63 research outputs found
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
Composable architecture for rack scale big data computing
The rapid growth of cloud computing, both in terms of the spectrum and volume of cloud workloads, necessitate re-visiting the traditional rack-mountable servers based datacenter design. Next generation datacenters need to offer enhanced support for: (i) fast changing system configuration requirements due to workload constraints, (ii) timely adoption of emerging hardware technologies, and (iii) maximal sharing of systems and subsystems in order to lower costs. Disaggregated datacenters, constructed as a collection of individual resources such as CPU, memory, disks etc., and composed into workload execution units on demand, are an interesting new trend that can address the above challenges. In this paper, we demonstrated the feasibility of composable systems through building a rack scale composable system prototype using PCIe switch. Through empirical approaches, we develop assessment of the opportunities and challenges for leveraging the composable architecture for rack scale cloud datacenters with a focus on big data and NoSQL workloads. In particular, we compare and contrast the programming models that can be used to access the composable resources, and developed the implications for the network and resource provisioning and management for rack scale architecture
Live media production: multicast optimization and visibility for clos fabric in media data centers
Media production data centers are undergoing a major architectural shift to introduce digitization concepts to media creation and media processing workflows. Content companies such as NBC Universal, CBS/Viacom and Disney are modernizing their workflows to take advantage of the flexibility of IP and virtualization.
In these new environments, multicast is utilized to provide point-to-multi-point communications. In order to build point-to-multi-point trees, Multicast has an established set of control protocols such as IGMP and PIM. The existing multicast protocols do not optimize multicast tree formation for maximizing network throughput which lead to decreased fabric utilization and decreased total number of admitted flows. In addition, existing multicast protocols are not bandwidth-aware and could cause links to over-subscribe leading to packet loss and lower video quality.
TV production traffic patterns are unique due to ultra high bandwidth requirements and high sensitivity to packet loss that leads to video impairments. In such environments, operators need monitoring tools that are able to proactively monitor video flows and provide actionable alerts. Existing network monitoring tools are inadequate because they are reactive by design and perform generic monitoring of flows with no insights into video domain.
The first part of this dissertation includes a design and implementation of a novel Intelligent Rendezvous Point algorithm iRP for bandwidth-aware multicast routing in media DC fabrics. iRP utilizes a controller-based architecture to optimize multicast tree formation and to increase bandwidth availability in the fabric. The system offers up to 50\% increase in fabric capacity to handle multicast flows passing through the fabric.
In the second part of this dissertation, DiRP algorithm is presented. DiRP is based on a distributed decision-making approach to achieve multicast tree capacity optimization while maintaining low multicast tree setup time. DiRP algorithm is tested using commercially available data center switches. DiRP algorithm offers substantially lower path setup time compared to centralized systems while maintaining bandwidth awareness when setting up the fabric.
The third part of this dissertation studies the utilization of machine learning algorithms to improve on multicast efficiency in the fabric. The work includes implementation and testing of LiRP algorithm to increase iRP\u27s fabric efficiency by implementing k-fold cross validation method to predict future multicast group memberships for time-series analysis. Testing results confirm that LiRP system increases the efficiency of iRP by up to 40\% through prediction of multicast group memberships with online arrival.
In the fourth part of this dissertation, The problem of live video monitoring is studied. Existing network monitoring tools are either reactive by design or perform generic monitoring of flows with no insights into video domain. MediaFlow is a robust system for active network monitoring and reporting of video quality for thousands of flows simultaneously using a fraction of the cost of traditional monitoring solutions. MediaFlow is able to detect and report on integrity of video flows at a granularity of 100 mSec at line rate for thousands of flows. The system increases video monitoring scale by a thousand-fold compared to edge monitoring solutions
SDNsec: Forwarding Accountability for the SDN Data Plane
SDN promises to make networks more flexible, programmable, and easier to
manage. Inherent security problems in SDN today, however, pose a threat to the
promised benefits. First, the network operator lacks tools to proactively
ensure that policies will be followed or to reactively inspect the behavior of
the network. Second, the distributed nature of state updates at the data plane
leads to inconsistent network behavior during reconfigurations. Third, the
large flow space makes the data plane susceptible to state exhaustion attacks.
This paper presents SDNsec, an SDN security extension that provides
forwarding accountability for the SDN data plane. Forwarding rules are encoded
in the packet, ensuring consistent network behavior during reconfigurations and
limiting state exhaustion attacks due to table lookups. Symmetric-key
cryptography is used to protect the integrity of the forwarding rules and
enforce them at each switch. A complementary path validation mechanism allows
the controller to reactively examine the actual path taken by the packets.
Furthermore, we present mechanisms for secure link-failure recovery and
multicast/broadcast forwarding.Comment: 14 page
Green spine switch management for datacenter networks
Energy consumption for datacenter has grown significantly and the trend is still growing due to the increasing popularity of cloud computing. Datacenter networks (DCNs), however, are starting to consume a greater portion of overall energy in comparison to servers used in datacenters due to advanced virtualization techniques. On the other hand, devices in a DCN often remain under-utilized. There are various DCN architectures. This paper proposes an approach called Green Spine Switch Management System (GSSMS) for Spine-Leaf topology based DCNs. The objective of the approach is to reduce energy consumption used by the network for a Spine-Leaf topology-based datacenter. The primary idea of GSSMS is to monitor the dynamic workload and only keep Spine switches that are necessary for handling the current network traffic. We have developed an adaptive management system to control the number of Spine switches in a Spine-Leaf DCN for efficient energy consumption. Further, we hav
Optical Technologies and Control Methods for Scalable Data Centre Networks
Attributing to the increasing adoption of cloud services, video services and associated machine learning applications, the traffic demand inside data centers is increasing exponentially, which necessitates an innovated networking infrastructure with high scalability and cost-efficiency. As a promising candidate to provide high capacity, low latency, cost-effective and scalable interconnections, optical technologies have been introduced to data center networks (DCNs) for approximately a decade. To further improve the DCN performance to meet the increasing traffic demand by using photonic technologies, two current trends are a)increasing the bandwidth density of the transmission links and b) maximizing IT and network resources utilization through disaggregated topologies and architectures. Therefore, this PhD thesis focuses on introducing and applying advanced and efficient technologies in these two fields to DCNs to improve their performance. On the one hand, at the link level, since the traditional single-mode fiber (SMF) solutions based on wavelength division multiplexing (WDM) over C+L band may fall short in satisfying the capacity, front panel density, power consumption, and cost requirements of high-performance DCNs, a space division multiplexing (SDM) based DCN using homogeneous multi-core fibers (MCFs) is proposed.With the exploited bi-directional model and proposed spectrum allocation algorithms, the proposed DCN shows great benefits over the SMF solution in terms of network capacity and spatial efficiency. In the meanwhile, it is found that the inter-core crosstalk (IC-XT) between the adjacent cores inside the MCF is dynamic rather than static, therefore, the behaviour of the IC-XT is experimentally investigated under different transmission conditions. On the other hand, an optically disaggregated DCN is developed and to ensure the performance of it, different architectures, topologies, resource routing and allocation algorithms are proposed and compared. Compared to the traditional server-based DCN, the resource utilization, scalability and the cost-efficiency are significantly improved
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