We consider the problem of distributed admission control without knowledge of the capacity region in single-hop wireless networks, for flows that require a pre-specified bandwidth from the network. We present an optimization framework that allows us to design a scheduler and resource allocator, and by properly choosing a suitable utility function in the resource allocator, we prove that existing flows can be served with a pre-specified bandwidth, while the link requesting admission can determine the largest rate that it can get such that it does not interfere with the allocation to the existing flows.
Under the assumption that requests can be split, @cite_26 proposes a solution for multi-hop multichannel networks. If the requests cannot be split, a heuristic is presented using the least-congested, minimum-hop path to route requests.
@cite_26
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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. This paper presents the evaluation of the multi-hop aggregate information efficiency of the slotted and unslotted ALOHA protocols. We consider a multi-hop wireless network where the nodes are spatially characterized by a Poisson point process and the traffic generation also follows a Poisson distribution. By applying the properties of stochastic geometry, we derive a closed-form lower bound on the outage probability as a function of the required communication rate, the single-hop distance, the number of hops and the maximum number of retransmissions. The results indicate that slotted ALOHA always outperforms its unslotted version, demonstrating the importance of synchronization in distributed networks. In addition, we show that it is always possible to optimize the network efficiency by properly setting the required rate for a given packet density. Finally, in the scenario considered, the use of retransmissions and multiple hops never achieves the best performance if compared to the option of single-hop links without retransmissions. We study the end-to-end resource allocation in an OFDM based multi-hop network consisting of a one-dimensional chain of nodes including a source, a destination, and multiple relays. The problem is to maximize the end-to-end average transmission rate under a long-term total power constraint by adapting the transmission power on each subcarrier over each hop and the transmission time used by each hop in every time frame. The solution to the problem is derived by decomposing it into two subproblems: short-term time and power allocation given an arbitrary total power constraint for each channel realization, and total power distribution over all channel realizations. We show that the optimal solution has the following features: the power allocation on subcarriers over each hop has the water-filling structure and a higher water level is given to the hop with relatively poor channel condition; meanwhile, the fraction of transmission time allocated to each hop is adjusted to keep the instantaneous rates over all hops equal. To tradeoff between performance, computational complexity and signalling overhead, three suboptimal resource allocation algorithms are also proposed. Numerical results are illustrated under different network settings and channel environments. We propose three heuristics to compute QoS routes in a multihop wireless networks considering interferences constraints. It has been proved that reservation under such conditions is an NP-complete problem. Our heuristics are based on Dijkstra's shortest path algorithm in which we integrate the notion of bandwidth capacity in order to satisfy flows requirements.We show with several simulations that these heuristics not only allows computation of routes that save bandwidth of nodes with low capacity but also that network can handle more QoS-flows. In multi-hop ad hoc networks, stations may pump more traffic into the networks than can be supported, resulting in high packet-loss rate, re-routing instability and unfairness problems. This paper shows that controlling the offered load at the sources can eliminate these problems. To verify the simulation results, we set up a real 6-node multi-hop network. The experimental measurements confirm the existence of the optimal offered load. In addition, we provide an analysis to estimate the optimal offered load that maximizes the throughput of a multi-hop traffic flow. We believe this is a first paper in the literature to provide a quantitative analysis (as opposed to simulation) for the impact of hidden nodes and signal capture on sustainable throughput. The analysis is based on the observation that a large-scale 802.11 network with hidden nodes is a network in which the carrier-sensing capability breaks down partially. Its performance is therefore somewhere between that of a carrier-sensing network and that of an Aloha network. Indeed, our analytical closed-form solution has the appearance of the throughput equation of the Aloha network. Our approach allows one to identify whether the performance of an 802.11 network is hidden-node limited or spatial-reuse limited. In this paper, we propose a distributed multi-hop interference avoidance algorithm, namely, IAA to avoid co-channel interference inside a wireless body area network (WBAN). Our proposal adopts carrier sense multiple access with collision avoidance (CSMA CA) between sources and relays and a flexible time division multiple access (FTDMA) between relays and coordinator. The proposed scheme enables low interfering nodes to transmit their messages using base channel. Depending on suitable situations, high interfering nodes double their contention windows (CW) and probably use switched orthogonal channel. Simulation results show that proposed scheme has far better minimum SINR (12dB improvement) and longer energy lifetime than other schemes (power control and opportunistic relaying). Additionally, we validate our proposal in a theoretical analysis and also propose a probabilistic approach to prove the outage probability can be effectively reduced to the minimal. 