ONOS is an open source distributed network operating system for software defined networking. It provides a global network view through a distributed architecture and network graph abstraction. Key features include high availability through fault tolerance using a distributed registry for control isolation, and scalability through a simple scale-out design where each instance is responsible for building and maintaining part of the network graph.
Tech Talk: ONOS- A Distributed SDN Network Operating Systemnvirters
This event takes us to the cusp of Distributed Software Development and SDN Controllers. We will be hosting Madan and Brian who have been involved in the architecture and development of ONOS (Open Network Operating System).
Synopsis
ONOS is a distributed SDN network operating system architected to provide performance, scale-out, resiliency, and well-defined northbound and southbound abstractions. Madan and Brian, both from ON.Lab, will start the talk with a deep-dive into ONOS architecture, including the key technical challenges that were solved to build this platform. They will also walk us through a live demo of building a SDN application on ONOS.
Details:
ONOS Architecture
ONOS Abstractions and Modularity
ONOS Distributed architecture
ONOS APIs and their usage
Live demo- Building a SDN app on ONOS
Speaker Bios
Madan Jampani, Distributed Systems Architect, ONOS
Madan is Distributed Systems Architect at ON.Lab focusing on the core distributed systems problems for ONOS. Prior to joining ON.Lab in Sep 2014, Madan worked at Amazon for around 10 years. At Amazon, Madan was instrumental in building several key technologies ranging from Amazon retail ordering systems, distributed data stores and shared compute clusters for running large-scale data processing and machine learning workloads.
Brian O’Connor, Lead Developer, ONOS
Brian is the ONOS Application Intent Framework lead and a core developer at ON.Lab, working on ONOS and Mininet. Brian O’Connor received Bachelor’s and Master’s degrees in Computer Science from Stanford University. At Stanford, he helped develop “An Introduction to Computer Networking,” one of Stanford’s first MOOCs (Massively Open Online Courses).
ABOUT ON.LAB and ONOS
Open Networking Lab (ON.Lab) is a non-profit organization founded by SDN inventors and leaders from Stanford University and UC Berkeley to foster an open source community for developing tools and platforms to realize the full potential of SDN. ON.Lab brings innovative ideas from leading edge research and delivers high quality open source platforms on which members of its ecosystem and the industry can build real products and solutions.
ONOS, a SDN network operating system for service provider and mission critical networks, was open sourced on Dec 5th, 2014. ONOS delivers a highly available, scalable SDN control plane featuring northbound and southbound abstractions and interfaces for a diversity of management, control, service applications and network devices. ONOS ecosystem comprises of ON.Lab, organizations who are funding and contributing to the ONOS initiative including AT&T, NTT Communications, SK Telecom, Ciena, Cisco, Ericsson, Fujitsu, Huawei, Intel, NEC; members who are collaborating and contributing to ONOS include ONF, Infoblox, SRI, Internet2, Happiest Minds, CNIT, Black Duck, Create-Net and the broader ONOS community. Learn how you can get involved with ONOS at onosproject.org.
ONOS: Open Network Operating System. An Open-Source Distributed SDN Operating...ON.LAB
ONOS
Open Network Operating System
An Open-Source Distributed SDN OS
Pankaj Berde, Jonathan Hart, Masayoshi Kobayashi, Pavlin Radoslavov, Pingping Lin, Rachel Sverdlov, Suibin Zhang, William Snow, Guru Parulkar
Tech Talk: ONOS- A Distributed SDN Network Operating Systemnvirters
This event takes us to the cusp of Distributed Software Development and SDN Controllers. We will be hosting Madan and Brian who have been involved in the architecture and development of ONOS (Open Network Operating System).
Synopsis
ONOS is a distributed SDN network operating system architected to provide performance, scale-out, resiliency, and well-defined northbound and southbound abstractions. Madan and Brian, both from ON.Lab, will start the talk with a deep-dive into ONOS architecture, including the key technical challenges that were solved to build this platform. They will also walk us through a live demo of building a SDN application on ONOS.
