6 research outputs found

    A Novel Optimal routing using Hop-by-Hop Adaptive linking

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    I am presenting the first of its kind project, the first link-state routing solution carrying traffic through packet-switched networks. At each node, for every other node, the algorithm independently and iteratively updates the fraction of traffic destined to that leaves on each of its outgoing links. At each iteration, the updates are calculated based on the shortest path to each destination as determined by the marginal costs of the network’s links. The marginal link costs used to find the shortest paths are in turn obtained from link-state updates that are flooded through the network after each iteration. For stationary input traffic, we prove that our project converges to the routing assignment that minimizes the cost of the network. Furthermore, I observe that our technique is adaptive, automatically converging to the new optimal routing assignment for quasi-static network changes. I also report numerical and experimental evaluations to confirm our theoretical predictions, explore additional aspects of the solution, and outline a proof-of-concept implementation of proposal

    Hop-by-Hop Adaptive linking A Novel Approach for Finest routing

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    Using Hop-by-Hop Adaptive linking for achieving finest routing is an unprecedented approach. And it is the first link-state routing solution carrying traffic through packet-switched networks. At each node, for every other node, the algorithm independently and iteratively updates the fraction of traffic destined to that leaves on each of its outgoing links. At each iteration, the updates are calculated based on the shortest path to each destination as determined by the marginal costs of the network’s links. The marginal link costs used to find the shortest paths are in turn obtained from link-state updates that are flooded through the network after each iteration. For stationary input traffic, we prove that our project converges to the routing assignment that minimizes the cost of the network. Furthermore, I observe that our technique is adaptive, automatically converging to the new optimal routing assignment for quasi-static network changes. I also report numerical and experimental evaluations to confirm our theoretical predictions, explore additional aspects of the solution, and outline a proof-of-concept implementation of proposal

    Simulation and analysis of adaptive routing and flow control in wide area communication networks

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    This thesis presents the development of new simulation and analytic models for the performance analysis of wide area communication networks. The models are used to analyse adaptive routing and flow control in fully connected circuit switched and sparsely connected packet switched networks. In particular the performance of routing algorithms derived from the L(_R-I) linear learning automata model are assessed for both types of network. A novel architecture using the INMOS Transputer is constructed for simulation of both circuit and packet switched networks in a loosely coupled multi- microprocessor environment. The network topology is mapped onto an identically configured array of processing centres to overcome the processing bottleneck of conventional Von Neumann architecture machines. Previous analytic work in circuit switched work is extended to include both asymmetrical networks and adaptive routing policies. In the analysis of packet switched networks analytic models of adaptive routing and flow control are integrated to produce a powerful, integrated environment for performance analysis The work concludes that routing algorithms based on linear learning automata have significant potential in both fully connected circuit switched networks and sparsely connected packet switched networks

    Simulation of a minimum delay distributed routing algorithm

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    Bibliography: p. 139.Prepared under National Science Foundation Grant NSF/ENG76-24447.Originally presented as the author's thesis, (M.S.) in the M.I.T. Dept. of Electrical Engineering and Computer Science, 1977.by John Christopher Poulos

    On quadratic adaptive routing algorithms

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