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. In this paper, a point-to-point orthogonal-frequency- division multiplexing (OFDM) system with a decode-and- forward (DF) relay is considered. The transmission consists of two hops. The source transmits in the first hop, and the relay transmits in the second hop. Each hop occupies one time slot. The relay is half-duplex, and capable of decoding the message on a particular subcarrier in one time slot, and re-encoding and forwarding it on a different subcarrier in the next time slot. Thus, each message is transmitted on a pair of subcarriers in two hops. It is assumed that the destination is capable of combining the signals from the source and the relay pertaining to the same message. The goal is to maximize the weighted sum rate of the system by jointly optimizing subcarrier pairing and power allocation on each subcarrier in each hop. The weighting of the rates is to take into account the fact that different subcarriers may carry signals for different services. Both total and individual power constraints for the source and the relay are investigated. For the situations where the relay does not transmit on some subcarriers because doing so does not improve the weighted sum rate, we further allow the source to transmit new messages on these idle subcarriers. To the best of our knowledge, such a joint optimization inclusive of the destination combining has not been discussed in the literature. The problem is first formulated as a mixed integer programming problem. It is then transformed to a convex optimization problem by continuous relaxation, and solved in the dual domain. Based on the optimization results, algorithms to achieve feasible solutions are also proposed. Simulation results show that the proposed algorithms almost achieve the optimal weighted sum rate and outperform the existing methods in various channel conditions. In this paper, we investigate the problem of Multicast Routing in Sparse Splitting Networks (MR-SSN). Given a network topology with the multicast capable nodes distributed uniformly throughout the network, and a multicast session, the MR-SSN problem is to find a route from the source node of the multicast session to all destinations of the multicast session such that the total number of fibers used in establishing the session is minimized. In this paper, we develop a rerouting algorithm for a given Steiner tree, which makes it feasible to route a multicast session using a tree-based solution in sparse light splitting optical networks. In addition, we present a heuristic based on Tabu Search (TS) that requires only one transmitter for the source node and one wavelength for each multicast session. To evaluate the performance of heuristics, we formulate the MR-SSP problem as an integer linear program (ILP), and optimally solve small instances using the commercially available linear solver, CPLEX. We test our heuristic on a wide range of network topologies. Our experimental results show that: (1) The difference between our solution and ILP optimal solution, in terms of the number of fibers used for establishing a multicast session, is within 10 in almost all the instances and within 5 in about half of the instances. (2) The average delay, taken over all destination nodes, falls within three times the optimal value. (3) A sparse light splitting all-optical network with 30 of multicast capable cross-connects has an acceptable low cost and relatively good performance. (4) The improvement achieved by TS heuristic increases considerably when the session size is large, the number of Splitter-and-Delivery cross-connects is small, and the network connectivity is dense. This letter proposes a new approach to model the intra-flow contention problem in multi-hop networks. The model takes into consideration of neighboring interference, hidden-node collision and multi-rate scenario. It can be easily used to do admission control or to calculate the end-to-end capacity of a given multi-hop route. Simulation results validate its accuracy. We consider the problem of resource allocation in downlink OFDMA systems for multi service and unknown environment. Due to users' mobility and intercell interference, the base station cannot predict neither the Signal to Noise Ratio (SNR) of each user in future time slots nor their probability distribution functions. In addition, the traffic is bursty in general with unknown arrival. The probability distribution functions of the SNR, channel state and traffic arrival density are then unknown. Achieving a multi service Quality of Service (QoS) while optimizing the performance of the system (e.g. total throughput) is a hard and interesting task since it depends on the unknown future traffic and SNR values. In this paper we solve this problem by modeling the multiuser queuing system as a discrete time linear dynamic system. We develop a robust H∞ controller to regulate the queues of different users. The queues and Packet Drop Rates (PDR) are controlled by proposing a minimum data rate according to the demanded service type of each user. The data rate vector proposed by the controller is then fed as a constraint to an instantaneous resource allocation framework. This instantaneous problem is formulated as a convex optimization problem for instantaneous subcarrier and power allocation decisions. Simulation results show small delays and better fairness among users. In this paper, a novel framework is proposed for optimizing the operation and performance of a large-scale multi-hop millimeter wave (mmW) backhaul within a wireless small cell network having multiple mobile network operators (MNOs). The proposed framework enables the small base stations to jointly decide on forming the multi-hop, mmW links over backhaul infrastructure that belongs to multiple, independent MNOs, while properly allocating resources across those links. In this regard, the problem is addressed using a novel framework based on matching theory composed of two, highly inter-related stages: a multi-hop network formation stage and a resource management stage. One unique feature of this framework is that it jointly accounts for both wireless channel characteristics and economic factors during both network formation and resource management. The multi-hop network formation stage is formulated as a one-to-many matching game, which is solved using a novel algorithm, that builds on the so-called deferred acceptance algorithm and is shown to yield