Details:
ONOS Architecture
ONOS Abstractions and Modularity
ONOS Distributed architecture
ONOS APIs and their usage
Live demo- Building a SDN app on ONOS
Speaker Bios
Madan Jampani, Distributed Systems Architect, ONOS
Madan is Distributed Systems Architect at ON.Lab focusing on the core distributed systems problems for ONOS. Prior to joining ON.Lab in Sep 2014, Madan worked at Amazon for around 10 years. At Amazon, Madan was instrumental in building several key technologies ranging from Amazon retail ordering systems, distributed data stores and shared compute clusters for running large-scale data processing and machine learning workloads.
Brian O’Connor, Lead Developer, ONOS
Brian is the ONOS Application Intent Framework lead and a core developer at ON.Lab, working on ONOS and Mininet. Brian O’Connor received Bachelor’s and Master’s degrees in Computer Science from Stanford University. At Stanford, he helped develop “An Introduction to Computer Networking,” one of Stanford’s first MOOCs (Massively Open Online Courses).
ABOUT ON.LAB and ONOS
Open Networking Lab (ON.Lab) is a non-profit organization founded by SDN inventors and leaders from Stanford University and UC Berkeley to foster an open source community for developing tools and platforms to realize the full potential of SDN. ON.Lab brings innovative ideas from leading edge research and delivers high quality open source platforms on which members of its ecosystem and the industry can build real products and solutions.
ONOS, a SDN network operating system for service provider and mission critical networks, was open sourced on Dec 5th, 2014. ONOS delivers a highly available, scalable SDN control plane featuring northbound and southbound abstractions and interfaces for a diversity of management, control, service applications and network devices. ONOS ecosystem comprises of ON.Lab, organizations who are funding and contributing to the ONOS initiative including AT&T, NTT Communications, SK Telecom, Ciena, Cisco, Ericsson, Fujitsu, Huawei, Intel, NEC; members who are collaborating and contributing to ONOS include ONF, Infoblox, SRI, Internet2, Happiest Minds, CNIT, Black Duck, Create-Net and the broader ONOS community. Learn how you can get involved with ONOS at onosproject.org.
ONOS: Open Network Operating System. An Open-Source Distributed SDN Operating...ON.LAB
ONOS
Open Network Operating System
An Open-Source Distributed SDN OS
Pankaj Berde, Jonathan Hart, Masayoshi Kobayashi, Pavlin Radoslavov, Pingping Lin, Rachel Sverdlov, Suibin Zhang, William Snow, Guru Parulkar
Software Load Balancer for OpenFlow Complaint SDN architecturePritesh Ranjan
Download this presentation and view in Microsoft powerpoint. Animation effects make it difficult to understand on Slideshare.
REFERENCE:
R. Wang, D. Butnariu, and J. Rexford, “OpenFlow-based server load balancing gonewild,” In Hot-ICE, 2011.
SDN (Software Defined Networking) ControllerVipin Gupta
SDN is going to redefine networking and cloud world. This is the biggest thing that has happened in networking field in last 30 years. SDN is a New Way to Design, Build and Operate Networks. Here we are discussing about SDN Controllers.
This is an overview of OpenFlow Networking. Derived from a talk presented at the Open Networking Summit, it talks about the motivations for OpenFlow, the details of the protocol, and the current state of hardware and software.
Introduction to Software Defined Networking (SDN)rjain51
Class lecture by Prof. Raj Jain on Introduction to . The talk covers Origins of SDN, What is SDN?, Original Definition of SDN, What = Why We need SDN?, SDN Definition, XMPP, XMPP in Data Centers, Path Computation Element, PCE, Forwarding and Control Element, Sample ForCES Exchanges, Application Layer Traffic Optimization, ALTO, ALTO Extension, Current SDN Debate: What vs. How?, SDN Controller Functions, RESTful APIs, OSGi Framework, Open Daylight SDN Controller, OpenDaylight Tools, Affinity Metadata Service, SDN Related Organizations and Projects, SDN Web Sites, Hierarchy of Operations, Introduction to, Origins of SDN, What is SDN?, Original Definition of SDN, What = Why We need SDN?, SDN Definition, XMPP, XMPP in Data Centers, Path Computation Element, PCE, Forwarding and Control Element, Sample ForCES Exchanges, Application Layer Traffic Optimization, ALTO, ALTO Extension, Current SDN Debate: What vs. How?, SDN Controller Functions, RESTful APIs, OSGi Framework, Open Daylight SDN Controller, OpenDaylight Tools, Affinity Metadata Service, SDN Related Organizations and Projects, SDN Web Sites. Video recording available in YouTube.
