Chair of Future Communication
Prof. Dr. K. Tutschku
Institute for Multimedia and Distributed Systems
Faculty of Computer Science
Network Virtualization as a Mean for Service Convergence
for Future Communication Systems –
What can we learn from Federated Experimental Facilities?
K. Tutschku (kurt.tutschku@univie.ac.at)
Future Internet?
Overview
 The Internet under pressure
 The success of the Internet
 Network virtualization: virtual structures for convergent
services
 The GENI experimental facility
 Performance issues of Transport Virtualization
 Conclusion
Internet under Pressure
Access
networks
Core
networks
 Internet will become a network of applications, services und content
 Services are the new central elements  Convergence in usage
 What changes hereof are anticipated for users, mechanisms and the future
network architectures?
Networks under Change: Services
Applications
Teletext
Data service
Services
Service
provider
POTS
Voice
(wired)
 Limited convergence
X.25 / FR
Voice
(cellular)
ResellerAA
Reseller
class. national PTT
Network
operator
Mobile
ISDN
GSM
Networks under Change: Services
Applications
POTS
Web
IP service
Services
Service
provider
Network
operator
mobile
IP Service Provider
A
B
C
ATM/
MPLS
 Limit convergence
 Internet Protocol (IP) is main converging layer
D
E
GPRS
Deficiencies of the Current Internet
 Performance (“World wide wait”)
 However: No convergence; QoS islands with
are available (depending on technology and
provider)
 Reliability:




Again: no convergence
Availability of the Internet ´03: 93.2% − 99.6%
Availability of POTS: 99.99% – 99.999%
However: sophisticated resilience mechanisms
available at experienced ISP
 Competition / business models:
 J. Crowcroft: “… I can go on the web
and get my gas, electricity, … changed , why
is it not possible to get a SPOT price for broadband internet?” (E2E-interest mailing list on April
26th, 2008); contracts prohibit change
 No convergence; even technically infeasible
Networks under Change: Services
Applications
Services
Web.
Unified communication appl.
IP Service
Voice
Video
Messaging
Data
D
E
Overlays (e.g. Skype)
Service
provider
Network
provider
IP Service Provider
A
xDSL
B
C
UMTS
PSTN
WLAN
Multi-Network Services
 Limit convergence
 Internet Protocol (IP) is main converging layer (but: hour glass model!)
 Integration of different technical and administrative domains by virtual networks:
Overlays
 Overcome deficiencies and implement new features
 Networks/overlays have to be (self-)organized for the services
Networks under Change: Services
Data/
Service
Data/
Service
consumer
provider at
at edge
edge
of
of network
network
?
centralized
distributed
?
Network-based provider (server)
Data/
Service
Data/
Service
Data/
Service
Data/
Service
 Services will be offered and controlled from the edge („edge-based services“)
 Central services will be virtualized
 Boundaries between consumer and provider vanish (“prosumer”)
 Symmetrical rolls require new architectures (ADSL?) and permit new business
models („Peer productivity“)
 Management of edge-based services? Optimal placement? Different user behavior?
Dimensioning?
 Which functions should be self-*?
Networks under Change: Services
 Application-oriented and self-organizing overlays outperform current services
 Support for resources contribution by arbitrary users: „Overlays for Cooperation/
Participation“
 What is the performance of self-*? Scalability? Churn? Dynamical traffic patterns?
Networks under Change: Transport
Systems
Management plane
Service
request (FAX, Web)
„semi-manual“
provisioning
E3
Remote office
ATM
Headquarter
Networks under Change: Transport
Systems
Management Plane
Control Plane
auto. Signaling
auto. provisioning
IP layer
EPON
Remote office
100GE layer
DWDM layer
Headquarter
MultiLayerNetworks
 State-of-the-art optical transport systems:
 Ultra-high transmission capacities; embedding of different transport network into one
physical network (multi-layer networks)
 Decay of CAPEX per Bit  Increased automation  self-* features (self-operation,
self-organization)
 However: higher complexity („numerous overlays“?)
 How to achieve convergence?
Success of the Current Internet
 Efficient P2P-based, self-organizing
content distribution networks
P2P, 67,3%
 Ratio of data traffic types at
public access node
eMail, 1,2%
FTP, 0,3%
Web, 7,9%
other, 23,3%
Quelle: Telefonica (2003)
 Data traffic by IP TV
Terrabytes per month
YouTube − world wide (Cisco est., May 2008)
100.000
P2P Video streaming in China (Jan. 2008)
33.000
YouTube − USA (Mai 2008)
30.500
US. Internet back bone at year end 2000
25.000
US. Internet back bone at year end 1998
6.000
Quelle: CISCO (2008)
Multi-Source Download (eDonkey, BT)
Offers file X
Peer
Offers file X
Transfer of
segment B
Offers file X
Index
server
Transfer of
segment A
Looking for X
 P2P: two overlays (virtual structures) with different application layer functions (two
basic P2P functions: searching / content exchange); each with different topology,
addressing, and routing
 Search function: able of self-contained re-organization of search mechanism
 Downloading peer: self-initiated selection of providing peer (parallel routing of content)
based on resource quality (throughput)  select the best (multi-)path for the content
→ Self-operation of basic P2P functions among networks  convergence is possible
Diversity I: Multi-Provider Environment
West coast
East coast
 High diversity wrt. paths:
 Three North-american nation-wide
ISPs Tier1 (AS 3967 Exodus,
AS3356 Level3, AS6467 Abovenet;
M. Liljenstam et al., 2003)
 Multiple routes for increased
resilience and competition are (theoretically) readily
available!
Network selection not available in
current IP  no convergence
 Any way: autonomous identification of available resources
needed
(Thanks to Michael Menth für vsualization)
Diversity II: Multi-Quality Environment
 25% of paths violate the triangle inequality
(wrt. packet delay)
 Measurements in PlanetLab by
S. Banerjee et al. (2004)
Using an
intermediate
A
direct
connection
➞ Internet routing is far from optimal
B
C
➞ Better paths exist; capazity is readily
available
Triangle Inequality (TI):
D(A,C) ≤ D(A,B) + D(B,C)
➞ Can be offered (competition)
➞ Again: autonomous identification of available
resources needed
! „Multi-homing“ not really available current IP protocols
Virtualization of Operating Systems
 One hardware executes multiple systems
 Safe: Strong isolation of resources, e.g. for testing and debugging
 Individual and powerful: User see whole computing center as his own
computer
 Efficient: reduction of CAPEX (consolidation of multiple machines in a single
physical one) and OPEX (operational issue)
 Convergence of operating systems
Virtual Networks for Convergent Services
Stellt X zur
Verfügung
Peer
Stellt X zur
Verfügung
Transfer von
Segment B
Diversity
 Exploit diversity of resources by smart
localization
Provide optimal resources
Stellt X zur
Verfügung
Index
server
Transfer von
Segment A
Sucht X
Overlays
 Overlays: application-oriented topology,
addressing, and routing
 Multi-Network Services
 Self-operation of functions
 Enables global convergence
Convergence by