a stable and Pareto optimal multi-hop mmW backhaul network. Then, a one-to-many matching game is formulated to enable proper resource allocation across the formed multi-hop network. This game is then shown to exhibit peer effects and, as such, a novel algorithm is developed to find a stable and optimal resource management solution that can properly cope with these peer effects. Simulation results show that, with manageable complexity, the proposed framework yields substantial gains, in terms of the average sum rate, reaching up to 27 and 54 , respectively, compared with a non-cooperative scheme in which inter-operator sharing is not allowed and a random allocation approach. The results also show that our framework improves the statistics of the backhaul sum rate and provides insights on how to manage pricing and the cost of the cooperative mmW backhaul network for the MNOs. In this paper, we deal with a network design problem arising from the deployment of synchronous optical networks (SONET), a standard of transmission using optical fiber technology. The problem is to find an optimal clustering of traffic demands in the network such that the total number of node assignments (and, hence, add-drop multiplexer equipment requirements) is minimized, while satisfying the ring capacity and node cardinality constraints. This problem can be conceptualized as an edge-capacitated graph partitioning problem with node cardinality constraints. We formulate the problem as a mixed-integer programming model and develop a new branch-and-cut algorithm along with preprocessing routines for optimally solving the problem. We also prescribe an effective heuristic procedure. Promising computational results are obtained using the proposed method. 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 . We address the problem of balancing the traffic load in multi-hop wireless networks. We consider a point-to-point communicating network with a uniform distribution of source-sink pairs. When routing along shortest paths, the nodes that are centrally located forward a disproportionate amount of traffic. This translates into increased congestion and energy consumption. However, the maximum load can be decreased if the packets follow curved paths. We show that the optimum such routing scheme can be expressed in terms of geometric optics and computed by linear programming. We then propose a practical solution, which we call Curveball Routing which achieves results not much worse than the optimum. We evaluate our solution at three levels of fidelity: a Java high-level simulator, the ns2 simulator, and the Intel Mirage Sensor Network Testbed. Simulation results using the high-level simulator show that our solution successfully avoids the crowded center of the network, and reduces the maximum load by up to 40 . At the same time, the increase of the expected path length is minimal, i.e., only 8 on average. Simulation results using the ns2 simulator show that our solution can increase throughput on moderately loaded networks by up to 15 , while testbed results show a reduction in peak energy usage by up to 25 . Our prototype suggests that our solution is easily deployable. 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 secondary-interference 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 regarding Local Pooling focused mostly on obtaining abstract conditions and on networks with single-hop interference or single-hop 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 single-hop 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. This paper shows that, for single-hop WDM networks, a multicast scheduling algorithm which always tries to partition a multicast transmission into multiple unicast or multicast transmissions may not always produce lower mean packet delay than a multicast scheduling algorithm which does not partition multicast transmissions. The performance of a multicast scheduling algorithm may depend on the traffic conditions and the availability of the channel resource in the network. A hybrid multicast scheduling algorithm that can produce good performance for wide ranges of the traffic conditions and the availability of the channel resource in the network is proposed. Depending on the average utilizations of the data channels and the receivers, the proposed hybrid multicast scheduling algorithm dynamically chooses to employ a multicast scheduling algorithm which always tries to partition multicast transmissions or a multicast scheduling algorithm which does not partition multicast transmissions. Extensive simulations are performed to study the performance of the proposed hybrid algorithm. Our simulation results show that the proposed hybrid algorithm produces lower mean packet delay for wide ranges of the load, the maximum multicast group size, the percentage of unicast traffic, and the number of data channels in the network compared with a multicast scheduling algorithm which always tries to partition multicast transmissions and a multicast scheduling which does not partition multicast transmissions. 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 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 queue 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. This paper considers the problem of determining the achievable rates in multi-hop wireless mesh networks with orthogonal channels. We classify wireless networks with orthogonal channels into two types, half duplex and full duplex, and consider the problem of jointly routing the flows and scheduling transmissions to achieve a given rate vector. We develop tight necessary and sufficient conditions for the achievability of the rate vector. We develop efficient and easy to implement Fully Polynomial Time Approximation Schemes for solving the routing problem. The scheduling problem is a solved as a graph edge-coloring problem. We show that this approach guarantees that the solution obtained is within 50 of the optimal solution in the worst case (within 67 of the optimal solution in a common special case) and, in practice, is close to 90 of the optimal solution on the average. The approach that we use is quite flexible and can be extended to handle more sophisticated interference conditions, and routing with diversity requirements.