The Open Network Operating System (ONOS) is the first open source SDN network operating system targeted specifically at the Service Provider and mission critical networks. ONOS is purpose built to provide the high availability (HA), scale-out, and performance these networks demand.
Software Load Balancer for OpenFlow Complaint SDN architecturePritesh Ranjan
Download this presentation and view in Microsoft powerpoint. Animation effects make it difficult to understand on Slideshare.
REFERENCE:
R. Wang, D. Butnariu, and J. Rexford, “OpenFlow-based server load balancing gonewild,” In Hot-ICE, 2011.
SDN (Software Defined Networking) ControllerVipin Gupta
SDN is going to redefine networking and cloud world. This is the biggest thing that has happened in networking field in last 30 years. SDN is a New Way to Design, Build and Operate Networks. Here we are discussing about SDN Controllers.
This is an overview of OpenFlow Networking. Derived from a talk presented at the Open Networking Summit, it talks about the motivations for OpenFlow, the details of the protocol, and the current state of hardware and software.
Introduction to Software Defined Networking (SDN)rjain51
Class lecture by Prof. Raj Jain on Introduction to . The talk covers Origins of SDN, What is SDN?, Original Definition of SDN, What = Why We need SDN?, SDN Definition, XMPP, XMPP in Data Centers, Path Computation Element, PCE, Forwarding and Control Element, Sample ForCES Exchanges, Application Layer Traffic Optimization, ALTO, ALTO Extension, Current SDN Debate: What vs. How?, SDN Controller Functions, RESTful APIs, OSGi Framework, Open Daylight SDN Controller, OpenDaylight Tools, Affinity Metadata Service, SDN Related Organizations and Projects, SDN Web Sites, Hierarchy of Operations, Introduction to, Origins of SDN, What is SDN?, Original Definition of SDN, What = Why We need SDN?, SDN Definition, XMPP, XMPP in Data Centers, Path Computation Element, PCE, Forwarding and Control Element, Sample ForCES Exchanges, Application Layer Traffic Optimization, ALTO, ALTO Extension, Current SDN Debate: What vs. How?, SDN Controller Functions, RESTful APIs, OSGi Framework, Open Daylight SDN Controller, OpenDaylight Tools, Affinity Metadata Service, SDN Related Organizations and Projects, SDN Web Sites. Video recording available in YouTube.
The Open Network Operating System (ONOS) is the first open source SDN network operating system targeted specifically at the Service Provider and mission critical networks. ONOS is purpose built to provide the high availability (HA), scale-out, and performance these networks demand.
Inter-controller Traffic in ONOS Clusters for SDN Networks Paolo Giaccone
In distributed SDN architectures, the network is controlled by a cluster of multiple controllers. This distributed ap- proach permits to meet the scalability and reliability requirements of large operational networks. Despite that, a logical centralized view of the network state should be guaranteed, enabling the simple development of network applications. Achieving a consis- tent network state requires a consensus protocol, which generates control traffic among the controllers whose timely delivery is crucial for network performance.
We focus on the state-of-art ONOS controller, designed to scale to large networks, based on a cluster of self-coordinating controllers, and concentrate on the inter-controller control traffic. Based on real traffic measurements, we develop a model to quan- tify the traffic exchanged among the controllers, which depends on the topology of the controlled network. This model is useful to design and dimension the control network interconnecting the controllers.
OPNFV VIM integrates control and management components from upstream projects such as openstack, ONOS, ODL, etc. While huge success has been achieved in OPNFV for integration, automated build and deployment, the performance of VIM for controlling and managing virtual network has received little attention. This presentation is to address the VIM performance related to the network part of the infrastructure. Based on a Telco use case, we define performance metrics for SDN controller, northbound communication channels, and network provisioning. ONOSFW and OpenStack are two components for VIM. Test data is collected and analyzed for performance evaluation and suggestions for future improvements. China Unicom, ON.LAB and Huawei jointly define the use case and methodology, do analysis, and produce results.
