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Minimum-interference channel assignment in multi-radio wireless mesh networks
- IN SECON
, 2006
"... In this paper, we consider multi-hop wireless mesh networks, where each router node is equipped with multiple radio interfaces and multiple channels are available for communication. We address the problem of assigning channels to communication links in the network with the objective of minimizing ov ..."
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Cited by 107 (2 self)
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In this paper, we consider multi-hop wireless mesh networks, where each router node is equipped with multiple radio interfaces and multiple channels are available for communication. We address the problem of assigning channels to communication links in the network with the objective of minimizing overall network interference. Since the number of radios on any node can be less than the number of available channels, the channel assignment must obey the constraint that the number of different channels assigned to the links incident on any node is atmost the number of radio interfaces on that node. The above optimization problem is known to be NP-hard. We design centralized and distributed algorithms for the above channel assignment problem. To evaluate the quality of the solutions obtained by our algorithms, we develop a semidefinite program formulation of our optimization problem to obtain a lower bound on overall network interference. Empirical evaluations on randomly generated network graphs show that our algorithms perform close to the above established lower bound, with the difference diminishing rapidly with increase in number of radios. Also, detailed ns-2 simulation studies demonstrate the performance potential of our channel assignment algorithms in 802.11-based multi-radio mesh networks.
A distributed optimization algorithm for multi-hop cognitive radio networks
- IEEE INFOCOM
, 2008
"... Cognitive radio (CR) is a revolution in radio technology and is viewed as an enabling technology for dynamic spectrum access. This paper investigates how to design distributed algorithm for a multi-hop CR network, with the objective of maximizing data rates for a set of user communication sessions. ..."
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Cited by 44 (1 self)
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Cognitive radio (CR) is a revolution in radio technology and is viewed as an enabling technology for dynamic spectrum access. This paper investigates how to design distributed algorithm for a multi-hop CR network, with the objective of maximizing data rates for a set of user communication sessions. We study this problem via a cross-layer optimization approach, with joint consideration of power control, scheduling, and routing. For the centralized problem, we show that this optimization problem is in the form of mixed integer nonlinear program (MINLP), which cannot be solved in polynomial time. To develop a performance benchmark for the distributed optimization algorithm, we first develop a tight upper bound on the objective function via relaxation on the MINLP problem. Subsequently, we develop a distributed optimization algorithm that iteratively increases the data rate among user communication sessions. During each iteration, there are two separate processes, a Conservative Iterative Process (CIP) and an Aggressive Iterative Process (AIP). Both CIP and AIP incorporates routing, min-imalist scheduling, and power control/scheduling modules. Via simulation results, we compare the performance of the distributed optimization algorithm with the upper bound and validate its efficacy.
High Throughput Spectrum-aware Routing for Cognitive Radio Networks
- PROC. OF INTERNATIONAL CONFERENCE ON COGNITIVE RADIO ORIENTED WIRELESS NETWORKS AND COMMUNICATIONS (CROWNCOM)
, 2007
"... Dynamic spectrum networks enable fast deployment of new wireless technologies by effectively utilizing allocated yet unused wireless spectrum. By sensing and utilizing available wireless channels, cognitive radio devices can provide high throughput, low latency communication. Existing schemes for ch ..."
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Cited by 30 (0 self)
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Dynamic spectrum networks enable fast deployment of new wireless technologies by effectively utilizing allocated yet unused wireless spectrum. By sensing and utilizing available wireless channels, cognitive radio devices can provide high throughput, low latency communication. Existing schemes for channel assignment suffer drawbacks in throughput and reachability in the presence of location-dependent channel availability. We propose SPEctrum-Aware Routing Protocol (SPEAR), a robust and efficient distributed channel assignment and routing protocol for dynamic spectrum networks based on two principles: integrated spectrum and route discovery for robust multi-hop path formation, and distributed path reservations to minimize inter- and intra-flow interference. Through simulations and testbed measurements, we show that SPEAR establishes robust paths in diverse spectrum conditions and provides near-optimal throughput and end-to-end packet delivery latency. SPEAR performs extremely fast flow setup and teardowns, and can maintain interference-free flows in the presence of variance in channel availability.
Resource allocation in multi-radio multi-channel multi-hop wireless networks
- IEEE INFOCOM 2008
, 2008
"... Abstract—A joint congestion control, channel allocation and scheduling algorithm for multi-channel multi-interface multi-hop wireless networks is discussed. The goal of maximizing a utility function of the injected traffic, while guaranteeing queues stability, is defined as an optimization problem w ..."
