Datacenter Traffic Control: Understanding Techniques and Trade-offs

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

FatPaths: Routing in Supercomputers and Data Centers when Shortest Paths Fall Short

We introduce FatPaths: a simple, generic, and robust routing architecture that enables state-of-the-art low-diameter topologies such as Slim Fly to achieve unprecedented performance. FatPaths targets Ethernet stacks in both HPC supercomputers as well as cloud data centers and clusters. FatPaths exposes and exploits the rich ("fat") diversity of both minimal and non-minimal paths for high-performance multi-pathing. Moreover, FatPaths uses a redesigned "purified" transport layer that removes virtually all TCP performance issues (e.g., the slow start), and incorporates flowlet switching, a technique used to prevent packet reordering in TCP networks, to enable very simple and effective load balancing. Our design enables recent low-diameter topologies to outperform powerful Clos designs, achieving 15% higher net throughput at 2x lower latency for comparable cost. FatPaths will significantly accelerate Ethernet clusters that form more than 50% of the Top500 list and it may become a standard routing scheme for modern topologies

Power-Aware Datacenter Networking and Optimization

Present-day datacenter networks (DCNs) are designed to achieve full bisection bandwidth in order to provide high network throughput and server agility. However, the average utilization of typical DCN infrastructure is below 10% for significant time intervals. As a result, energy is wasted during these periods. In this thesis we analyze traffic behavior of datacenter networks using traces as well as simulated models. Based on the insight developed, we present techniques to reduce energy waste by making energy use scale linearly with load. The solutions developed are analyzed via simulations, formal analysis, and prototyping. The impact of our work is significant because the energy savings we obtain for networking infrastructure of DCNs are near optimal. A key finding of our traffic analysis is that network switch ports within the DCN are grossly under-utilized. Therefore, the first solution we study is to modify the routing within the network to force most traffic to the smallest of switches. This increases the hop count for the traffic but enables the powering off of many switch ports. The exact extent of energy savings is derived and validated using simulations. An alternative strategy we explore in this context is to replace about half the switches with fewer switches that have higher port density. This has the effect of enabling even greater traffic consolidation, thus enabling even more ports to sleep. Finally, we explore a third approach in which we begin with end-to-end traffic models and incrementally build a DCN topology that is optimized for that model. In other words, the network topology is optimized for the potential use of the datacenter. This approach makes sense because, as other researchers have observed, the traffic in a datacenter is heavily dependent on the primary use of the datacenter. A second line of research we undertake is to merge traffic in the analog domain prior to feeding it to switches. This is accomplished by use of a passive device we call a merge network. Using a merge network enables us to attain linear scaling of energy use with load regardless of datacenter traffic models. The challenge in using such a device is that layer 2 and layer 3 protocols require a one-to-one mapping of hardware addresses to IP (Internet Protocol) addresses. We overcome this problem by building a software shim layer that hides the fact that traffic is being merged. In order to validate the idea of a merge network, we build a simple mere network for gigabit optical interfaces and demonstrate correct operation at line speeds of layer 2 and layer 3 protocols. We also conducted measurements to study how traffic gets mixed in the merge network prior to being fed to the switch. We also show that the merge network uses only a fraction of a watt of power, which makes this a very attractive solution for energy efficiency. In this research we have developed solutions that enable linear scaling of energy with load in datacenter networks. The different techniques developed have been analyzed via modeling and simulations as well as prototyping. We believe that these solutions can be easily incorporated into future DCNs with little effort

A survey on architectures and energy efficiency in Data Center Networks

Data Center Networks (DCNs) are attracting growing interest from both academia and industry to keep pace with the exponential growth in cloud computing and enterprise networks. Modern DCNs are facing two main challenges of scalability and cost-effectiveness. The architecture of a DCN directly impacts on its scalability, while its cost is largely driven by its power consumption. In this paper, we conduct a detailed survey of the most recent advances and research activities in DCNs, with a special focus on the architectural evolution of DCNs and their energy efficiency. The paper provides a qualitative categorization of existing DCN architectures into switch-centric and server-centric topologies as well as their design technologies. Energy efficiency in data centers is discussed in details with survey of existing techniques in energy savings, green data centers and renewable energy approaches. Finally, we outline potential future research directions in DCNs

