An incrementally scalable and cost-efficient interconnection structure for datacenters

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)

Optimal Networks from Error Correcting Codes

To address growth challenges facing large Data Centers and supercomputing clusters a new construction is presented for scalable, high throughput, low latency networks. The resulting networks require 1.5-5 times fewer switches, 2-6 times fewer cables, have 1.2-2 times lower latency and correspondingly lower congestion and packet losses than the best present or proposed networks providing the same number of ports at the same total bisection. These advantage ratios increase with network size. The key new ingredient is the exact equivalence discovered between the problem of maximizing network bisection for large classes of practically interesting Cayley graphs and the problem of maximizing codeword distance for linear error correcting codes. Resulting translation recipe converts existent optimal error correcting codes into optimal throughput networks.Comment: 14 pages, accepted at ANCS 2013 conferenc

On random wiring in practicable folded clos networks for modern datacenters

Big scale, high performance and fault-tolerance, low-cost and graceful expandability are pursued features in current datacenter networks (DCN). Although there have been many proposals for DCNs, most modern installations are equipped with classical folded Clos networks. Recently, regular random topologies, as the Jellyfish, have been proposed for DCNs. However, their completely unstructured nature entails serious design problems. In this paper we propose Random Folded Clos (RFC) and Hydra networks in which the interconnection between certain switches levels is made randomly. Both RFCs and Hydras preserve important properties of Clos networks that provide a straightforward deadlock-free multi-path routing. The proposed networks leverage randomness to be gracefully expandable, thereby allowing for fine grain upgrading. RFCs and Hydras are compared in the paper, in topological and cost terms, against fat-trees, orthogonal fat-trees and random regular networks. Also, experiments are carried out to simulate their performance under synthetic traffic patterns emulating common loads present in warehouse scale computers. These theoretical and empirical studies reveal the interest of these topologies, concluding that Hydra constitutes a practicable alternative to current datacenter networks since it appropriately balance all the main design requirements. Moreover, Hydras perform better than the fat-trees, their natural competitor, being able to connect the same or more computing nodes with significant lower cost and latency while exhibiting comparable throughput. © 1990-2012 IEEE

ExCCC-DCN: A Highly Scalable, Cost-Effective and Engergy-Efficient Data Center Stucture

PublishedThis is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Over the past decade, many data centers have been constructed around the world due to the explosive growth of data volume and type. The cost and energy consumption have become the most important challenges of building those data centers. Data centers today use commodity computers and switches instead of high-end servers and interconnections for cost-effectiveness. In this paper, we propose a new type of interconnection networks called Exchanged Cube-Connected Cycles (ExCCC). The ExCCC network is an extension of Exchanged Hypercube (EH) network by replacing each node with a cycle. The EH network is based on link removal from a Hypercube network, which makes the EH network more cost-effective as it scales up. After analyzing the topological properties of ExCCC, we employ commodity switches to construct a new class of data center network models, namely ExCCC-DCN, by leveraging the advantages of the ExCCC architecture. The analysis and experimental results demonstrate that the proposed ExCCC-DCN models significantly outperform four state-of-the-art data center network models in terms of the total cost, power consumption, scalability, and other static characteristics. It achieves the goals of low cost, low energy consumption, high network throughput, and high scalability simultaneously.This work is supported by the National Natural Science Foundation (NSF) of China under Grant (No. 61572232, and No. 61272073), the key program of Natural Science Foundation of Guangdong Province (No.S2013020012865), and the Fundamental Research Funds for the Central Universities

Space Shuffle: A Scalable, Flexible, and High-Bandwidth Data Center Network

Data center applications require the network to be scalable and bandwidth-rich. Current data center network architectures often use rigid topologies to increase network bandwidth. A major limitation is that they can hardly support incremental network growth. Recent work proposes to use random interconnects to provide growth flexibility. However routing on a random topology suffers from control and data plane scalability problems, because routing decisions require global information and forwarding state cannot be aggregated. In this paper we design a novel flexible data center network architecture, Space Shuffle (S2), which applies greedy routing on multiple ring spaces to achieve high-throughput, scalability, and flexibility. The proposed greedy routing protocol of S2 effectively exploits the path diversity of densely connected topologies and enables key-based routing. Extensive experimental studies show that S2 provides high bisectional bandwidth and throughput, near-optimal routing path lengths, extremely small forwarding state, fairness among concurrent data flows, and resiliency to network failures