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

Understanding the characteristics of Internet traffic and designing an efficient RaptorQ-based data transport protocol for modern data centres

This thesis is the amalgamation of research on efficient data transport protocols for data centres and a comprehensive and systematic study of Internet traffic, which came as a result of the need to understand traffic patterns and workloads in modern computer networks. The first part of the thesis is on the development of efficient data transport pro- tocols for data centres. We study modern data transport protocols for data centres through large scale simulations using the OMNeT++ simulator. We developed and experimented with an OMNeT++ model of NDP. This has led to the identification of limitations of the state of the art and the formulation of research questions with respect to data transport protocols for modern data centres. The developed model includes an implementation of a Fat-tree topology and per-packet ECMP load bal- ancing. We discuss how we integrated the model with the INET Framework and validated it by running various experiments that test different model parameters and components. This work revealed limitations of NDP with respect to efficient one-to-many and many-to-one communication in data centres, which led to the de- velopment of SCDP, a novel and general-purpose data transport protocol for data centres that, in contrast to all other protocols proposed to date, natively supports one-to-many and many-to-one data communication, which is extremely common in modern data centres. SCDP does so without compromising on efficiency for short and long unicast flows. SCDP achieves this by integrating RaptorQ codes with receiver-driven data transport, in-network packet trimming and Multi-Level Feed- back Queuing (MLFQ); (1) RaptorQ codes enable efficient one-to-many and many- to-one data transport; (2) on top of RaptorQ codes, receiver- driven flow control, in combination with in-network packet trimming, enable efficient usage of network re- sources as well as multi-path transport and packet spraying for all transport modes. Incast and Outcast are eliminated; (3) the systematic nature of RaptorQ codes, in combination with MLFQ, enable fast, decoding-free completion of short flows. We extensively evaluated SCDP in a wide range of simulated scenarios with realistic data centre workloads. For one-to-many and many-to-one transport sessions, SCDP performs significantly better than NDP. For short and long unicast flows, SCDP performs equally well or better compared to NDP. In the second part of the thesis, we extensively study Internet traffic. Getting good statistical models of traffic on network links is a well-known, often-studied problem. A lot of attention has been given to correlation patterns and flow duration. The distribution of the amount of traffic per unit time is an equally important but less studied problem. We study a large number of traffic traces from many different networks including academic, commercial and residential networks using state-of-the-art statistical techniques. We show that the log-normal distribution is a better fit than the Gaussian distribution. We also investigate a second, heavy- tailed distribution and show that its performance is better than Gaussian but worse than log-normal. We examine anomalous traces which are a poor fit for all tested distributions and show that this is often due to traffic outages or links that hit maximum capacity. Stationarity tests showed that the traffic is stationary at some range of aggregation times. We demonstrate the utility of the log-normal distribution in two contexts: predicting the proportion of time traffic will exceed a given level (for link capacity estimation) and predicting 95th percentile pricing. We also show the log-normal distribution is a better predictor than Gaussian orWeibull distributions

Optimizing Communication for Massively Parallel Processing

The current trends in high performance computing show that large machines with tens of thousands of processors will soon be readily available. The IBM Bluegene-L machine with 128k processors (which is currently being deployed) is an important step in this direction. In this scenario, it is going to be a significant burden for the programmer to manually scale his applications. This task of scaling involves addressing issues like load-imbalance and communication overhead. In this thesis, we explore several communication optimizations to help parallel applications to easily scale on a large number of processors. We also present automatic runtime techniques to relieve the programmer from the burden of optimizing communication in his applications. This thesis explores processor virtualization to improve communication performance in applications. With processor virtualization, the computation is mapped to virtual processors (VPs). After one VP has finished computation and is waiting for responses to its messages, another VP can compute, thus overlapping communication with computation. This overlap is only effective if the processor overhead of the communication operation is a small fraction of the total communication time. Fortunately, with network interfaces having co-processors, this happens to be true and processor virtualization has a natural advantage on such interconnects. The communication optimizations we present in this thesis, are motivated by applications such as NAMD (a classical molecular dynamics application) and CPAIMD (a quantum chemistry application). Applications like NAMD and CPAIMD consume a fair share of the time available on supercomputers. So, improving their performance would be of great value. We have successfully scaled NAMD to 1TF of peak performance on 3000 processors of PSC Lemieux, using the techniques presented in this thesis. We study both point-to-point communication and collective communication (specifically all-to-all communication). On a large number of processors all-to-all communication can take several milli-seconds to finish. With synchronous collectives defined in MPI, the processor idles while the collective messages are in flight. Therefore, we demonstrate an asynchronous collective communication framework, to let the CPU compute while the all-to-all messages are in flight. We also show that the best strategy for all-to-all communication depends on the message size, number of processors and other dynamic parameters. This suggests that these parameters can be observed at runtime and used to choose the optimal strategy for all-to-all communication. In this thesis, we demonstrate adaptive strategy switching for all-to-all communication. The communication optimization framework presented in this thesis, has been designed to optimize communication in the context of processor virtualization and dynamic migrating objects. We present the streaming strategy to optimize fine grained object-to-object communication. In this thesis, we motivate the need for hardware collectives, as processor based collectives can be delayed by intermediate that processors busy with computation. We explore a next generation interconnect that supports collectives in the switching hardware. We show the performance gains of hardware collectives through synthetic benchmarks

