We investigate the performance of First-In, First-Out (FIFO) queues over wireless networks. We characterize the stability region of a general scenario where an arbitrary number of FIFO queues, which are served by a wireless medium, are shared by an arbitrary number of flows. In general, the stability region of this system is non-convex. Thus, we develop a convex inner-bound on the stability region, which is provably tight in certain cases. The convexity of the inner bound allows us to develop a resource allocation scheme; dFC. Based on the structure of dFC, we develop a stochastic flow control and scheduling algorithm; qFC. We show that qFC achieves optimal operating point in the convex inner bound. Simulation results show that our algorithms significantly improve the throughput of wireless networks with FIFO queues, as compared to the well-known queue-based flow control and max-weight scheduling.
The strengths of backpressure-based network control have recently received increasing interest in terms of practical implementation. Multi-path TCP scheme is implemented over wireless mesh networks in @cite_1 for routing and scheduling packets using a backpressure based heuristic. At the link layer, @cite_4 @cite_8 @cite_11 propose, analyze, and evaluate link layer backpressure-based implementations with queue prioritization and congestion window size adjustment. Backpressure is implemented over sensor networks @cite_14 and wireless multi-hop networks @cite_15 . In these schemes, either last-in, first-out queueing is employed @cite_14 or link layer FIFO queues are strictly controlled @cite_15 to reduce the number of packets in the FIFO queues, hence HOL blocking.
@cite_14 @cite_4 @cite_8 @cite_1 @cite_15 @cite_11
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There has been extensive work on network architectures that support multi-path routing to improve performance in wireless mesh networks. However, previous work uses ad-hoc design principles that cannot guarantee any network-wide performance objectives such as conjointly maximizing resource utilization and improving fairness. In parallel, numerous theoretical results have addressed the issue of optimizing a combined metric of network utilization and fairness using techniques based on back-pressure scheduling, routing and flow control. However, the proposed theoretical algorithms are extremely difficult to implement in practice, especially in the presence of the 802.11 MAC and TCP. We propose Horizon, a novel system design for multi-path forwarding in wireless meshes, based on the theoretical results on back-pressure. Our design works with an unmodified TCP stack and on top of the existing 802.11 MAC. We modified the back-pressure approach to obtain a simple 802.11-compatible packet-forwarding heuristic and a novel, light-weight path estimator, while maintaining global optimality properties. We propose a delayed reordering algorithm that eliminates TCP timeouts while keeping TCP packet reordering to a minimum. We have evaluated our implementation on a 22-node testbed. We have shown that Horizon effectively utilizes available resources (disjoint paths). In contrast to previous work, our design not only avoids bottlenecks but also optimally load-balances traffic across them when needed, improving fairness among competing flows. To our knowledge, Horizon is the first practical wireless system based on back-pressure. In a wireless ad hoc network with multihop transmissions and interference-limited link rates, can we balance power control in the physical layer and congestion control in the transport layer to enhance the overall network performance, while maintaining the stability, robustness, and architectural modularity of the network? We present a distributive power control algorithm that couples with the original TCP protocols to increase the end-to-end throughput and energy efficiency of the network. Under the rigorous framework of nonlinearly constrained optimization, we prove the convergence of this coupled system to the global optimum of joint power control and congestion control, for both synchronized and asynchronous implementations. The rate of convergence is geometric and a desirable modularity between the transport and physical layers is maintained. In particular, when the congestion control mechanism is TCP Vegas, that a simple utilization in the physical layer of the router buffer occupancy information suffices to achieve the joint optimum of this cross layer design. Both analytic results and simulations illustrate other desirable properties of the proposed algorithm, including robustness to channel outage and to path loss estimation errors, and flexibility in trading-off performance optimality for implementation simplicity. Congestion control in wireless multi-hop networks is challenging and complicated because of two reasons. First, interference is ubiquitous and causes loss in the shared medium. Second, wireless multihop networks are characterized by the use of diverse and dynamically changing routing paths. Traditional end point based congestion control protocols are ineffective in such a setting resulting in unfairness and starvation. This paper adapts the optimal theoretical work of Tassiulas and Ephremedes on cross-layer optimization of wireless networks involving congestion control, routing and scheduling, for practical solutions to