47 research outputs found

    Routing algorithms for recursively-defined data centre networks

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    The server-centric data centre network architecture can accommodate a wide variety of network topologies. Newly proposed topologies in this arena often require several rounds of analysis and experimentation in order that they might achieve their full potential as data centre networks. We propose a family of novel routing algorithms on two well-known data centre networks of this type, (Generalized) DCell and FiConn, using techniques that can be applied more generally to the class of networks we call completely connected recursively-defined networks. In doing so, we develop a classification of all possible routes from server-node to server-node on these networks, called general routes of order t, and find that for certain topologies of interest, our routing algorithms efficiently produce paths that are up to 16% shorter than the best previously known algorithms, and are comparable to shortest paths. In addition to finding shorter paths, we show evidence that our algorithms also have good load-balancing properties

    An incrementally scalable and cost-efficient interconnection structure for datacenters

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.The explosive growth in the volume of data storing and complexity of data processing drive data center networks (DCNs) to become incrementally scalable and cost-efficient while to maintain high network capacity and fault tolerance. To address these challenges, this paper proposes a new structure, called Totoro, which is defined recursively and hierarchically: dual-port servers and commodity switches are used to make Totoro affordable; a bunch of servers are connected to an intra-switch to form a basic partition; to construct a high-level structure, a half of the backup ports of servers in the low-level structures are connected by inter-switches in order to incrementally build a larger partition. Totoro is incrementally scalable since expanding the structure does not require any rewiring or routing alteration. We further design a distributed and fault-tolerant routing protocol to handle multiple types of failures. Experimental results demonstrate that Totoro is able to satisfy the demands of fault tolerance and high throughput. Furthermore, architecture analysis indicates that Totoro balances between performance and costs in terms of robustness, structural properties, bandwidth, economic costs and power consumption.This work is supported by the NSF of China under grant (no. 61272073, and no. 61572232), the NSF of Guangdong Province (no. S2013020012865)

    Measuring and Understanding Throughput of Network Topologies

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    High throughput is of particular interest in data center and HPC networks. Although myriad network topologies have been proposed, a broad head-to-head comparison across topologies and across traffic patterns is absent, and the right way to compare worst-case throughput performance is a subtle problem. In this paper, we develop a framework to benchmark the throughput of network topologies, using a two-pronged approach. First, we study performance on a variety of synthetic and experimentally-measured traffic matrices (TMs). Second, we show how to measure worst-case throughput by generating a near-worst-case TM for any given topology. We apply the framework to study the performance of these TMs in a wide range of network topologies, revealing insights into the performance of topologies with scaling, robustness of performance across TMs, and the effect of scattered workload placement. Our evaluation code is freely available
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