☝
OS virtualization
 Strong isolation of resources
 Consolidation and efficient
operation
 Enables local convergence
Network Virtualization
Build a „personal network (PN)” for an application (PN  PC)
Integration of different technologies and administrative domains
Re-use of generic infrastructure on small time scale
Push application-layer mechanisms safely down the stack
Avoid “multi-layer” trap  autonomic/self-* operation; particularly smart resource mgmt
A Formal Description for Virtualization
 Virtual resources
 Generation of logical resources
 Sharing: one physical, multiple logical resources
 Aggregation: one logical, multiple physical
Share
Virtual Machine
Servic
e
Servic
e
Guest OS
Guest OS
Virtual CPU
Virtual
Machine
Virtual Memory
Aggregation
Load Balancer
Servic
e
Logical Virtual Server
Load Balancer
Switch
Virtual I/O
Virtual Machine Monitor
CPU
Memory
I/O
Physical
Server
Transport Virtualization (TV)
 Example: Virtual Memory
 OS integrates disconnected physical memory, even disk
space, into continuous memory
 location of physical memory doesn’t matter
 Transport Virtualization (Tutschku, Nakao, 2008):
abstraction concept for data transport resources
 Physical location of transport resource doesn't matter
(as long resource is accessible)
 Achieved by: abstract data transport resources
T. Zinner, P. Tran-Gia
A. Nakao
 combined from one or more physical/overlay transport
resources, e.g. leased line, wave length path, an overlay
link, MPLS path, or an IP forwarding capability
 physical resources can be used preclusive or concurrently
 basic resources can be located in even different physical
networks or administrative domains
Concurrent Multi-Path Transfer
Aim:
Overlays of
provider II
Very high and reliable transmission between two
end hosts
Transport Virtualization:
Aim: Very highSolution:
and reliable
throughput between two
Combine multiple paths (even from different
end hosts
overlays)
pooled transport pipe
Overlays of
provider I
POP
Physical topology
Implementation: routing overlays
Routing Overlay (= P2P Multi-Source Download)
Internet Router
3
1
2
1
2
4
Divert selected endhost packets
Request Paths for Diverted Packets
Path
Path oracle
Source
One-hop
(SOR)
SORASource
RouterRouter
(One-(Overlay)-Hop)
3
Encapsulated, send using path
4
Decapsulate, egress to destination
Gummadi et al (2004):
Nakao, Tutschku, Zinner:
(2008)
Scalable “One-Hop” (= intermediate) routing overlays
Consideration of multiple paths
! May be inefficient
 Reduction of overhead (since edge-based)
 Placement of NV router in core
 Application: Transport System Virtualization for
 high-capacity transmissions, e.g. for HD TV
 How can we test it?
GENI: The Global Environment for
Network Innovation
 Started in 2007
 Original agenda
 Research:
○ Identify fundamental questions; Drive a set of experiments to
validate theories and models
 Experiments & requirements
○ Drives what infrastructure and facilities are needed
 Currently
 One very rough blueprint; Five different control
architecture
 Major ideas infrastructure operation:
 Clearing house: settles usage request
 Lifetime for resources: has to be returned at predefined lifetime
Appealing Idea: Federation
My experiment runs across
the evolving GENI federation.
Corporate
GENI suites
Wireless #1
Compute Backbone #2
Cluster #1
Access #1
Other-Nation
My GENI Slice Projects
Compute
Cluster #2 Backbone #1
Other-Nation
Projects
NSF parts of GENI
Wireless #2
(Slide by Chip Elliot)
Resource Discovery
Aggregates publish resources, schedules, etc., via clearinghouses
What resources can I use?
GENI
Clearinghouse
Offer
Researcher
Components
Components
Components
Aggregate A
Aggregate B
Aggregate C
Computer Cluster
Backbone Net
Metro Wireless
(Slide by Chip Elliot)
Slice Creation
Clearinghouse checks credentials & enforces policy
Aggregates allocate resources & create topologies
Create my slice
GENI
Clearinghouse
Components
Components
Components
Aggregate A
Aggregate B
Aggregate C
Computer Cluster
Backbone Net
Metro Wireless
(Slide by Chip Elliot)
Experimentation
Researcher loads software, debugs, collects measurements
Experiment – Install my software,
debug, collect data, retry, etc.
GENI
Clearinghouse
Components
Components
Components
Aggregate A
Aggregate B
Aggregate C
Computer Cluster
Backbone Net
Metro Wireless
(Slide by Chip Elliot)
Slice Growth & Revision
Allows successful, long-running experiments to grow larger
Make my slice bigger !
GENI
Clearinghouse
Components
Components
Components
Aggregate A
Aggregate B
Aggregate C
Computer Cluster
Backbone Net
Metro Wireless
(Slide by Chip Elliot)
Federation of Clearinghouses
Growth path to international, semi-private, and commercial GENIs
Make my slice even bigger !
GENI
Clearinghouse
Components
Components
Components
Components
Aggregate A
Aggregate B
Aggregate C
Aggregate D
Computer Cluster
Backbone Net
Metro Wireless
Non-NSF Resources
(Slide by Chip Elliot)
Federated
Clearinghouse
Operations & Management
Always present in background for usual reasons
Will need an ‘emergency shutdown’ mechanism
Stop the experiment
immediately !
GENI
Clearinghouse
Oops
Components
Components
Components
Components
Aggregate A
Aggregate B
Aggregate C
Aggregate D
Computer Cluster
Backbone Net
Metro Wireless
Non-NSF Resources
(Slide by Chip Elliot)
Federated
Clearinghouse
Federation for Transport
Virtualization
Path selection
Routing
Overlay
used
path
Path selection for
concurrent use
Routing
Overlay
pooled
ressource
Path selection in federated
networks  convegence
of networks
Routing
Overlay I
pooled
ressource
Routing
Overlay II
Transmission Model
Data stream divided at router into
segments with k parts
p1,1
each provider will offer a set ni of parallel paths
(i = 1…m)
overlay 1
p1,n1
1
 Scheduling?
Assumption: use k
parallel paths on m
overlays
2

