Browsing by Author "Chen, Johnny"

Now showing 1 - 5 of 5
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    A New Approach to Routing With Dynamic Metrics
    (1998-11-18) Chen, Johnny; Druschel, Peter; Subramanian, Devika
    We present a new routing algorithm to compute paths within a network using dynamic link metrics. Dynamic link metrics are cost metrics that depend on a link's dynamic characteristics, e.g., the congestion on the link. Our algorithm is destination-initiated: the destination initiates a global path computation to itself using dynamic link metrics. All other destinations that do not initiate this dynamic metric computation use paths that are calculated and maintained by a traditional routing algorithm using static link metrics. Analysis of Internet packet traces show that a high percentage of network traffic is destined for a small number of networks. Because our algorithm is destination-initiated, it achieves maximum performance at minimum cost when it only recomputes dynamic metric paths to these selected "hot" destination networks. This selective approach to route recomputation reduces many of the problems (principally route oscillations) associated with calculating all routes simultaneously. We compare the routing efficiency and end-to-end performance of our algorithm against those of traditional algorithms using dynamic link metrics. The results of our experiments show that our algorithm can provide higher network performance at a significantly lower routing cost under conditions that arise in real networks. The effectiveness of the algorithm stems from the independent, time-staggered recomputation of important paths using dynamic metrics, allowing for splits in congested traffic that cannot be made by traditional routing algorithms.
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    A Simple, Practical Distributed Multi-Path Routing Algorithm
    (1998-07-16) Chen, Johnny; Druschel, Peter; Subramanian, Devika
    We present a simple and practical distributed routing algorithm based on backward learning. The algorithm periodically floods \emscout packets that explore paths to a destination in reverse. Scout packets are small and of fixed size; therefore, they lend themselves to hop-by-hop piggy-backing on data packets, largely defraying their cost to the network. The correctness of the proposed algorithm is analytically verified. Our algorithm also has loop-free multi-path routing capabilities, providing increased network utilization and route stability. The Scout algorithm requires very little state and computation in the routers, and can efficiently and gracefully handle high rates of change in the network's topology and link costs. An extensive simulation study shows that the proposed algorithm is competitive with link-state and distance vector algorithms, particularly in highly dynamic networks.
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    Ants and Reinforcement Learning: A Case Study in Routing in Dynamic Networks
    (1997-02-17) Chen, Johnny; Druschel, Peter; Subramanian, Devika
    We investigate two new distributed routing algorithms for data networks based on simple biological "ants" that explore the network and rapidly learn good routes, using a novel variation of reinforcement learning. These two algorithms are fully adaptive to topology changes and changes in link costs in the network, and have space and computational overheads that are competitive with traditional packet routing algorithms: although they can generate more routing traffic when the rate of failures in a network is low, they perform much better under higher failure rates. Both algorithms are more resilient than traditional algorithms, in the sense that random corruption of routing state has limited impact on the computation of paths. We present convergence theorems for both of our algorithms drawing on the theory of non-stationary and stationary discrete-time Markov chains over the reals. We present an extensive empirical evaluation of our algorithms on a simulator that is widely used in the computer networks community for validating and testing protocols. We present comparative results on data delivery performance, aggregate routing traffic (algorithm overhead), as well as the degree of resilience for our new algorithms and two traditional routing algorithms in current use. We also show that the performance of our algorithms scale well with increase in network size using a realistic topology.
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    New approaches to routing for large-scale data networks
    (2000) Chen, Johnny; Druschel, Peter
    This thesis develops new routing methods for large-scale, packet-switched data networks such as the Internet. The methods developed increase network performance by considering routing approaches that take advantage of more available network resources than do current methods. Two approaches are explored: dynamic metric and multipath routing. Dynamic metric routing provides paths that change dynamically in response to network traffic and congestion, thereby increasing network performance because data travel less congested paths. The second approach, multipath routing, provides multiple paths between nodes and allows nodes to use these paths to best increase their network performance. Nodes in this environment achieve increased performance through aggregating the resources of multiple paths. This thesis implements and analyzes algorithms for these two routing approaches. The first approach develops hybrid-Scout, a dynamic metric routing algorithm that calculates independent and selective dynamic metric paths. These two calculation properties are key to reducing routing costs and avoiding routing instabilities, two difficulties commonly experienced in traditional dynamic metric routing. For the second approach, multipath routing, this thesis develops a complete multipath network that includes the following components: routing algorithms that compute multiple paths, a multipath forwarding method to ensure that data travel their specified paths, and an end-host protocol that effectively uses multiple paths. Simulations of these two routing approaches and their components demonstrate significant improvement over traditional routing strategies. The hybrid-Scout algorithm requires 3--4 times to 1--2 orders of magnitude less routing cost compared to traditional dynamic metric routing algorithms while delivering comparable network performance. For multipath routing, nodes using the multipath protocol fully exploit the offered paths and increase performance linearly in the additional resources provided by the multipath network. The performance improvements validate the multipath routing algorithms and the effectiveness of the proposed end-host protocol. Furthermore, this new multipath forwarding method allows multipath networks to be supported at low routing costs. This thesis demonstrates that the proposed methods to implement dynamic metric and multipath routing are efficient and deliver significant performance improvements.
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    New Approaches to Routing for Large-Scale Data Networks
    (1999-06-21) Chen, Johnny
    This thesis develops new routing methods for large-scale, packet-switched data networks such as the Internet. The methods developed increase network performance by considering routing approaches that take advantage of more available network resources than do current methods. Two approaches are explored: dynamic metric and multipath routing. Dynamic metric routing provides paths that change dynamically in response to network traffic and congestion, thereby increasing network performance because data travel less congested paths. The second approach, multipath routing, provides multiple paths between nodes and allows nodes to use these paths to best increase their network performance. Nodes in this environment achieve increased performance through aggregating the resources of multiple paths. This thesis implements and analyzes algorithms for these two routing approaches. The first approach develops hybrid-Scout, a dynamic metric routing algorithm that calculates independent and selective dynamic metric paths. These two calculation properties are key to reducing routing costs and avoiding routing instabilities, two difficulties commonly experienced in traditional dynamic metric routing. For the second approach, multipath routing, this thesis develops a complete multipath network that includes the following components: routing algorithms that compute multiple paths, a multipath forwarding method to ensure that data travel their specified paths, and an end-host protocol that effectively uses multiple paths. Simulations of these two routing approaches and their components demonstrate significant improvement over traditional routing strategies. The hybrid-Scout algorithm requires 3-4 times to 1-2orders of magnitude less routing cost compared to traditional dynamic metric routing algorithms while delivering comparable network performance. For multipath routing, nodes using the multipath protocol fully exploit the offered paths and increase performance linearly in the additional resources provided by the multipath network. The performance improvements validate the multipath routing algorithms and the effectiveness of the proposed end-host protocol. Furthermore, this new multipath forwarding method allows multipath networks to be supported at low routing costs. This thesis demonstrates that the proposed methods to implement dynamic metric and multipath routing are efficient and deliver significant performance improvements.