144 research outputs found

    Continuum Equilibria and Global Optimization for Routing in Dense Static Ad Hoc Networks

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    We consider massively dense ad hoc networks and study their continuum limits as the node density increases and as the graph providing the available routes becomes a continuous area with location and congestion dependent costs. We study both the global optimal solution as well as the non-cooperative routing problem among a large population of users where each user seeks a path from its origin to its destination so as to minimize its individual cost. Finally, we seek for a (continuum version of the) Wardrop equilibrium. We first show how to derive meaningful cost models as a function of the scaling properties of the capacity of the network and of the density of nodes. We present various solution methodologies for the problem: (1) the viscosity solution of the Hamilton-Jacobi-Bellman equation, for the global optimization problem, (2) a method based on Green's Theorem for the least cost problem of an individual, and (3) a solution of the Wardrop equilibrium problem using a transformation into an equivalent global optimization problem

    Autonomous Traffic Balancing Routing in Wireless Mesh Networks

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    Numerical solutions of continuum equilibria for routing in dense ad-hoc networks

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    International audienceWe study the routing problem in massively dense static ad-hoc networks as the node density increases. We use a fluid approximation in which the graph providing the available routes becomes so dense that it can be approximated by a continuous area which inherits from the original problem the cost structure: a cost density is defined at each point on the limit plain; it is a function of the location and the congestion at that point. We solve numerically the routing problem for the case where the cost density is linear with respect to congestion and we obtain a result of convergence via Finite Elements Method

    Self-organized backpressure routing for the wireless mesh backhaul of small cells

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    The ever increasing demand for wireless data services has given a starring role to dense small cell (SC) deployments for mobile networks, as increasing frequency re-use by reducing cell size has historically been the most effective and simple way to increase capacity. Such densification entails challenges at the Transport Network Layer (TNL), which carries packets throughout the network, since hard-wired deployments of small cells prove to be cost-unfeasible and inflexible in some scenarios. The goal of this thesis is, precisely, to provide cost-effective and dynamic solutions for the TNL that drastically improve the performance of dense and semi-planned SC deployments. One approach to decrease costs and augment the dynamicity at the TNL is the creation of a wireless mesh backhaul amongst SCs to carry control and data plane traffic towards/from the core network. Unfortunately, these lowcost SC deployments preclude the use of current TNL routing approaches such as Multiprotocol Label Switching Traffic Profile (MPLS-TP), which was originally designed for hard-wired SC deployments. In particular, one of the main problems is that these schemes are unable to provide an even network resource consumption, which in wireless environments can lead to a substantial degradation of key network performance metrics for Mobile Network Operators. The equivalent of distributing load across resources in SC deployments is making better use of available paths, and so exploiting the capacity offered by the wireless mesh backhaul formed amongst SCs. To tackle such uneven consumption of network resources, this thesis presents the design, implementation, and extensive evaluation of a self-organized backpressure routing protocol explicitly designed for the wireless mesh backhaul formed amongst the wireless links of SCs. Whilst backpressure routing in theory promises throughput optimality, its implementation complexity introduces several concerns, such as scalability, large end-to-end latencies, and centralization of all the network state. To address these issues, we present a throughput suboptimal yet scalable, decentralized, low-overhead, and low-complexity backpressure routing scheme. More specifically, the contributions in this thesis can be summarized as follows: We formulate the routing problem for the wireless mesh backhaul from a stochastic network optimization perspective, and solve the network optimization problem using the Lyapunov-driftplus-penalty method. The Lyapunov drift refers to the difference of queue backlogs in the network between different time instants, whereas the penalty refers to the routing cost incurred by some network utility parameter to optimize. In our case, this parameter is based on minimizing the length of the path taken by packets to reach their intended destination. Rather than building routing tables, we leverage geolocation information as a key component to complement the minimization of the Lyapunov drift in a decentralized way. In fact, we observed that the combination of both components helps to mitigate backpressure limitations (e.g., scalability,centralization, and large end-to-end latencies). The drift-plus-penalty method uses a tunable optimization parameter that weight the relative importance of queue drift and routing cost. We find evidence that, in fact, this optimization parameter impacts the overall network performance. In light of this observation, we propose a self-organized controller based on locally available information and in the current packet being routed to tune such an optimization parameter under dynamic traffic demands. Thus, the goal of this heuristically built controller is to maintain the best trade-off between the Lyapunov drift and the penalty function to take into account the dynamic nature of semi-planned SC deployments. We propose low complexity heuristics to address problems that appear under different wireless mesh backhaul scenarios and conditions..

    Load balancing in multi-hop wireless ad hoc networks

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    In this thesis we study the load distribution and load balancing problem in wireless ad hoc networks. Using a discrete unit disk graph model of the network, we analyze the distribution of load induced by greedy routing in the network with an all-to-all communication pattern between the nodes. We derive an estimate for average load of the nodes in the network. We also calculate the expected load of a node as a function of its geometric coordinates in the network. We express the actual load of a node in the network as a random variable and obtain the parameters of this random variable. Using this random variable we derive an estimate for the maximum load of the nodes in the network. Our result is more accurate than previous studies which were based on a continuous model of the network. We analyze how different parameters of the network, i.e., number of nodes, transmission range, and different routing algorithms can affect the parameters of the load distribution. We give a technique to reduce the variance of the load distribution, and hence decrease the maximum load of the nodes in the network. Our technique can be combined with any location-based routing algorithm. We also introduce a class of algorithms that improve the maximum expected load of nodes in the network. Experimental results show that our algorithms outperform other existing algorithms in reducing the maximum load of the networ

    Asymptotically optimal time synchronization in dense sensor networks

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    Local Area Dynamic Routing Protocol: a Position Based Routing Protocol for MANET

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    A Mobile Ad Hoc Network (MANET) comprises mobile nodes (MNs), equipped with wireless communications devices; which form a temporary communication network without fixed network infrastructure or topology. The characteristics of MANET are: limited bandwidth; limited radio range; high mobility; and vulnerability to attacks that degrade the signal to noise ratio and bit error rates. These characteristics create challenges to MANET routing protocols. In addition, the mobility pattern of the MNs also has major impact on the MANET routing protocols. The issue of routing and maintaining packets between MNs in the mobile ad hoc networks (MANETs) has always been a challenge; i.e. encountering broadcast storm under high node density, geographically constrained broadcasting of a service discovery message and local minimum problem under low node density. This requires an efficient design and development of a lightweight routing algorithm which can be handled by those GPS equipped devices. Most proposed location based routing protocols however, rely on a single route for each data transmission. They also use a location based system to find the destination address of MNs which over time, will not be accurate and may result in routing loop or routing failure. Our proposed lightweight protocol, ‘Local Area Network Dynamic Routing’ (LANDY) uses a localized routing technique which combines a unique locomotion prediction method and velocity information of MNs to route packets. The protocol is capable of optimising routing performance in advanced mobility scenarios, by reducing the control overhead and improving the data packet delivery. In addition, the approach of using locomotion prediction, has the advantage of fast and accurate routing over other position based routing algorithms in mobile scenarios. Recovery with LANDY is faster than other location protocols, which use mainly greedy algorithms, (such as GPRS), no signalling or configuration of the intermediate nodes is required after a failure. The key difference is that it allows sharing of locomotion and velocity information among the nodes through locomotion table. The protocol is designed for applications in which we expect that nodes will have access to a position service (e.g., future combat system). Simulation results show that LANDY`s performance improves upon other position based routing protocols
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