Andreas Fischer, University of Passau
andreas.fischer@uni-passau.de
Network Virtualization in the
Future Internet
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Table of Contents
Introduction to virtualization
Network virtualization
Terminology and Concepts Applications
Instantiation and Management
Virtual Network Embedding
Problem description Problem complexity Strategies
Evaluation
Virtualization of Resources –
Definition
virtual: adj.[via the technical term virtual memory, prob.: from the term virtual image in optics]
1. Common alternative to logical; often used to refer to the artificial objects (like addressable virtual memory larger than physical memory) simulated by a computer system as a convenient way to manage access to shared resources. 2. Simulated; performing the functions of something that isn't really there. An
imaginative child's doll may be a virtual playmate. Oppose real.
Eric S. Raymond – Jargon File http://www.catb.org/~esr/jargon/
Virtualization of Resources: Create virtual resources
To partition and/or aggregate real resources To create resources with new qualities
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Virtualization of Resources
Aggregation and splitting of resources
Combination of resources (clustering)
e.g., Grid computing
Splitting of resources (zoning, partitioning)
e.g., Server virtualization
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Resources that can be virtualized
CPU
Partition CPU time into slices
Memory
Use swap mechanisms to create virtual memory address space
Hard drive
Span multiple physical disks Use file as virtual hard drive
Network card
Create virtual network adapter
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
System Virtualization
Virtual Machine Monitor (VM Monitor)
Virtualizes host resources
Multiplexes Virtual Machines onto physical hardware
Virtual Machine (VM)
Provides virtual hardware to guest operating system Exists in an isolated environment
Available management primitives
Start / Pause / Resume / Stop VM Migrate VM (cold, live)
Add / Remove hardware to VM
6 VM VM G u es t OS G u es t OS Real Machine VM Monitor
A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Advantages of System
Virtualization
Reuse existing hardware instead of installing new devices
Consolidation of services Reduces operational cost
Reduces energy consumption
New flexibility available
Use Virtual Machines as test environments
Use snapshots to return to a known configuration
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Problems of System
Virtualization
Rising complexity through additional layers
Management of resources needed New security threats possible
“Virtual Machine Sprawl”
Ease of creation leads to high number of virtual machines Increased administrative effort
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Table of Contents
Introduction to virtualization
Network virtualization
Terminology and Concepts Applications
Instantiation and Management
Virtual Network Embedding
Problem description Problem complexity Strategies
Evaluation
Network Virtualization:
Motivation
Today’s network layer is too inflexible
Slow adoption of new techniques (e.g. DiffServ/IntServ, IPv6) Leads to makeshift solutions (e.g. Network Address Translation) New services are restricted by current limitations
We need to overcome ossification of today’s Internet
Cater to new services Dynamically adaptable
Use virtualization mechanisms to increase flexibility
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Nodes
E.g., routers, firewalls,
caches, ...
Qualitative properties
Active
Programmable
Quantitative properties
CPU capacity (Number of
CPUs, clock rate)
Memory capacity (both RAM
and disk)
...
Links
E.g., CAT-5 cable, wireless
channel, ...
(+ interfaces) Qualitative properties
Passive Non-programmable Quantitative properties
Bandwidth (uni- or bidirectional) Bit error rate Delay
...
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Network Virtualization:
Terminology (1)
Network Virtualization:
Terminology (2)
Physical resources
„Real“ hardware
„That, which is touchable and consumes power“
Virtual resources
„Simulated“ hardware
Characteristics: Demands for particular amount of resources
Substrate resources
Resources used to create virtual resources Can be virtual themselves Recursion
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Network Virtualization:
Terminology (3)
Topology
A graph, representing the network Consists of nodes and links
Can have particular characteristics (random, structured, ...)
