AKAMAI WHITE PAPER
Network Function
Virtualization
NETWORK FUNCTION VIRTUALIZATION 1
ADVANTAGES OF CLOUD COMPUTING 1
CONTENT DELIVERY 2 HyperCache 2 Request Router 2 IP Streamer 2 Intercept Service 2 Analytics 2 Objects Store 2 Multi-Screen Video 3 Multi-Tenant CDN 3 Transparent Caching 3 PERFORMANCE 4
SERVICE DEVELOPMENT KIT (SDK) 6
Virtualized Platform 6
Management Framework 6
Service Composition 6
SUMMARY 6
Network Function Virtualization 1
Network Function Virtualization
Akamai’s pioneering work on Network Function Virtualization (NFV) – including
a proof-of-concept announced jointly with BT, HP and Intel – demonstrated the
viability of replacing hardware-based appliances with virtualized software running
on commodity servers (some streaming throughput results are included in this paper).
In addition to showcasing multiple virtualized services running side-by-side on a
single platform, the team conducted an in-depth analysis that shows a potential
to reduce the total cost of ownership by a third to a half. What’s harder to quantify,
but most exciting about the potential of NFV, is the opportunity it provides operators
to be more agile in deploying new services.
But the promise of NFV reaches far beyond a simple transition from hardware-based
appliances to VM-based appliances. The bigger story is the transition from a
server-based approach (be it virtual or physical) to a service-server-based approach. This is the
transition enabled by applying the principles of cloud computing to operator-provided
network services.
Advantages of Cloud Computing
The advantages of cloud computing are well understood: (1) the availability of elastic resources makes it easy to scale applications as demand increases; (2) a rich ecosystem of programming environments and foundational services lowers the barrier-to-entry for building new applications; and (3) the ability to amortize system administration across many users reduces the total cost of ownership.
Importantly, the ability to scale a service depends on more than abundant and cost-effective Virtual Machines (VMs) – it also leverages the state of the art in self-healing and self-balancing algorithms, without which an increase in resources does not translate into an increase in either availability or aggregate performance. Cloud computing typically implies data centers, but network operators – Telcos and MSOs that operate access networks – recognize that the same advantages apply to the network edge, albeit with an edge-specific twist. Extending the cloud to the network edge means deploying commodity servers in the operator’s regional PoPs and edge sites (e.g., PDN-GW, B-RAS and CMTS), virtualizing that hardware infrastructure and running network services across the resulting distributed cloud.
With respect to resource elasticity, being able to deploy network services in virtual machines running on commodity processors instead of deploying purpose-built appliances means reducing the time-to-market for introducing new services, as well as making it easy to re-provision the resources allocated to existing services as demand dictates. With respect to the software ecosystem, being able to leverage general-purpose building block services instead of integrating stove-piped applications from a limited set of vendors makes it easier to introduce incremental value-added functionality into the network, and as a consequence, opens the space for innovation by third-party service providers. With respect to reducing operating costs, extending the cloud into the access network introduces both a risk and an opportunity. Since network operators are both cloud users (they introduce and operate applications running on the cloud platform) and cloud providers (they own and operate the underlying network/computing infrastructure), the risk is that a proliferation of services will introduce a proliferation of OSS/BSS procedures. At the same time, however there is an opportunity to introduce a unified approach to OSS/BSS across a wide set of services.
Content Delivery
What applications are best delivered at the network edge, or asked another way, what’s the killer app that is pulling the cloud out of the data center and into routing centers and edge sites of the access networks? In two words: content delivery. The explosion of video is causing operators to deploy caches deeper in their networks; these caches are best deployed on virtualized commodity hardware; and once deployed, this same hardware is in position to deliver a host of other network services, each running in its own virtual machine (VM).
This is exactly the service delivery model used by Akamai’s Aura Lumen CDN, which supports the following set of building block services:
• HyperCache – The core caching service that implements scalable caching sites and a network-wide caching hierarchy.