CORD aims to bring the data center economy and cloud agility to the service provider networks and is an end-to-end solution for the next generation central offices. CORD leverages three related technologies: SDN, NFV, and Cloud and builds on merchant silicon, white boxes and open-source platforms such as ONOS, OpenStack, and XOS. ON.Lab, AT&T and partners demonstrated CORD POC at ONS2015 and are now building a CORD POD for a market trial.
The CORD thought leaders and developers introduce CORD, explain the motivation from a service provider perspective, discuss CORD architecture, related services and key use cases including vOLT, vSG and vRouter.
Topics of Discussion
>>> CORD Introduction
>>> Motivation from a Service Provider Perspective
>>> CORD Architecture
>>> Usecases: vOLT, vSG and vRouter
>>> CORD Future Plans
Global SDN-IP Deployment at NCTU, TaiwanFei Ji Siao
Introduction to Overview of ONOS SDN-IP at NCTU, Taiwan
Ping-Chun Huang (pichuang@cs.nctu.edu.tw)
Min-Cheng Chan (charles@onlab.us)
Prof. Bao-Shuh Paul Lin (bplin@mail.nctu.edu.tw)
Prof. Chieo-Chao Tseng (cctseng@cs.nctu.edu.tw)
Reference:
Global SDN-IP Deployment at NCTU, Taiwan https://youtu.be/a8LR1DyzGY4
ONOS Lightning Talk: Global SDN deployment powered by ONOS https://youtu.be/orI2FtyxN1I
SDN 101: Software Defined Networking Course - Sameh Zaghloul/IBM - 2014SAMeh Zaghloul
Sameh Zaghloul
Technology Manager @ IBM
+2 0100 6066012
zaghloul@eg.ibm.com
SDN: Technology that enables data center team to use software to efficiently control network resources
SDN Overview
SDN Standards
NFV – Network Function Virtualization
SDN Scenarios and Use Cases
SDN Sample Research Projects
SDN Technology Survey
SDN Case Study
SDN Online Courses
SDN Lab SW Tools
- OpenStack Framework
- OpenDayLighyt – SDN Controller
- FloodLight – SDN Controller
- Open vSwitch – Virtual Switch
- MiniNet – Virtual Network: OpenFlow Switches, SDN Controllers, and Servers/Hosts
- OMNet++ Network Simulator
- Avior – Sample FloodLight Java Application
- netem - Network Emulation
- NOX/POX - C++/ Python OpenFlow API for building network control applications
- Pyretic = Python + Frenetic - Enables network programmers and operators to write modular network applications by providing powerful abstractions
- Resonance - Event-Driven Control for Software-Defined Networks (written in Pyretic)
SDN Project
Disaggregated Networking - The Drivers, the Software & The High AvailabilityOpen Networking Summit
Dis-agregration is real… This trend started with SDN and the separation of Data plane and Control plane. The scope has expanded to include separate of hardware and software and created a whole new industry of white boxes, general purpose X86 commodity hardware. All three markets - Cloud, Enterprise and Carriers are now engaged in various solutions inside the Data Center. The disaggregation is impacted all parts of the network including Access and Edge layers.
DragonFlow sdn based distributed virtual router for openstack neutronEran Gampel
Dragonflow is an implementation of a fully distributed virtual router for OpenStack® Neutron™ that is based on a light weight SDN controller
blog.gampel.net
OpenStack Networks the Web-Scale Way - Scott Laffer, Cumulus NetworksOpenStack
Audience Level
Beginner
Synopsis
Layer 2 versus Layer 3, MLAG, Spanning-Tree, switch mechanism drivers, overlays and routing-on-the-host — What scales and what does not? The underlying plumbing of an OpenStack network is something you’d rather not have to think about. This presentation examines the network architectures of web-scale and large enterprise OpenStack users and how those same efficiencies can be used in deployments of all sizes.
Speaker Bio:
Scott is a Member of Technical Staff at Cumulus Networks where he designs, supports and deploys web-scale technologies and architectures in enterprise networks globally. Prior to becoming a founding member of the Cumulus office in Australia, Scott started his career as a network administrator before joining Cisco Systems to support their data centre products.
