in the network as a utility maximization problem with constraints that arise from contention for channel access. We present two algorithms that are not only distributed spatially, but more interestingly, they decompose vertically into two protocol layers where TCP and MAC jointly solve the system problem. The first is a primal algorithm where the MAC layer at the links generates congestion (contention) prices based on local aggregate source rates, and TCP sources adjust their rates based on the aggregate prices in their paths. The second is a dual subgradient algorithm where the MAC subalgorithm is implemented through scheduling linklayer flows according to the congestion prices of the links. Global convergence properties of these algorithms are proved. This is a preliminary step towards a systematic approach to jointly design TCP congestion control algorithms and MAC algorithms, not only to improve performance, but more importantly, to make their interaction more transparent.
RealTime communication and coordination in embedded sensor networks
 PROCEEDINGS OF THE IEEE
, 2003
"... Sensor networks can be considered distributed computing platforms with many severe constraints including limited CPU speed, memory size, power, and bandwidth. Individual nodes in sensor networks are typically unreliable and the network topology dynamically changes, possibly frequently. Sensor networ ..."
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Cited by 63 (9 self)
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Sensor networks can be considered distributed computing platforms with many severe constraints including limited CPU speed, memory size, power, and bandwidth. Individual nodes in sensor networks are typically unreliable and the network topology dynamically changes, possibly frequently. Sensor networks can also be considered a form of ad hoc network. However, here also many constraints in sensor networks are different or more severe. Sensor networks also differ because of their tight interaction with the physical environment via sensors and actuators. Due to all of these differences many solutions developed for general distributed computing platforms and for ad hoc networks cannot be applied to sensor networks. Many new and exciting research challenges exist. This paper discusses the state of the art and presents the key research challenges to be solved, some with initial solutions or approaches.
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 59 (1 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.
On Power Efficient Communication over Multihop Wireless Networks: Joint Routing, Scheduling and Power Control
, 2004
"... With increasing interest in energy constrained multihop wireless networks [2], a fundamental problem is one of determining energy efficient communication strategies over these multihop networks. The simplest problem is one where a given source node wants to communicate with a given destination, wi ..."
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Cited by 49 (1 self)
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With increasing interest in energy constrained multihop wireless networks [2], a fundamental problem is one of determining energy efficient communication strategies over these multihop networks. The simplest problem is one where a given source node wants to communicate with a given destination, with a given rate over a multihop wireless network, using minimum power. Here the power refers to the total amount of power consumed over the entire network in order to achieve this rate between the source and the destination. There are three decisions that have to be made (jointly) in order to minimize the power requirement. • The path(s) that...
Complexity in geometric sinr
 In MobiHoc
, 2007
"... In this paper we study the problem of scheduling wireless links in the geometric SINR model, which explicitly uses the fact that nodes are distributed in the Euclidean plane. We present the first NPcompleteness proofs in such a model. In particular, we prove two problems to be NPcomplete: Scheduli ..."
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Cited by 46 (1 self)
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In this paper we study the problem of scheduling wireless links in the geometric SINR model, which explicitly uses the fact that nodes are distributed in the Euclidean plane. We present the first NPcompleteness proofs in such a model. In particular, we prove two problems to be NPcomplete: Scheduling and OneShot Scheduling. The first problem consists in finding a minimumlength schedule for a given set of links. The second problem receives a weighted set of links as input and consists in finding a maximumweight subset of links to be scheduled simultaneously in one shot. In addition to the complexity proofs, we devise an approximation algorithm for each problem.