• Request Router – A service that routes requests from end users to the service node that will deliver content to that
particular user.
• IP Streamer – A service that streams cached content to end users using legacy streaming protocols (e.g., RTMP).
• Intercept Service – A service that intercept requests for over-the-top (OTT) content and redirects it into the caching hierarchy.
• Analytics – A service that collects, aggregates and analyzes traffic that flows through the caching hierarchy.
• Object Store – A service that ingests content from a provider’s Content Management System (CMS) into the caching
hierarchy.
Network Function Virtualization 3
HyperCache
Request Router
Analytics
Internet Str
eamer
Inter
cept Service
VoD Asset
Manager
Virtual Machine Monitor
Commodity Hardware
These building-block services run in VMs on commodity servers, where a Linux kernel provides the underlying virtualization machinery. A centralized management suite is used to provision VMs across the network, configure and manage services running in those VMs, and proactively monitor service behavior.
The network operator then configures these building-block services in different combinations to implement a set of applications (solutions). For example:
• Multi-Screen Video – Accelerate and scale the delivery of operator-owned video to the Internet devices of the
operator’s broadband subscribers. Implemented by a combination of
(HyperCache + Request Router + Analytics)
• Multi-Tenant CDN – A revenue-generating service offered to the operator’s business customers, allowing them
to accelerate and scale the delivery of their content to the operator’s broadband subscribers. Implemented by a combination of
(HyperCache + Request Router + Analytics)
• Transparent Caching – A network optimization (cost reduction) technique, whereby the operator caches over-the-top
(OTT) content (e.g., YouTube), and then delivers it to the operator’s broadband subscribers. Implemented by a combination of
The Aura Lumen model of constructing content delivery solutions from building-block services only works because the building blocks are general-purpose – they work across diverse usage scenarios.
HyperCache supports a wide range of object types equally well — both small and large files (the former implies the need for high transaction rates and the latter implies the need to sustained high bandwidths); both progressive downloads and HTTP adaptive streaming (the later implies request routing needs to scale to support hundreds of millions of objects); and both live and on-demand streaming (the former implies the need for low-latency, cut-through caches). The secret is that HyperCache uses the best practices in scaling through software, including self-healing and self-balancing algorithms. Request Router scales to support HTTP-AS and provides operators with a rich policy language to specify how user requests are routed. For example, it is not only able to route user requests to the best edge cache within a CDN but also to route requests to the best available CDN.
The services collectively accommodate ingesting content from multiple sources. Request Router augments the HyperCache to acquire content from peer CDNs, global CDNs and enterprise customers and the Intercept Service augments HyperCache to acquire content from Over-the-Top content aggregators. HyperCache, in turn, is able to support this range of content sources because it supports dynamic content acquisition and on-demand content placement.
Performance
To evaluate the performance of an NFV-based solution, BT, Akamai, Ineoquest, Spirent and HP have jointly demonstrated HyperCache (AHC) co-located on the same HP BL460 G8 blade server as Ineoquest’s Adaptive Streaming Monitor (ASM) in support of an IPTV application. Both AHC and ASM run in virtual machines, on top of VMware’s ESXi hypervisor. The AHC virtual machine is allocated 6 vCPUs, 28GB of RAM, 750GB or SSD, and is connected to a 10Gbps NIC.
External load was put on the system using an external Spirent Avalanche C1, which ran three test suites measuring streaming throughput as the number of users is ramped up over time: (1) progressive download (PDL), (2) adaptive bit rate (ABR), and (3) a mix of PDL and ABR. All three delivered content from the AHC cache. The key results are as follows. First, AHC was able to deliver PDL content from the cache at 8.5 – 9.0Gbps. At that rate, the CPU is running at an average utilization of 60%. 1E7 9000000 8000000 7000000 6000000 5000000 4000000 3000000 2000000 1000000 0 0 100 200 300 400 Eapsed Time (Seconds)
Incoming + SimUsers Incoming Traffic (kbps) 2013/01/17 10:34:23 SimUsers Animated 2013/01/17 10:34:23
Network Function Virtualization 5 1E7 9000000 8000000 7000000 6000000 5000000 4000000 3000000 2000000 1000000 0 0 100 200 300 400 Traffic Incoming Outgoing 500 600 Eapsed Time (Seconds)
Second, an ABR test using HLS (HTTP Live Streaming) with churn (viewers coming and going and rates upshifting and downshifting), results in AHC delivering a peak of 9Gbps, with an average rate of 7Gbps. We conclude that AHC can safely support 7 – 8Gbps without adversely affecting end user video quality.