OpenStack Australia Day Melbourne 2017
https://events.aptira.com/openstack-australia-day-melbourne-2017/
Many thanks to Nick McKeown (Stanford), Jennifer Rexford (Princeton), Scott Shenker (Berkeley), Nick Feamster (Princeton), Li Erran Li (Columbia), Yashar Ganjali (Toronto)
Paper PDF is available: https://dl.acm.org/citation.cfm?id=3195871
Accepted and presented at 5th Workshop on CrossCloud Infrastructures & Platforms, EuroSys Conference, April 2018
Scaling OpenStack Networking Beyond 4000 Nodes with Dragonflow - Eshed Gal-Or...Cloud Native Day Tel Aviv
As OpenStack matures, more users move from “dipping a toe” to deploying at large scale, with 1000's of nodes.
OpenStack networking has long been a limiting factor in scaling beyond a few hundreds of nodes, forcing users to turn to cell splitting, or to complete offloading of the networking to the underlay systems and forfeit the overlay network altogether.
Dragonflow is a fully distributed, open source, SDN implementation of Neutron, that handles large scale deployments without splitting to cells.
In testing we've conducted, we were able to scale to 4000+ controllers (each controller is typically deployed on a compute node), while maintaining the same performance we had on a small 30 node environment.
Modification of l3 learning switch code for firewall functionality in pox con...eSAT Journals
Abstract Software-Defined Networking (SDN) is the new trend in the networking field. The separation of the control plane from the forwarding plane has enabled the complete programmability of the network, since the control plane and the forwarding plane are decoupled. An API for POX controller is firewall. A modification of the Learning layer 3 switch code for POX controller is done for a tree topology of depth 3 by using mininet network emulator and the packet flow between the hosts is controlled according to the rules inserted in the Learning switch using OpenFlow controller. Keywords:-POX, SDN, Controller, rules, topology, Learning switch, Firewall
Running Neutron at Scale - Gal Sagie & Eran Gampel - OpenStack Day Israel 2016Cloud Native Day Tel Aviv
For the past 2 years we’ve been working on running OpenStack in ever growing scales. In Juno we started Dragonflow, a Neutron integrated distributed SDN project with an ambitious goal – scaling to 10,000 physical servers in a single zone. Although we’re not there yet, we’re definitely on the right track.
Dragonflow employs the following principles
• Pluggable NoSQL DB – to adapt for different size deployments and SLAs
• Distribution of Policies rather than flows – moving the “brain” to the edges
• Distributed architecture – enforcing network policies in the compute nodes
• Hybrid flow pipeline – Utilizing both proactive and reactive flows to easily allow built-in distributed smart apps (e.g. distributed DHCP)
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
How world-class product teams are winning in the AI era by CEO and Founder, P...
ONOS Open Network Operating System
1. ONOS
Open
Network
Opera.ng
System
Experimental
Open-‐Source
Distributed
SDN
OS
2. So3ware
Defined
Networking
TE
Network
OS
Mobility
Network
Virtualiza6on
Sco9
Shenker,
ONS
‘11
Global
Network
View
Packet
Forwarding
Packet
Forwarding
Packet
Forwarding
Packet
Forwarding
Packet
Forwarding
Openflow
Rou6ng
Abstract
Network
Model
3. Logically
Centralized
NOS
–
Key
Ques.ons
TE
Network
OS
Mobility
Network
Virtualiza6on
Global
Network
View
Packet
Forwarding
Packet
Forwarding
Packet
Forwarding
Packet
Forwarding
Packet
Forwarding
Openflow
Rou6ng
Abstract
Network
Model
Fault
Tolerance?
Scale-‐out?