Reducing the Cost of Operating a Datacenter Network

Datacenters are a significant capital expense for many enterprises. Yet, they are difficult to manage and are hard to design and maintain. The initial design of a datacenter network tends to follow vendor guidelines, but subsequent upgrades and expansions to it are mostly ad hoc, with equipment being upgraded piecemeal after its amortization period runs out and equipment acquisition is tied to budget cycles rather than changes in workload. These networks are also brittle and inflexible. They tend to be manually managed, and cannot perform dynamic traffic engineering. The high-level goal of this dissertation is to reduce the total cost of owning a datacenter by improving its network. To achieve this, we make the following contributions. First, we develop an automated, theoretically well-founded approach to planning cost-effective datacenter upgrades and expansions. Second, we propose a scalable traffic management framework for datacenter networks. Together, we show that these contributions can significantly reduce the cost of operating a datacenter network. To design cost-effective network topologies, especially as the network expands over time, updated equipment must coexist with legacy equipment, which makes the network heterogeneous. However, heterogeneous high-performance network designs are not well understood. Our first step, therefore, is to develop the theory of heterogeneous Clos topologies. Using our theory, we propose an optimization framework, called LEGUP, which designs a heterogeneous Clos network to implement in a new or legacy datacenter. Although effective, LEGUP imposes a certain amount of structure on the network. To deal with situations when this is infeasible, our second contribution is a framework, called REWIRE, which using optimization to design unstructured DCN topologies. Our results indicate that these unstructured topologies have up to 100-500\% more bisection bandwidth than a fat-tree for the same dollar cost. Our third contribution is two frameworks for datacenter network traffic engineering. Because of the multiplicity of end-to-end paths in DCN fabrics, such as Clos networks and the topologies designed by REWIRE, careful traffic engineering is needed to maximize throughput. This requires timely detection of elephant flows---flows that carry large amount of data---and management of those flows. Previously proposed approaches incur high monitoring overheads, consume significant switch resources, or have long detection times. We make two proposals for elephant flow detection. First, in the Mahout framework, we suggest that such flows be detected by observing the end hosts' socket buffers, which provide efficient visibility of flow behavior. Second, in the DevoFlow framework, we add efficient stats-collection mechanisms to network switches. Using simulations and experiments, we show that these frameworks reduce traffic engineering overheads by at least an order of magnitude while still providing near-optimal performance

Transition to SDN is HARMLESS: Hybrid ARchitecture for Migrating Legacy Ethernet Switches to SDN

Software-Defined Networking (SDN) offers a new way to operate, manage, and deploy communication networks and to overcome many long-standing problems of legacy networking. However, widespread SDN adoption has not occurred yet due to the lack of a viable incremental deployment path and the relatively immature present state of SDN-capable devices on the market. While continuously evolving software switches may alleviate the operational issues of commercial hardware-based SDN offerings, namely lagging standards-compliance, performance regressions, and poor scaling, they fail to match the cost-efficiency and port density. In this paper, we propose HARMLESS, a new SDN switch design that seamlessly adds SDN capability to legacy network gear, by emulating the OpenFlow switch OS in a separate software switch component. This way, HARMLESS enables a quick and easy leap into SDN, combining the rapid innovation and upgrade cycles of software switches with the port density and cost-efficiency of hardware-based appliances into a fully dataplane-transparent and vendor-neutral solution. HARMLESS incurs an order of magnitude smaller initial expenditure for an SDN deployment than existing turnkey vendor SDN solutions while, at the same time, yields matching, or even better, data plane performance for smaller enterprises

Improving multipath routing of TCP flows by network exploration

Ethernet switched networks are widely used in enterprise and data center networks. However, they have some drawbacks, mainly that, to prevent loops, they cannot take advantage of multipath topologies to balance traffic. Several multipath routing proposals use link-state protocols and Equal Cost Multi-Path routing (ECMP) to distribute the load over multiple paths. But, these proposals are complex and prone to flow collisions that may degrade performance. This paper studies TCP-Path, a protocol that employs a different approach. It uses a distributed network exploration mechanism based on broadcasting the TCPSYN packet to identify and select the fastest available path to the destination host, on the fly. Our evaluation shows that it improves on ECMP by up to 70% in terms of throughput for elephant flows and by up to 60% in terms of flow completion time for mouse flows. Indeed, network exploration offers a better, yet simple alternative to ECMP-based solutions for multipath topologies. In addition, we also study TCP-Path for elephant flows (TFE), which restricts TCP-Path application to elephant flows to reduce the exploration broadcast overhead and the size of forwarding tables, thus improving its scalability. Although elephant flows represent a small fraction (about 5%) of total flows, they have a major impact on overall performance, as we show in our evaluation. TFE reduces both the overhead incurred during path setup and the size of the forwarding tables by a factor of almost 20. Moreover, it achieves results close to those obtained by TCPPath for elephant flows, especially when working with high loads, and yields significant improvements for all types of flow at medium and high load levels.Comunidad de MadridUniversidad de Alcal