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

AgileDCN:An Agile Reconfigurable Optical Data Center Network Architecture

This paper presents a detailed examination of a novel data center network (DCN) that can satisfy the high capacity and low latency requirements of modern cloud computing applications. This reconfigurable architecture called AgileDCN uses fast-switching optical components with a centralized control function and workload scheduler. By providing a highly flexible optical network fabric between server racks, very high network efficiencies can be achieved even under imbalanced loading patterns. Our simulation results show that, at high (70%) loads, TCP flow completion times in the AgileDCN are significantly lower than in an equivalent electronic leaf-spine network

Providing Performance Guarantees in Data Center Network Switching Fabrics

This paper proposes a novel and highly scalable multistage packet-switch design based on Networks-on-Chip (NoC). In particular, we describe a three-stage packet-switch fabric with a Round-Robin packets dispatching scheme where each central stage module is an Output-Queued Unidirectional NoC (OQ-UDN), instead of the conventional single-hop crossbar. We test the switch performance under different traffic profiles. In addition to experimental results, we present an analytical approximation for the theoretical throughput of the switch under Bernoulli i.i.d arrivals. We also provide an upper-bound estimation of the end-to-end blocking probability in the proposed switch to help predict performance and to optimize the design

Robust Data Center Network Design using Space Division Multiplexing

With the ever-increasing demand for data transmission in our generation where Internet and cloud concepts play a vital role, it has become essential that we handle data in a most efficient way. A possible solution to overcome the capacity crunch problem which is so evident in future, is applications of Space Division Multiplexing, where we explore the remaining unused domain that is the spatial domain. Space Division Multiplexing using multi-core fibers (MCFs), and few-mode fibers (FMFs) has been studied in our work to enhance the data-carrying capacity of optical fibers while minimizing the transmission cost per bit. The objective of our work is to develop a path protection scheme to handle communication requests in data center (DC) networks using elastic optical networking and space division multiplexing (SDM). Our approach to this problem is to 1) determine a dedicated primary and backup path, 2) possible allocation of spectrum using the flex-grid fixed-SDM model, 3) choose the best possible modulation format to minimize the number of subcarriers needed for data transfer, 4) measure the cost of the resources required to handle the new requests. We propose to evaluate the developed Integer Linear Programming (ILP) formulation based on this scheme, considering the possibility of disasters. We study the impact of the design on the cost of the solution, hence explore whether it promotes significant resource savings