1E7 9000000 8000000 7000000 6000000 5000000 4000000 3000000 2000000 1000000 0 0 100 200 300 400 Incoming 500 600
Eapsed Time (Seconds)
Incoming Traffic (kbps) 2013/01/17 15:43:10
Third, with a mix of ABR (specifically HLS) and PDL, and PDL streams throttled to 600Kbps, the virtualized AHC delivers an aggregate load for all PDL users of 5.2Gbps, with the peak rate achieved for the ABR/PDL traffic mix reaching 8.6Gbps.
Service Development Kit (SDK)
An alternative view of the Aura Lumen CDN is that it defines a service development kit (SDK) for the operator’s network, and as such, effectively supports the Platform-as-a-Service (PaaS) model of cloud computing. The Aura Lumen SDK consists of three main elements:
• Virtualized Platform – Services run in isolated virtual machines (VMs) on commodity servers deployed throughout the operator’s network. Any service that runs on any variant of Linux can run on the Aura Lumen SDK and enjoy I/O performance (to both storage and the network) as good as native Linux. Moreover, each VM provides full security, fault and resource isolation.
• Management Framework – The Aura Lumen SDK provides a unified OSS/BSS across all services. This includes
the ability to provision the service (map them onto a network of VMs), configure and control the service in response to customer requests, proactively monitor the service’s operational behavior, and collect usage data suitable for both billing and analytics. The SDK may also lower the barrier-to-entry for developing new services through a set of management plug-ins.
• Service Composition – The current service catalogue includes three anchor services that new services can leverage
through well-defined interfaces. The first anchor service is HyperCache, which provides services with access to cached content. The second anchor service is Request Router, which provides services with the ability to route user requests to the best service access point. The third anchor service is the Intercept Service, which can be used to intercept targeted packet flows.
The real power of the SDK is in the new services and applications it enables. For example, Dynamic Site Acceleration (DSA) can readily be developed and deployed by factoring out dynamic page construction and placing it in a VM on the very same edge nodes that are caching the static images that appear in those pages. This will be especially important for mobile networks, where reducing traffic over the wireless link is critically important. Beyond generic DSA, the edge is a natural place to enhance the end-user experience. For example, social networking applications could benefit from edge acceleration.
Network-level services already running at the edge can also benefit from being ported to virtualized commodity processors. This seems particularly relevant to edge PDN-GW, B-RAS and CMTS sites, where the opportunity to manage and customize subscriber sessions is almost limitless – mobility, locality, security and quality of service.
Summary
In summary, the Aura Lumen CDN is extensible, which brings many of the advantages of data-center based clouds to the operator’s network. Through the use of virtualization, the underlying computing resources can be rapidly provisioned to supporting changing workloads. By exploiting a rich software ecosystem, the time-to-market for rolling out new applications may be dramatically reduced. By unifying OSS/BSS process in an integrated management framework, the total cost of ownership is likely to decrease. Taken as a whole, this strategy has the ability to deliver on the promise of NFV.
©2015 Akamai Technologies, Inc. All Rights Reserved. Reproduction in whole or in part in any form or medium without express written permission is prohibited. Akamai and the Akamai wave logo are registered trademarks. Other trademarks contained herein are the property of their respective owners. Akamai believes that the information in this publication is accurate as of its publication date; such information is subject to change without notice. Published 05/15.
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