Novel flat DCN architecture based on optical switches with fast flow control

To solve the bandwidth and latency issues in current hierarchical data center network (DCN) architectures based on electrical switches, we propose a novel hybrid DCN architecture based on distributed flow-controlled fast optical switches (FOS) and modified top-of-the-rack (TOR) switches (HiFOST). The intra-cluster interconnection of HiFOST is built by FOS with wavelength switching in nanoseconds’ time for an efficient statistical multiplexing operation, while the inter-cluster interconnection is connected by the TOR interfaces directly. Due to the lack of practical optical buffers, optical flow control is implemented to retransmit packets in case of contention. We investigate the performance of HiFOST DCN with different TOR buffer sizes, optical link capacities, elastic allocation of transceivers, and network scales under realistic data center (DC) traffic. The results show an average server-to-server latency of less than 2.8 μs, a packet loss <5.6×10−6 at load of 0.5 for a DC size of 94,080 servers with limited 50 KB TOR buffer. In addition, for scaling out the servers’ number and scaling up the data rate of connected servers, the cost and power consumption of the HiFOST DCN have been investigated and compared with the electrical Fat-Tree and Leaf-Spine DCN architectures, as well as with the optical H-LION and OPSquare DCN architectures. Results indicate that, for 94,080 servers operating at 10 Gb/s, HiFOST has a 48.2% and 34.1% savings of the cost and 46.3% and 32.5% savings of the power consumption with respect to the Fat-Tree and Leaf-Spine, respectively. For a HiFOST DCN supporting a 10880 server, scaling up the operating data rate of the server to 100 Gb/s, the HiFOST solution has a cost savings of 35.6% and 34.1% and power consumption of 56.5% and 59.2% as compared to the Fat-Tree and Leaf-Spine, respectively.

In recent years, data center network (DCN) architectures (e.g., DCell [5], FiConn [6], BCube [4], FatTree [1], and VL2 [2]) received a surge of interest from both the industry and academia. However, none of existing efforts provide an in-depth understanding of the impact of these architectures on application performance in practical multi-tier systems under realistic workload. Moreover, it is also unclear how these architectures are affected in virtualized environments. In this paper, we fill this void by conducting an experimental evaluation of FiConn and FatTree, each respectively as a representative of hierarchical and flat architectures, in a three-tier transaction system using virtual machine (VM) based implementation. We observe several fundamental characteristics that are embedded in both classes of network topologies and cast a new light on the implication of virtualization in DCN architectures. Issues observed in this paper are generic and should be properly addressed by any DCN architectures before being considered for actual deployment, especially in mission-critical real-time transaction systems.

Understanding data center network architectures in virtualized environments: A view from multi-tier applications

With the development of cloud computing, data center network (DCN) architectures as the core of the cloud platform received a surge of interesting from both the industry and academia. However, assessments of those new DCN architectures are mainly concentrated in load balancing, improvement of architectures and as well as some research of performance analysis in visualized environment. Moreover, none of them focus on the security in DCN architectures. In this paper, we propose contribution matrix method based on information entropy theory from the point of view of node importance which is the basic of the topology vulnerability. In addition, we conduct an experimental evaluation of the state-of-the-art Multi-rooted Tree and FiConn architectures, each respectively as a representative of the switch-centric network architecture and server-centric network architecture. Firstly, we use an undirected graph theory to describe the architecture. Secondly, we obtain the associated matrix of betweenness and degree, and calculate their weights by information entropy theory. And then, according to the definition 3 (see Section III-B); we obtain the contribution matrix for each one. Last but not least, we get the value of node importance for each node of normalized. Compared with other methods, our proposed method is effective and has a much higher accuracy. Furthermore, our method is generic and can be widely used for the new DCN architectures.

The network of traditional data center has been usually designed and constructed for the provision of user's equal access of data centre's resource or data. Therefore, network administrators have a strong tendency to manage user traffic from the viewpoint that the traffic has a similar size and characteristics. But, the emersion of big data begins to make data centers have to deal with 1015 byte-data transfer at once. Such a big data transfer can cause problems in network traffic management in the existed data center. And, the tiered network architecture of the legacy data center magnifies the magnitude of the problems. One of the well-known big data in science is from large hadron collider such as LHC in Swiss CERN. CERN LHC generates multi-peta byte data per year. From our experience of CERN data service, this paper showed the impact of network traffic affected by large-scale data stream using NS2 simulation, and then, suggested the evolution direction based on separating of large-scale data stream for the big data center's network architecture.