Network
A weighted topology
Nodes and links are annotated with resources Virtual network: Demands resources
Substrate network: Provides resources
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Virtual Router
Virtual router
in the context of
system virtualization
OS with routing functionality Encapsulated in a VM
Managed by a VMM
Virtualization advantages:
Router OSs sandboxed from
each other
Different routing mechanisms on
the same (real) machine
R o u te r O S Real Machine VMM VM R o u te r O S R o u te r O S VM VM
Virtual
Router
A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
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Virtual Link
Virtual link
Logical interconnection of two virtual routers Appearing to them as a direct physical link
Properties can be set dynamically (e.g. bandwidth)
Can traverse more than one physical link (i.e., aggregation)
Virtual Link Phys. Link VMM Real Machine R o u te r OS Real Machine VMM R o u te r OS RM Phys. Link R o u te r OS R o u te r OS VM VM VM VM
A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Creating a virtual network
Host A
Start VM1
# qemu –enable kvm ... vm1.img
Create bridge, connect VM
# brctl addbr virbr0
# brctl addif virbr0 vnet0
Create virtual link (tunnel)
# ssh -o Tunnel=ethernet -f -w 0:0 HostB true
Connect SSH endpoint to
bridge
# brctl addif virbr0 tun0
Host B
Start VM2
# qemu –enable kvm ... vm2.img
Create bridge, connect VM
# brctl addbr virbr0
# brctl addif virbr0 vnet0
Wait for tunnel connection
...
Connect SSH endpoint to
bridge
# brctl addif virbr0 tun0
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Virtual network instantiation
Coordination of physical resources
Discover network topology Determine available resources
Start up virtual nodes
Determine physical resources
to be used
Configure and start virtual nodes
Start virtual links
Connect virtual nodes
Configure virtual network interfaces
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Management of virtual resources
Common interface necessary to create and modify virtual
networks
Provide management primitives Create / destroy virtual nodes Create / destroy virtual links Provide monitoring information
Enable dynamic creation and modification of networks
Requires sufficient performance
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Performance:
Creation of virtual networks
Virtual networks have to be created on the fly
Support dynamic establishment of communication channels Dynamicity depends on time to reach fully operational state Time may depend on resources already hosted
E.g., start new node
Create node: May need time to boot
Connect with other nodes: Set up networking, configure links
What are performance limits?
Minimum time for resource creation
Performance:
Modification of virtual networks
Node migration as part of network reconfiguration
React to upcoming network challenges Redistribute physical resources
Step 1: Move virtual node
Requires bandwidth and time Minimize effect on network
Step 2: Redirect network traffic
Avoid loss of packets Minimize downtime
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Virtual Machine Migration for
Resilience
Migrate from unhealthy node to healthy node
Requires health monitoring Requires failure prediction
Cold state
Disk image Hardware configuration Hot state
CPU state RAM contents 21 H o t st at e Real Machine Virtualisation Layer Migration Real Machine Virtualisation Layer C ol d st at e VM H ot st at e C ol d st at e VMA. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Migration phases
Several distinct phases during migration
Needs significant lead time
Elaborate monitoring mechanisms Depends on type of challenges
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Application: Companies
Multiple logical networks on top
of one physical network
Reflects workgroups or company processes Historically different networks
Ensure separation
of concerns
Network virtualization
Compartmentalization Today: VLAN 23A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Application: Cloud data centres
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Virtual services are not isolated
Services can be highly interconnected
E.g. Load-balancer <-> Webserver(s) <-> Database(s)
Customer requirements have to be considered
Minimum bandwidth needed Maximum delay accepted
Communication has influence on energy
Switch ports turned on/off Routers active/inactive
Has to be reflected in data centre
management
Within a single data centre Across federated data centres
Application: Future Internet
Testbeds
Motivation: Test new network protocols and architectures
Lots of different approaches
PlanetLab
1298 nodes, 621 sites GENI
US extension of PlanetLab G-Lab
German extension of PlanetLab
Vision: Seamless convergence towards a future Internet
In Europe: FIRE initiative:
http://www.ict-fire.eu/25
A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Future Internet Business model
Current cloud model
Infrastructure provider
(e.g., Amazon EC²)
Service provider (e.g., Dropbox)
Future model
Virtual Network Provider assembles Virtual Network Operator operates
Roles may be mixed
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Table of Contents
Introduction to virtualization
Network virtualization
Terminology and Concepts Applications
Instantiation and Management
Virtual Network Embedding
Problem description Problem complexity Strategies
Evaluation
Virtual Network Embedding
Virtual Network Embedding (VNE): Map virtual resources to
substrate resources
Substrate network
provides resources
Virtual networks
consume resources
Resources are node and
link properties
Node: E.g. CPU power Link: E.g. bandwidth
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Virtual Network Embedding
Given a set of Virtual Network Requests (VNRs), what is the
optimal way of instantiating them on a substrate network?