congestion control in multi-hop wireless networks. This work is the first that implements in real off-shelf radios, a differential backlog based MAC scheduling and router-assisted backpressure congestion control for multi-hop wireless networks. Our adaptation, called DiffQ, is implemented between transport and IP and supports legacy TCP and UDP applications. In a network of 46 IEEE 802.11 wireless nodes, we demonstrate that DiffQ far outperforms many previously proposed "practical" solutions for congestion control. Current data collection protocols for wireless sensor networks are mostly based on quasi-static minimum-cost routing trees. We consider an alternative, highly-agile approach called backpressure routing, in which routing and forwarding decisions are made on a per-packet basis. Although there is a considerable theoretical literature on backpressure routing, it has not been implemented on practical systems to date due to concerns about packet looping, the effect of link losses, large packet delays, and scalability. Addressing these concerns, we present the Backpressure Collection Protocol (BCP) for sensor networks, the first ever implementation of dynamic backpressure routing in wireless networks. In particular, we demonstrate for the first time that replacing the traditional FIFO queue service in backpressure routing with LIFO queues reduces the average end-to-end packet delays for delivered packets drastically (75 under high load, 98 under low load). Further, we improve backpressure scalability by introducing a new concept of floating queues into the backpressure framework. Under static network settings, BCP shows a more than 60 improvement in max-min rate over the state of the art Collection Tree Protocol (CTP). We also empirically demonstrate the superior delivery performance of BCP in highly dynamic network settings, including conditions of extreme external interference and highly mobile sinks. 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 single-rate 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 multi-rate 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 time-varying 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 dual-based algorithm remains stable and optimal when the constraint set is modulated by an irreducible finite-state Markov chain. This paper thus presents a step toward a systematic way to carry out cross-layer design in the framework of “layering as optimization decomposition” for time-varying channel models. There has been considerable work developing a stochastic network utility maximization framework using Backpressure algorithms, also known as MaxWeight. A key open problem has been the development of utility-optimal algorithms that are also delay-efficient. In this paper, we show that the Backpressure algorithm, when combined with the last-in-first-out (LIFO) queueing discipline (called LIFO-Backpressure), is able to achieve a utility that is within O(1 V) of the optimal value, for any scalar V ≥ 1, while maintaining an average delay of O([log(V)]2) for all but a tiny fraction of the network traffic. This result holds for a general class of problems with Markovian dynamics. Remarkably, the performance of LIFO-Backpressure can be achieved by simply changing the queueing discipline; it requires no other modifications of the original Backpressure algorithm. We validate the results through empirical measurements from a sensor network testbed, which show a good match between theory and practice. Because some packets may stay in the queues for a very long time under LIFO-Backpressure, we further develop the LIFOp-Backpressure algorithm, which generalizes LIFOp-Backpressure by allowing interleaving between first-in-first-out (FIFO) and LIFO. We show that LIFOp Backpressure also achieves the same O(1 V) close-to-optimal utility performance and guarantees an average delay of O([log(V)]2) for the packets that are served during the LIFO period. Several high-speed TCP variants are adopted by end users and therefore, heterogeneous congestion control has become the characteristic of newly emerging high-speed optical networks. In contrast to homogeneous TCP flows, fairness among heterogeneous TCP flows now depends on router parameters such as queue management scheme and buffer size. To the best of our knowledge, this is the first study of fairness performance among heterogeneous TCP variants over a 10 Gbps high-speed optical network environment. Our evaluation scenarios for heterogeneous TCP flows consist of TCP variants with substantial presence in current Internet; therefore, TCP-SACK, CUBIC TCP (CUBIC) and HighSpeed TCP (HSTCP) compete for bottleneck bandwidth. Experimental results for fairness are presented for different queue management schemes, such as Drop-tail, Random Early Detection (RED), CHOose and Keep for responsive flows CHOose and Kill for unresponsive flows (CHOKe), and Approximate Fair Dropping (AFD), with varying degree of buffer sizes. We observe heterogeneous TCP flows induce more unfairness than homogeneous ones. Active queue management (AQM) schemes, RED, CHOKe, and AFD, improve fairness for large buffer sizes as compared to Drop-tail, whereas AQM schemes lose the fairness advantage for small buffer sizes. This study provides preliminary results for fairness challenges to deploy all-optical routers with limited buffer size. Backpressure routing