As the volume of data keeps growing rapidly, more and more storage devices, servers and network devices are continuously added into data centers to store, manage and analyze the data. The industry experience indicates that, instead of a huge number of servers added at a time, the data center network also expands gradually by adding a small number of servers from time to time. As a result, how to achieve an incremental scalability is becoming a very important challenge in designing modern data center network architectures in order to maintain the topological properties unchanged when the size of data centers grows. In this paper, we propose a new type of data center network architecture named HSDC (High Scalability Data Center Network Architecture) based on the hypercube network. The HSDC is constructed by using $m$m-port switches and 2-port servers. The fault-tolerant routing algorithm designed in this paper for HSDC can be executed on any vertex and is able to construct a path between any pair of vertices. In order to achieve an incremental scalability, we further propose three types of incomplete HSDC structures that allow gradually adding servers into the structures, while maintaining all the topological properties. The simulation experiments and performance results demonstrate that the throughput of HSDC is comparable to that of Fat-Tree, BCube and DCell. Furthermore, the analysis results indicate that HSDC strikes a good balance among diameter, bisection width, incremental scalability, cost and energy consumption in contrast to the state-of-the-art data center network architectures.

Data center networks (DCNs) are at the forefront of a radical transformation, fueled by the rapid rise of artificial intelligence (AI), cloud-native adoption, and enterprise digitalization, which together place unprecedented demands on their design and performance. From healthcare AI and intelligent transportation to business analytics, modern DCNs are expected to support a diverse and evolving mix of bandwidth-demanding applications, each with distinct quality of service (QoS) requirements. Yet, most state-of-the-art DCN solutions rely on oversimplified DCN data traffic models, failing to address the required application-level differentiation in terms of end-to-end (E2E) latency demands. In response, we propose ALAS-DCN, a novel, to our knowledge, application-aware, low-latency, scalable DCN architecture, based on optical packet switching in the intra-rack and inter-rack domains that is both designed and rigorously evaluated using commercial QoS specifications and realistic traffic patterns of different applications coexisting within the same DCN. ALAS-DCN integrates three hierarchical optical sub-networks: intra-rack, inter-rack, and bridge, each governed by a custom wavelength division multiplexing (WDM) medium access control (MAC) protocol that dynamically prioritizes critical traffic packets, according to the specific application E2E latency demands. Unlike prior approaches, our evaluation leverages realistic workload traces generated by established traffic generators, capturing the application diversity within modern data center (DC) environments. Extensive experimental simulations across five representative DC categories, each hosting a different mix of modern applications, demonstrate that ALAS-DCN consistently achieves up to 95% throughput efficiency and sub-µs latency for high priority traffic across a variety of applications, consistently meeting their differentiated latency constraints. Scalable up to 20,000 servers, ALAS-DCN redefines the DCN as not just a transport layer but an intelligent enabler of next-generation application performance.

Data Centers (DCs) are experiencing a tremendous growth in the number of hosted servers. Aggregate bandwidth requirement is a major bottleneck to data center performance. New Data Center Network (DCN) architectures are proposed to handle different challenges faced by current DCN architecture. In this paper we have implemented and simulated two promising DCN architectural models, namely switch-based and hybrid models, and compared their effectiveness by monitoring the network throughputs and average packet latencies. The presented analysis may be a background for the further studies on the simulation and implementation of the DCN customized topologies, and customized addressing protocols in the large-scale data centers.

All optical or hybrid electrical/optical switching data center network (DCN) architectures are capable of adapting the optical-layer topology to various network traffic demands based on the flexibility of optical switching technology. The topology reconfiguration strategies in previous research simply attempt to reconfigure optical circuit switching (OCS) links to offload heavier rack-to-rack traffic. However, due to the complex multi-layer interconnections and the various network traffic patterns in DCNs, the OCS links will not only offload the network traffic between its source and destination racks, but also forward the network traffic that belongs to the adjacent racks of the source and destinations racks. Previous strategies ignore the forwarding traffic and result in sub-optimal solutions. In order to overcome the shortcomings of previous methods and make full use of the OCS link resources in DCNs, an effective topology reconfiguration strategy named optical circuit bridge (OCBridge) has been proposed in our recent work. The main idea of our OCBridge is to take into account the traffic demands between the source and destination regions of each OCS link. In this paper, we first review our OCBridge, and then in simulation, we evaluate the performance of our OCBridge by testing it in two typical OCS-based DCNs, including OpenScale and Helios. Under our OCBridge, we analyze the outstanding network throughput performance of the DCNs and investigate the communication distance of traffic demands. Finally, in experiment, we deploy our OCBridge to a small prototype of OpenScale and verify that our OCBridge is capable of accelerating the distributed computing applications compared with previous topology reconfiguration strategies.