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Cited by 22 (0 self)
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Abstract—A joint congestion control, channel allocation and scheduling algorithm for multi-channel multi-interface multi-hop wireless networks is discussed. The goal of maximizing a utility function of the injected traffic, while guaranteeing queues stability, is defined as an optimization problem where the input traffic intensity, channel loads, interface to channel binding and transmission schedules are jointly optimized by a dynamic algorithm. Due to the inherent NP-Hardness of the scheduling problem, a simple centralized heuristic is used to define a lower bound for the performance of the whole optimization algorithm. The behavior of the algorithm for different numbers of channels, interfaces and traffic flows is shown through simulations. I.
1 Fast Data Collection in Tree-Based Wireless Sensor Networks
"... Abstract—We investigate the following fundamental question- how fast can information be collected from a wireless sensor network organized as tree? To address this, we explore and evaluate a number of different techniques using realistic simulation models under the many-to-one communication paradigm ..."
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Cited by 21 (3 self)
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Abstract—We investigate the following fundamental question- how fast can information be collected from a wireless sensor network organized as tree? To address this, we explore and evaluate a number of different techniques using realistic simulation models under the many-to-one communication paradigm known as convergecast. We first consider time scheduling on a single frequency channel with the aim of minimizing the number of time slots required (schedule length) to complete a convergecast. Next, we combine scheduling with transmission power control to mitigate the effects of interference, and show that while power control helps in reducing the schedule length under a single frequency, scheduling transmissions using multiple frequencies is more efficient. We give lower bounds on the schedule length when interference is completely eliminated, and propose algorithms that achieve these bounds. We also evaluate the performance of various channel assignment methods and find empirically that for moderate size networks of about 100 nodes, the use of multi-frequency scheduling can suffice to eliminate most of the interference. Then, the data collection rate no longer remains limited by interference but by the topology of the routing tree. To this end, we construct degree-constrained spanning trees and capacitated minimal spanning trees, and show significant improvement in scheduling performance over different deployment densities. Lastly, we evaluate the impact of different interference and channel models on the schedule length. Index Terms—Convergecast, TDMA scheduling, multiple channels, power-control, routing trees. 1
Distributed Scheduling Scheme for Video Streaming over Multi-Channel Multi-Radio Multi-Hop Wireless Networks
- IEEE J. Select. Areas Commun
, 2010
"... Abstract—An important issue of supporting multi-user video streaming over wireless networks is how to optimize the system-atic scheduling by intelligently utilizing the available network resources while, at the same time, to meet each video’s Quality of Service (QoS) requirement. In this work, we st ..."
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Cited by 21 (1 self)
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Abstract—An important issue of supporting multi-user video streaming over wireless networks is how to optimize the system-atic scheduling by intelligently utilizing the available network resources while, at the same time, to meet each video’s Quality of Service (QoS) requirement. In this work, we study the problem of video streaming over multi-channel multi-radio multi-hop wireless networks, and develop fully distributed scheduling schemes with the goals of minimizing the video distortion and achieving certain fairness. We first construct a general distortion model according to the network’s transmission mechanism, as well as the rate distortion characteristics of the video. Then, we formulate the scheduling as a convex optimization problem, and propose a distributed solution by jointly considering channel assignment, rate allocation, and routing. Specifically, each stream strikes a balance between the selfish motivation of minimizing video distortion and the global performance of minimizing network congestions. Furthermore, we extend the proposed scheduling scheme by addressing the fairness problem. Unlike prior works that target at users ’ bandwidth or demand fairness, we propose a media-aware distortion-fairness strategy which is aware of the characteristics of video frames and ensures max-min distortion-fairness sharing among multiple video streams. We provide extensive simulation results which demonstrate the effectiveness of our proposed schemes. Index Terms—multi-channel multi-radio; video transmission; distributed scheduling; QoS; fairness. I.
Multi-dimensional conflict graph based computing for optimal capacity
- in MR-MC wireless networks”, in Proc. IEEE ICDCS
, 2010
"... Abstract—Optimal capacity analysis in multi-radio multichannel wireless networks by nature incurs the formulation of a mixed integer programming, which is NP-hard in general. The current state of the art mainly resorts to heuristic algorithms to obtain an approximate solution. In this paper, we prop ..."