How
to
realize
a
Global
Network
View
4. Related
Work
Distributed
control
plaQorm
for
large-‐scale
networks
Focus
on
reliability,
scalability,
and
generality
State
distribu.on
primi.ves,
global
network
view,
ONIX
API
ONIX
Other
Work
Helios,
Hyperflow,
Maestro,
Kandoo
distributed
control
planes
NOX,
POX,
Beacon,
Floodlight,
Trema
controllers
5. Mo.va.on
Ø Build
an
open
source
distributed
NOS
Ø
Learn
and
share
with
community
Ø
Target
WAN
use
cases
6. Ø Demo
Key
Func6onality
Ø Fault-‐Tolerance:
Highly
Available
Control
plane
Ø Scale-‐out:
Using
distributed
Architecture
Ø Global
Network
View:
Network
Graph
abstrac6on
Ø Non
Goals
Ø Performance
op6miza6on
Ø Support
for
reac6ve
flows
Ø Stress
tes6ng
Phase
1:
Goals
December
2012
–
April
2013
9. ONOS:
Scale-‐out
using
control
isola.on
Distributed
Network
OS
Instance
2
Instance
3
Instance
1
Network
Graph
Simple
Scale-‐out
Design
Ø An
instance
is
responsible
for
building
&
maintaining
a
part
of
network
graph
Ø Control
capacity
can
grow
with
network
size
15. Cassandra
In-‐memory
DHT
Id:
1
A
Id:
101,
Label
Id:
103,
Label
Id:
2
C
Id:
3
B
Id:
102,
Label
Id:
104,
Label
Id:
106,
Label
Id:
105,
Label
Network
Graph
Titan
Graph
DB
ONOS
Network
Graph
Abstrac.on
16. Network
Graph
port
switch
port
device
port
on
port
port
port
link
switch
on
device
host
host
Ø Network
state
is
naturally
represented
as
a
graph
Ø Graph
has
basic
network
objects
like
switch,
port,
device
and
links
Ø Applica.on
writes
to
this
graph
&
programs
the
data
plane
17. Example:
Path
Computa.on
App
on
Network
Graph
port
switch
port
device
Flow
path
Flow
entry
port
on
port
port
port
link
switch
inport
on
Flow
entry
device
outport
switch
switch
host
host
flow
flow
• Applica.on
computes
path
by
traversing
the
links
from
source
to
des.na.on
• Applica.on
writes
each
flow
entry
for
the
path
Thus
path
computa.on
app
does
not
need
to
worry
about
topology
maintenance
18. Example:
A
simpler
abstrac.on
on
network
graph?
Logical
Crossbar
port
switch
port
device
Edge
Port
port
on
port
port
port
link
switch
physical
on
Edge
Port
device
physical
host
host
• App
or
service
on
top
of
ONOS
• Maintains
mapping
from
simpler
to
complex
Thus
makes
applica.ons
even
simpler
and
enables
new
abstrac.ons
Virtual
network
objects
Real
network
objects
19. Ø Demo
Key
Func6onality
ü Fault-‐Tolerance:
Highly
Available
Control
plane
ü Scale-‐out:
Using
distributed
Architecture
ü Global
Network
View:
Network
Graph
abstrac6on
Phase
1:
Goals
December
2012
–
April
2013
21. Switch
Manager
Switch
Manager
Switch
Manager
Network
Graph:
Switches
OF
OF
OF
OF
OF
OF
Network
Graph
and
Switches
22. SM
Network
Graph
Switch
Manager
SM
Switch
Manager
SM
Switch
Manager
Link
Discovery
Link
Discovery
Link
Discovery
Network
Graph
and
Link
Discovery
23. SM
Network
Graph:
Links
SM
SM
Link
Discovery
Link
Discovery
Link
Discovery
LLDP
LLDP
LLDP
Network
Graph
and
Link
Discovery
24. Network
Graph
SM
SM
SM
Link
Discovery
Link
Discovery
Link
Discovery
LD
LD
LD
Devices
and
Network
Graph
Device
Manager
Device
Manager
Device
Manager
25. Network
Graph:
Devices
SM
SM
SM
LD
LD
LD
Device
Manager
Device
Manager
Device
Manager
PKTIN
PKTIN
PKTIN
Host
Host
Host
Devices
and
Network
Graph
34. Consistency
Defini.on
Ø Strong
Consistency:
Upon
an
update
to
the
network
state
by
an
instance,
all
subsequent
reads
by
any
instance
returns
the
last
updated
value.
Ø Strong
consistency
adds
complexity
and
latency
to
distributed
data
management.
Ø Eventual
consistency
is
slight
relaxa.on
–
allowing
readers
to
be
behind
for
a
short
period
of
.me.