<p> Due to rapidly growing cloud-based applications and services, data center networks handle huge traffic and they started receiving significant attention recently. In this article, we first review various trends in data center network architectures. Then we propose a novel hyperscale architecture named Transparent HyperX (TH) and compare it to existing real-world architectures. The TH concept is inspired by the conventional HyperX topology, but designed with a number of additional all-optical diagonal links that maintain pod-to-pod path cost below two hops and ensure more transparent connectivity between pods throughout the entire data center. This reduction in path cost not only results in lower latency, but also saves on the number of switches and transponders, which eventually reduces the power consumption. This architecture also offers high scalability and supports over 1 million servers using 100 radix switches. </p>

The explosive growth of data center (DC) traffic imposes unprecedented challenges on the current electrical switch-based data center networks (DCNs) with the bottleneck of limited bandwidth and high latency. Benefitting from transparency to the data rate and format, optical switching with theoretically infinite bandwidth could overcome the bandwidth bottleneck of electrical switching DCNs. However, DCNs normally deploy multitenant applications with a variety of DC traffic. It is hard to reconfigure the optical interconnections in real-time to provide adaptable bandwidth to the traffic with heterogeneous characteristics. Moreover, to improve the bandwidth utilization, statistical multiplexing is generally deployed in optical DCNs to forward the traffic flow in a time slot, which requires the network time to be precisely synchronized to all network nodes. For fast optical switches with a nanosecond switching configuration time, overall end node times must be synchronized at subnanosecond magnitude. In this paper, we propose and experimentally investigate a reconfigurable and picosecond-synchronized optical DCN (ReSAW) based on an arrayed waveguide grating router (AWGR) and the White Rabbit (WR) protocol. A scheduler based on a distributed field-programmable gate array is implemented in the proposed ReSAW to realize flexible wavelength configuration by controlling the fast laser array based on semiconductor optical amplifiers (SOAs) according to time slot and traffic priority. Moreover, the WR protocol is implemented in optical DCNs for what we believe is the first time to synchronize the time of the distributed top of racks (ToRs). The experimental demonstration validates that ReSAW achieves an average end-to-end latency of 317.44 ns and a precise synchronized time with an average 386 ps skew. When the load is 0.4, the packet loss after ReSAW reconfiguration is less than 1.83 × 10 − 6 , and the network latency is less than 1.73 µs. Based on the experimental parameters and results, the OMNeT++ simulation model is built to further verify the reconfigurability and scalability of the ReSAW network. Results show that the packet loss rate and latency performance increase 8.24% and 12.47%, respectively, at a load of 0.6 as the ReSAW network scales from 2560 to 40,960 servers compared to before the reconfiguration.

Optical switching based small-world data center network

Data Center Networks (DCNs) suffer from the congestions caused by unbalanced traffic distributions. Nevertheless, it is difficult to address such a challenge with the existent Ethernet-based DCN architecture. Wireless networking has been considered as a viable approach with a high potential to tackle the problem due to its flexibility. This paper presents Wireless Link Scheduling for Data Center Networks (WLS-DCN) to provide a feasible wireless DCN. More specifically, we propose a wireless DCN architecture as well as a scheduling mechanism. In our wireless scheduling, two different optimization objectives are considered, with one targeting the unbalanced traffic distribution and one maximizing the total network utility, under the constraints of limited wireless resources and co-channel interference. We propose two heuristics for the two problems and carry out extensive simulation study to validate the performance of our design. Our results demonstrate that WLSDCN can significantly improve the performance of DCN.

Advances in data intensive computing and high performance computing facilitate rapid scaling of data center networks, resulting in a growing body of research exploring new network architectures that enhance scalability, cost effectiveness and performance. Understanding the tradeoffs between these different network architectures could not only help data center operators improve deployments, but also assist system designers to optimize applications running on top of them. In this paper, we present a comparative analysis of several well known data center network architectures using important metrics, and present our results on different network topologies. We show the tradeoffs between these topologies and present implications on practical data center implementations.

Data centers (DCs), owing to the exponential growth of Internet services, have emerged as an irreplaceable and crucial infrastructure to power this ever-growing trend. A DC typically houses a large number of computing and storage nodes, interconnected by a specially designed network, namely, DC network (DCN). The DCN serves as a communication backbone and plays a pivotal role in optimizing DC operations. However, compared to the traditional network, the unique requirements in the DCN, for example, large scale, vast application diversity, high power density, and high reliability, pose significant challenges to its infrastructure and operations. We have observed from the premium publication venues (e.g., journals and system conferences) that increasing research efforts are being devoted to optimize the design and operations of the DCN. In this paper, we aim to present a systematic taxonomy and survey of recent research efforts on the DCN. Specifically, we propose to classify these research efforts into two areas: 1) DCN infrastructure and 2) DCN operations. For the former aspect, we review and compare the list of transmission technologies and network topologies used or proposed in the DCN infrastructure. For the latter aspect, we summarize the existing traffic control techniques in the DCN operations, and survey optimization methods to achieve diverse operational objectives, including high network utilization, fair bandwidth sharing, low service latency, low energy consumption, high resiliency, and etc., for efficient DC operations. We finally conclude this survey by envisioning a few open research opportunities in DCN infrastructure and operations.