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Cited by 18 (6 self)
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Abstract—Optimal capacity analysis in multi-radio multichannel wireless networks by nature incurs the formulation of a mixed integer programming, which is NP-hard in general. The current state of the art mainly resorts to heuristic algorithms to obtain an approximate solution. In this paper, we propose a novel concept of multi-dimensional conflict graph (MDCG). Based on MDCG, the capacity optimization issue can be accurately modeled as a linear programming (LP) multi-commodity flow (MCF) problem, augmented with maximal independent set (MIS) constraints. The MDCG-based solution will provide not only the maximum throughput or utility, but also the optimal configurations on routing, channel assignment, and scheduling. Moreover, the MDCG-based optimal capacity planning can exploit dynamic channel swapping, which is difficult to achieve for those existing heuristic algorithms. A particular challenge associated with the MDCG-based capacity analysis is to search exponentially many possible MISs. We theoretically show that in fact only a small set of critical MISs, termed as critical MIS set, will be scheduled in the optimal resource allocation. We then develop a polynomial computing method, based on a novel scheduling index ordering (SIO) concept, to search the critical MIS set. Extensive numerical results are presented to demonstrate the efficiency of the MDCGbased resource allocation compared to well-known heuristic algorithm presented in [1], and the efficiency of SIO-based MIS computing compared to the widely adopted random algorithm for searching MISs. I.
Distributed Strategies for Channel Allocation and Scheduling in Software-Defined Radio Networks
"... Abstract—Equipping wireless nodes with multiple radios can significantly increase the capacity of wireless networks, by making these radios simultaneously transmit over multiple nonoverlapping channels. However, due to the limited number of radios and available orthogonal channels, designing efficie ..."
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Cited by 14 (3 self)
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Abstract—Equipping wireless nodes with multiple radios can significantly increase the capacity of wireless networks, by making these radios simultaneously transmit over multiple nonoverlapping channels. However, due to the limited number of radios and available orthogonal channels, designing efficient channel assignment and scheduling algorithms in such networks is a major challenge. In this paper, we present provablygood distributed algorithms for simultaneous channel allocation of individual links and packet-scheduling, in Software-Defined Radio (SDR) wireless networks. Our distributed algorithms are very simple to implement, and do not require any coordination even among neighboring nodes. A novel access hash function or random oracle methodology is one of the key drivers of our results. With this access hash function, each radio can know the transmitters ’ decisions for links in its interference set for each time slot without introducing any extra communication overhead between them. Further, by utilizing the inductivescheduling technique, each radio can also backoff appropriately to avoid collisions. Extensive simulations demonstrate that our bounds are valid in practice. I.
Distributed cross-layer optimization for cognitive radio networks
- IEEE Trans. Veh. Technol
, 2010
"... Abstract—This paper presents a distributed cross-layer opti-mization algorithm for a multihop cognitive radio network, with the objective of maximizing data rates for a set of user communi-cation sessions. We study this problem with joint consideration of power control, scheduling, and routing. Even ..."
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Cited by 10 (0 self)
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Abstract—This paper presents a distributed cross-layer opti-mization algorithm for a multihop cognitive radio network, with the objective of maximizing data rates for a set of user communi-cation sessions. We study this problem with joint consideration of power control, scheduling, and routing. Even under a centralized approach, such a problem has a mixed-integer nonlinear program formulation and is likely NP-hard. Thus, a distributed problem is very challenging. The main contribution of this paper is the de-velopment of a distributed optimization algorithm that iteratively increases data rates for user communication sessions. During each iteration, our algorithm has routing, minimalist scheduling, and power control/scheduling modules for improving the current solution at all three layers. To evaluate the performance of the distributed optimization algorithm, we compare it with an upper bound of the objective function. Results show that the distributed optimization algorithm can achieve a performance close to this upper bound. Because the optimal solution (unknown) is between the upper bound and the solution obtained by our distributed algorithm, we conclude that the results obtained by our distributed algorithm are highly competitive. Index Terms—Cognitive radio network (CRN), cross-layer optimization, distributed algorithm, power control, routing, scheduling. I.
Channel Assignment and Link Scheduling in Multi-Radio Multi-Channel Wireless Mesh Networks
"... Capacity limitation is one of the fundamental issues in wireless mesh networks. This paper addresses capacity improvement issues in multi-radio multi-channel wireless mesh networks. Our objective is to find both dynamic and static channel assignments and corresponding link schedules that maximize th ..."
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Cited by 8 (1 self)
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Capacity limitation is one of the fundamental issues in wireless mesh networks. This paper addresses capacity improvement issues in multi-radio multi-channel wireless mesh networks. Our objective is to find both dynamic and static channel assignments and corresponding link schedules that maximize the network capacity. We focus on determining the highest gain we can achieve from increasing the number of radios and channels under certain traffic demands. We consider two different types of traffic demands. One is expressed in the form of data size vector, and the other is in the form of data rate vector. For the first type of traffic demand, our objective is to minimize the number of time slots to transport all the data. For the second type of traffic demand, our objective is to satisfy the bandwidth requirement as much as possible. We perform a trade-off analysis between network performance and hardware cost based on the number of radios and channels in different topologies. This work provides valuable insights for wireless mesh network designers during network planning and deployment. I.