35. Strong
Consistency
using
Registry
Distributed
Network
OS
Instance
2
Instance
3
Network
Graph
Instance
1
A
=
Switch
A
Master
=
NONE
A
=
ONOS
1
Timeline
All
instances
Switch
A
Master
=
NONE
Instance
1
Switch
A
Master
=
ONOS
1
Instance
2
Switch
A
Master
=
ONOS
1
Instance
3
Switch
A
Master
=
ONOS
1
Master
elected
for
switch
A
Registry
Switch
A
Master
=
NONE
Switch
A
Master
=
ONOS
1
Switch
A
Master
=
ONOS
1
Switch
A
Master
=
NONE
Switch
A
Master
=
ONOS
1
Cost
of
Locking
All
instances
Switch
A
Master
=
NONE
36. Why
Strong
Consistency
is
needed
for
Master
Elec.on
Ø Weaker
consistency
might
mean
Master
elec.on
on
instance
1
will
not
be
available
on
other
instances.
Ø That
can
lead
to
having
mul.ple
masters
for
a
switch.
Ø Mul.ple
Masters
will
break
our
seman.c
of
control
isola.on.
Ø Strong
locking
seman.c
is
needed
for
Master
Elec.on
37. Eventual
Consistency
in
Network
Graph
Distributed
Network
OS
Instance
2
Instance
3
Network
Graph
Instance
1
SWITCH
A
STATE=
INACTIVE
Switch
A
State
=
INACTIVE
Switch
A
STATE
=
INACTIVE
All
instances
Switch
A
STATE
=
ACTIVE
Instance
1
Switch
A
=
ACTIVE
Instance
2
Switch
A
=
INACTIVE
Instance
3
Switch
A
=
INACTIVE
DHT
Switch
Connected
to
ONOS
Switch
A
State
=
ACTIVE
Switch
A
State
=
ACTIVE
Switch
A
STATE
=
ACTIVE
Timeline
All
instances
Switch
A
STATE
=
INACTIVE
Consistency
Cost
38. Cost
of
Eventual
Consistency
Ø Short
delay
will
mean
the
switch
A
state
is
not
ACTIVE
on
some
ONOS
instances
in
previous
example.
Ø Applica.ons
on
one
instance
will
compute
flow
through
the
switch
A
while
other
instances
will
not
use
the
switch
A
for
path
computa.on.
Ø Eventual
consistency
becomes
more
visible
during
control
plane
network
conges.on.
39. Why
is
Eventual
Consistency
good
enough
for
Network
State?
Ø Physical
network
state
changes
asynchronously
Ø Strong
consistency
across
data
and
control
plane
is
too
hard
Ø Control
apps
know
how
to
deal
with
eventual
consistency
Ø In
the
current
distributed
control
plane,
each
router
makes
its
own
decision
based
on
old
info
from
other
parts
of
the
network
and
it
works
fine
Ø Strong
Consistency
is
more
likely
to
lead
to
inaccuracy
of
network
state
as
network
conges6ons
are
real.
41. Ø Is
graph
the
right
abstrac.on?
Ø Can
it
scale
for
reac.ve
flows?
Ø What
is
the
Concurrency
requirement
on
graph?
Ø Is
it
large
enough
to
use
a
NoSQL
backend?
Ø What
about
No.fica.ons
or
publish/subscribe
on
Graph?
Ø Are
we
using
the
right
technologies
for
Graph?
Ø Is
DHT
a
right
choice?
Ø Cassandra
has
latencies
in
order
of
millisecond
–
is
it
ok?
Ø What
throughput
do
we
need?
Ø Titan
is
good
for
rapid
prototype
–
is
it
good
enough
for
produc.on?
Ø Have
we
got
our
Consistency
and
Par..on
Tolerance
right?
Ø What
is
the
latency
impact?
Ø Should
we
pick
Availability
over
Consistency?
ONOS
-‐
Ques.ons
42. What
is
Next
for
ONOS
ONOS
Core
ONOS
Apps
Performance
benchmarks
and
improvements
Reac.ve
flows
and
low-‐latency
forwarding
Events,
callbacks
and
publish/subscribe
API
Expand
graph
abstrac.on
for
more
types
of
network
state
ONOS
Northbound
API
Service
chaining
Network
monitoring,
analy.cs
and
debugging
framework
Community
Release
as
open
source
and/or
contribute
to
Open
DayLight.
Build
and
assist
developer
community
outside
ON.LAB
Support
deployments
in
R&E
networks