and scheduling, with throughput-optimal operation guarantee, is a promising technique to improve throughput in wireless multi-hop networks. Although backpressure is conceptually viewed as layered, the decisions of routing and scheduling are made jointly, which imposes several challenges in practice. In this work, we present Diff-Max, an approach that separates routing and scheduling and has three strengths: (i) Diff-Max improves throughput significantly, (ii) the separation of routing and scheduling makes practical implementation easier by minimizing cross-layer operations; i.e., routing is implemented in the network layer and scheduling is implemented in the link layer, and (iii) the separation of routing and scheduling leads to modularity; i.e., routing and scheduling are independent modules in Diff-Max, and one can continue to operate even if the other does not. Our approach is grounded in a network utility maximization (NUM) formulation and its solution. Based on the structure of Diff-Max, we propose two practical schemes: Diff-subMax and wDiff-subMax. We demonstrate the benefits of our schemes through simulation in ns-2. Contemporary wireless multi-hop networks operate much below their capacity due to the poor coordination among transmitting nodes. In this paper we present XPRESS, a cross-layer backpressure architecture designed to reach the full capacity of wireless multi-hop networks. Instead of a collection of poorly coordinated wireless routers, XPRESS turns a mesh network into a wireless switch. Transmissions over the network are scheduled using a throughput-optimal backpressure algorithm. Realizing this theoretical concept entails several challenges, which we identify and address with a cross-layer design and implementation on top of our wireless hardware platform. In contrast to previous work, we implement and evaluate backpressure scheduling over a TDMA MAC protocol, as it was originally proposed in theory. Our experiments in an indoor testbed show that XPRESS can yield up to 128 throughput gains over 802.11. We introduce a methodology for studying wireless ad hoc networks in a multihop traffic environment. Our approach is to use theoretical upper bounds on network performance for evaluating the effects of various design choices: we focus on power control, the queuing discipline, the choice of routing and media access protocols, and their interactions. Using this framework, we then concentrate on the problem of medium access for wireless multihop networks. We first study CSMA CA, and find that its performance strongly depends on the choice of the accompanying routing protocol. We then introduce two protocols that outperform CSMA CA, both in terms of energy efficiency and achievable throughput. The progressive back off algorithm (PBOA) performs medium access jointly with power control. The progressive rump up algorithm (PRUA) sacrifices energy efficiency in favor of higher throughput. Both protocols slot time, and are integrated with queuing disciplines that are more relaxed than the first in first out (FIFO) rule. They are totally distributed and the overhead they require does not increase with the size and node density of the network. In this paper we investigate the potential benefits of coordinated congestion control for multipath data transfers, and contrast with uncoordinated control. For static random path selections, we show the worst-case throughput performance of uncoordinated control behaves as if each user had but a single path (scaling like log(log(N)) log(N) where N is the system size, measured in number of resources). Whereas coordinated control gives a throughput allocation bounded away from zero, improving on both uncoordinated control and on the greedy-least loaded path selection of e.g. Mitzenmacher. We then allow users to change their set of routes and introduce the notion of a Nash equilibrium. We show that with RTT bias (as in TCP Reno), uncoordinated control can lead to inefficient equilibria. With no RTT bias, both uncoordinated or coordinated Nash equilibria correspond to desirable welfare maximising states. Moreover, simple path reselection polices that shift to paths with higher net benefit can find these states. A major challenge in the design and operation of wireless networks is to jointly route packets and schedule transmissions to efficiently share the common spectrum among links in the same area. Due to the lack of central control in wireless networks, these algorithms have to be decentralized. It was recently shown that distributed (greedy) algorithms can usually guarantee only fractional throughput. It was also recently shown that if a set of conditions regarding the network topology (known as Local Pooling) is satisfied, simple distributed maximal weight (greedy) scheduling algorithms achieve 100 throughput. In this paper, we focus on networks in which packets have to undergo multihop routing and derive multihop local pooling conditions for that setting. In networks satisfying these conditions, a backpressure-based joint routing and scheduling algorithm employing maximal weight scheduling achieves 100 throughput. The throughput of wireless networks can be significantly improved by multi-channel communications compared with single-channel communications since the use of multiple channels can reduce interference influence. In this paper, we study interference-aware