src
dst
k pooled
paths
k
pm,1
m
npaths
With k

i
1i

1
k-1
k parts are send in
parallel at time t
k parts have
arrived
k
overlay m
pm,nm
Re-sequencing buffer of
size L
Reassemble data stream from
obtained parts
 Buffer occupancy?
So far: Simulation Experiment
Input:
Number of paths
Path delay distributions
Scheduling
Path capacity
Source
Destination
Output: Re-sequencing buffer occupancy distribution
 Search for path selection strategies; future on-line selection for
convergence
Impact of Type of Delay Distribution I
Delay
Types of distributions:
Uniform:
artificial behavior
Truncated Gaussian: mathematical tractability
Bimodal:
two modes of a path
Investigation of different influence factors
Impact of Type of Delay Distribution II
Two synchronous, equal
capacity paths
Buffer
Three synchronous, equal
capacity paths
Buffer
Highly non-linear  careful and complex path selection
Current Work: Perform Real-World
Measurements
 Measurement set-up
 Gain realistic parameters and strategies
Conclusion
 Expected features of the Future Internet
 Faster, more reliable, more business cases, increased interaction
with users: symmetric rolls, „Architecture for Participation“
 Forming of applications-specific overlays
 Network virtualization:
 Consolidation of multiple (virtual) network into one physical
infrastructure
 Making data transport independent from resource locations 
transport virtualization
 Integration/convergence of different transport systems und
operator domains by overlays and network virtualization
 Design networks for applications (rather than designing
applications for networks)
 Experimental facilities:
 Federation: blue print for future network operation and
convergence
 Resources with limited lifetime  significant challenges in
resource management
Thanks for your
attention!
Questions?