On energy consumption of switch-centric data center networks

Data center network (DCN) is the core of cloud computing and accounts for 40% energy spend when compared to cooling system, power distribution and conversion of the whole data center (DC) facility. It is essential to reduce the energy consumption of DCN to esnure energy-efficient (green) data center can be achieved. An analysis of DC performance and efficiency emphasizing the effect of bandwidth provisioning and throughput on energy proportionality of two most common switch-centric DCN topologies: three-tier (3T) and fat tree (FT) based on the amount of actual energy that is turned into computing power are presented. Energy consumption of switch-centric DCNs by realistic simulations is analyzed using GreenCloud simulator. Power related metrics were derived and adapted for the information technology equipment (ITE) processes within the DCN. These metrics are acknowledged as subset of the major metrics of power usage effectiveness (PUE) and data center infrastructure efficiency (DCIE), known to DCs. This study suggests that despite in overall FT consumes more energy, it spends less energy for transmission of a single bit of information, outperforming 3T

Exploring Adaptive Implementation of On-Chip Networks

As technology geometries have shrunk to the deep submicron regime, the communication delay and power consumption of global interconnections in high performance Multi- Processor Systems-on-Chip (MPSoCs) are becoming a major bottleneck. The Network-on- Chip (NoC) architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication issues such as performance limitations of long interconnects and integration of large number of Processing Elements (PEs) on a chip. The choice of routing protocol and NoC structure can have a significant impact on performance and power consumption in on-chip networks. In addition, building a high performance, area and energy efficient on-chip network for multicore architectures requires a novel on-chip router allowing a larger network to be integrated on a single die with reduced power consumption. On top of that, network interfaces are employed to decouple computation resources from communication resources, to provide the synchronization between them, and to achieve backward compatibility with existing IP cores. Three adaptive routing algorithms are presented as a part of this thesis. The first presented routing protocol is a congestion-aware adaptive routing algorithm for 2D mesh NoCs which does not support multicast (one-to-many) traffic while the other two protocols are adaptive routing models supporting both unicast (one-to-one) and multicast traffic. A streamlined on-chip router architecture is also presented for avoiding congested areas in 2D mesh NoCs via employing efficient input and output selection. The output selection utilizes an adaptive routing algorithm based on the congestion condition of neighboring routers while the input selection allows packets to be serviced from each input port according to its congestion level. Moreover, in order to increase memory parallelism and bring compatibility with existing IP cores in network-based multiprocessor architectures, adaptive network interface architectures are presented to use multiple SDRAMs which can be accessed simultaneously. In addition, a smart memory controller is integrated in the adaptive network interface to improve the memory utilization and reduce both memory and network latencies. Three Dimensional Integrated Circuits (3D ICs) have been emerging as a viable candidate to achieve better performance and package density as compared to traditional 2D ICs. In addition, combining the benefits of 3D IC and NoC schemes provides a significant performance gain for 3D architectures. In recent years, inter-layer communication across multiple stacked layers (vertical channel) has attracted a lot of interest. In this thesis, a novel adaptive pipeline bus structure is proposed for inter-layer communication to improve the performance by reducing the delay and complexity of traditional bus arbitration. In addition, two mesh-based topologies for 3D architectures are also introduced to mitigate the inter-layer footprint and power dissipation on each layer with a small performance penalty.Siirretty Doriast

Wireless Communication in Data Centers: A Survey

Data centers (DCs) is becoming increasingly an integral part of the computing infrastructures of most enterprises. Therefore, the concept of DC networks (DCNs) is receiving an increased attention in the network research community. Most DCNs deployed today can be classified as wired DCNs as copper and optical fiber cables are used for intra- and inter-rack connections in the network. Despite recent advances, wired DCNs face two inevitable problems; cabling complexity and hotspots. To address these problems, recent research works suggest the incorporation of wireless communication technology into DCNs. Wireless links can be used to either augment conventional wired DCNs, or to realize a pure wireless DCN. As the design spectrum of DCs broadens, so does the need for a clear classification to differentiate various design options. In this paper, we analyze the free space optical (FSO) communication and the 60 GHz radio frequency (RF), the two key candidate technologies for implementing wireless links in DCNs. We present a generic classification scheme that can be used to classify current and future DCNs based on the communication technology used in the network. The proposed classification is then used to review and summarize major research in this area. We also discuss open questions and future research directions in the area of wireless DCs