topology control and QoS routing in IEEE 802.11-based multi-channel wireless mesh networks with dynamic traffic. Channel assignment and routing are two basic issues in such networks. Different channel assignments can lead to different network topologies. We present a novel definition of co-channel interference. Based on this concept, we formally define and present an effective heuristic for the minimum INterference Survivable Topology Control (INSTC) problem which seeks a channel assignment for the given network such that the induced network topology is interference-minimum among all K-connected topologies. We then formulate the Bandwidth-Aware Routing (BAR) problem for a given network topology, which seeks routes for QoS connection requests with bandwidth requirements. We present a polynomial time optimal algorithm to solve the BAR problem under the assumption that traffic demands are splittable. For the non-splittable case, we present a maximum bottleneck capacity path routing heuristic. Simulation results show that compared with the simple common channel assignment and shortest path routing approach, our scheme improves the system performance by 57 on average in terms of connection blocking ratio. Compared to single-hop networks such as WiFi, multihop infrastructure wireless mesh networks (WMNs) can potentially embrace the broadcast benefits of a wireless medium in a more flexible manner. Rather than being point-to-point, links in the WMNs may originate from a single node and reach more than one other node. Nodes located farther than a one-hop distance and overhearing such transmissions may opportunistically help relay packets for previous hops. This phenomenon is called opportunistic overhearing listening. With multiple radios, a node can also improve its capacity by transmitting over multiple radios simultaneously using orthogonal channels. Capitalizing on these potential advantages requires effective routing and efficient mapping of channels to radios (channel assignment (CA)). While efficient channel assignment can greatly reduce interference from nearby transmitters, effective routing can potentially relieve congestion on paths to the infrastructure. Routing, however, requires that only packets pertaining to a particular connection be routed on a predetermined route. Random network coding (RNC) breaks this constraint by allowing nodes to randomly mix packets overheard so far before forwarding. A relay node thus only needs to know how many packets, and not which packets, it should send. We mathematically formulate the joint problem of random network coding, channel assignment, and broadcast link scheduling, taking into account opportunistic overhearing, the interference constraints, the coding constraints, the number of orthogonal channels, the number of radios per node, and fairness among unicast connections. Based on this formulation, we develop a suboptimal, auction-based solution for overall network throughput optimization. Performance evaluation results show that our algorithm can effectively exploit multiple radios and channels and can cope with fairness issues arising from auctions. Our algorithm also shows promising gains over traditional routing solutions in which various channel assignment strategies are used. In this paper, we propose a cross layer optimization framework for multi-hop routing and resource allocation design in an orthogonal frequency division multiple access (OFDMA) based wireless mesh network. The network under consideration is assumed to consist of fixed mesh routers (or base station routers) inter-connected using OFDMA wireless links with some of the mesh routers functioning as gateways to a wired network. The objective of our cross-layer formulation is to allow joint determination of power control, frequency-selective OFDMA scheduling and multi-hop routing in order to maximize the minimum throughput that can be supported to all mesh routers. Results of our investigations under typical cellular deployment, propagation and channel model assumptions show that this approach achieves significant mesh throughput improvements primarily due to the following: (a) frequency selective scheduling with OFDMA which provides improved tone diversity thus allowing more efficient bandwidth utilization relative to single carrier methods; and (b) multi-hop routing which provides improved path diversity relative to single hop transmissions. The fair allocation of resources among different nodes is one of the critical problems in wireless mesh networks. Existing solutions mainly focus on rate-limitation policies or distributed fair MAC schemes at the potential expense of total network utilization. This paper investigates a special starvation problem among TCP flows that are different hops away from the BS, as well as its recently proposed solution, the ‘Minimum Content Window’ policy based on IEEE 802.11e. It is found that the aggregate throughput degrades sharply because the effect of this policy on the TCP congestion mechanism has been overlooked. This paper proposes a priority-based congestion control by using ‘Cross-Layer Explicit Congestion Notification’. Analysis and simulation results demonstrate that our scheme can improve the fairness of TCP flows while the aggregate throughput is at least 20 higher than the ‘Minimum Content Window’ policy. Copyright © 2011 John Wiley & Sons, Ltd. The goal of this paper is to establish which practical routing schemes for wireless networks are most suitable for power-limited and bandwidth-limited communication regimes. We regard channel state information (CSI) at the receiver and point-to-point capacity-achieving codes for the additive white Gaussian noise (AWGN) channel as practical features, interference cancellation (IC) as possible, but less practical, and synchronous cooperation (CSI at the transmitters) as impractical. We consider a communication network with a single source node, a single destination node, and N-1 intermediate nodes placed equidistantly on a line between them. We analyze the minimum total transmit power needed to achieve a desired end-to-end rate for several schemes and demonstrate that multihop communication with spatial reuse performs very well in the power-limited regime, even without IC. However, within a class of schemes not performing IC, single-hop transmission (directly from source to destination) is more suitable for the bandwidth-limited regime, especially when higher spectral efficiencies are required. At such higher spectral efficiencies, the gap between single-hop and multihop can be closed by employing IC, and we present a scheme based upon backward decoding that can remove all interference from the multihop system with an arbitrarily small rate loss. This new scheme is also used to demonstrate that rates of O(log N) are achievable over linear wireless networks even without synchronous cooperation. In this paper, a novel collision-free MAC scheme supporting multimedia applications is proposed for wireless mesh backbone. The proposed scheme is distributed, simple, and scalable. Benefiting from the fixed locations of wireless routers, the proposed MAC scheme reduces the control overhead greatly as compared with the conventional contention-based MAC protocols (e.g., IEEE 802.11). In addition, the proposed scheme can provide guaranteed priority access to real-time traffic and, at the same time, ensure fair channel access from the routers with data traffic. Unlike most of the existing works which focus on single-hop transmissions, the proposed MAC scheme takes the intra-flow correlations between up-stream and down-stream hops of a multi-hop flow into consideration. To avoid buffer overflow at bottleneck routers, a simple but effective congestion control mechanism is proposed. Simulation results demonstrate that the proposed scheme significantly improves the delay performance of real-time traffic, the fairness of data traffic, and the end-to-end data throughput, as compared with IEEE 802.11. In this paper, we propose a cross-layer deflect routing scheme that improves effective throughput of multi-hop millimeter-wave wireless personal area network (mmWave WPAN) system. The upcoming mmWave WPAN is designed to provide Gbps-order transmission capability, targeting applications like high definition TV (HDTV) transmission, high speed wireless docking and gaming etc. Adopting multi-hop relay offers solutions to the issues existing in mmWave WPAN system such as limited coverage range caused by the significant path loss, dramatic communication link change due to the unexpected blockage of the line-of-sight (LOS) path etc. However, multi-hop relay on the other hand decreases the effective throughput because of the required extra time. As a result, the compromised throughput may not be able to support the above applications which are greedy for data rate. Inspired by the fact that the significant path loss of millimeter-wave environment can provide good space isolation, our proposed scheme manages to improve the multi-hop throughput by sharing time slots for relay path with direct path for other transmissions. We also propose two algorithms, namely random fit deflect routing (RFDR) and best fit deflect routing (BFDR), to find the relay path on which the interference due to time slot sharing is low enough to guarantee the concurrent transmissions. Computer simulations show that, in realistic 60GHz environment, the effective multi-hop throughput can be improved up to 45 . In this paper we study the problem of jointly performing scheduling and congestion control in mobile ad-hoc networks so that network queues remain bounded and the resulting flow rates satisfy an associated network utility maximization problem. In recent years a number of papers have presented theoretical solutions to this problem that are based on combining differential-backlog scheduling algorithms with utility-based congestion control. However, this work typically does not address a number of issues such as how signaling should be performed and how the new algorithms interact with other wireless protocols. In this paper we address such issues. In particular: ldr We define a specific network utility maximization problem that we believe is appropriate for mobile adhoc networks. ldr We describe a wireless greedy primal dual (wGPD) algorithm for combined congestion control and scheduling that aims to solve this problem. ldr We show how the wGPD algorithm and its associated signaling can be implemented in practice with minimal disruption to existing wireless protocols. ldr We show via OPNET simulation that wGPD significantly outperforms standard protocols such as 802.11 operating in conjunction with TCP. This work was supported by the DARPA CBMANET program.