Problem: What is optimality?
Minimize usage of substrate resources? Maximize number of accepted VNRs?
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
VNE: Problem complexity
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Embedding is NP-hard for most applications
Nodes have CPU demands?
Bin-packing
Virtual nodes are
objects
Substrate nodes
are bins
Virtual links may not be split?
Multi-commodity flow
Virtual links are commodities NP-hard if unsplittable
Excursion: The P-NP Problem
Given a graph G with nodes N and links L:
G = (N, L)
Is there a round-trip that visits every link exactly once?
Easy to decide („Euler-cycle“)
Graph has to be connected and every node‘s degree is even
Is there a round-trip that visits every node exactly once?
??? („Hamilton-cycle“)
... try all combinations. Drawback: Exponential runtime!
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Excursion: The P-NP Problem
Given an airline network with cities interconnected by flights.
Assume that there is a fixed price for each connection.
What is the cheapest trip from Oslo to Passau?
Reasonably easy to calculate („Dijkstra‘s algorithm“)
Successively compute cheapest paths to neighbouring cities
until the destination is reached
What is the cheapest round-trip starting in Oslo and visiting
every city at least once?
??? („Travelling-Salesman Problem“)
... try all combinations. Drawback: Exponential runtime!
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Excursion: The P-NP Problem
Given a boolean formula with n variables:
F = ( x
1&& !x
2) || ( x
3&& x
2) || ...
Is there a configuration for the variables such that the entire
formula evaluates to „True“?
??? („SAT“, „satisfiability“)
Given a set of bins, each with a capacity c
iand a set of objects,
each with weight w
j
Can all objects be put into the bins without overflowing one
of them?
??? („Bin-packing“)
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Excursion: The P-NP Problem
Similarities between those problems
All of them can be solved in exponential runtime
(brute-force: try every combination)
Problems are closely related: If there were a polynomial
solution for one of them, all other problems could be solved polynomially, as well!
However: a polynomial solution is known for none of them
Are we lost?
Luckily not: Heuristics!
Optimal solution may be infeasible, but near-to-optimal will
often be enough
„Find me a cheap round-trip (not necessarily the cheapest)“
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
P-NP in Virtual Network
Embedding
Our problem here (just the node mapping):
Given a set of
bins substrate nodes
, each with a capacity c
iand a
set of
objects virtual nodes
, each with weight w
j
Can all
objects virtual nodes
be put into the
bins substrate
nodes
without overflowing one of them?
Just a reformulation of „Bin-packing“
We can use heuristics for that: Try to embed „a lot“ of virtual
nodes (even if maximum is not reached)
Does not consider links, though
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Strategies: Node and Link
embedding
Two-stage embedding
First: Node embedding E.g., first fit, best fit, ... Then: Link embedding
E.g., shortest-path routing
Problem: Link embedding may be bad
Single-stage embedding
Coordinated node and link embedding Takes link demands into
account
But: More complex
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Strategies: Offline vs. online
embedding
Offline embedding
All VNRs are known in advance
Can (in principle) calculate the overall optimal solution
Online embedding
VNRs may arrive randomly
VNRs have a specified life-time – will be deleted afterwards Challenges
Requires fast embedding Fragmentation may occur
Static vs. Dynamic embedding
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Strategies: Static vs. dynamic
embedding
Static embedding
: Embedding does not change
Dynamic embedding
: Embedding can be modified
Allows to make place for new VNRs Requires migration functionality
What is the cost of migration here?
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Large amount of approaches already existing
Algorithms can be classified in three dimensions
Centralized vs. distributed Static vs. dynamic
Concise vs. redundant
Most approaches focus on performance
Nodes: Distribute CPU capacity
Actually, vector packing would be similar Links: Distribute link bandwidth
But what about delay or failure rates?
Strategies: Different VNE
algorithms in literature
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Considering security issues
Virtual node to virtual node
Resource starvation: Excessive CPU usage Can be used as Denial of Service attack Sidechannel attacks
Virtual machine to virtual link
Eavesdrop on communication
Resource starvation: Excessive network traffic
Virtual machine to physical machine
Exploit vulnerabilities in virtualization solution Threatens other virtual machines as well
How to reflect in embedding?
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Considering energy efficiency
Improve energy efficiency of physical network
Maximize idle resources Can then be switched
into power saving mode
Difficulty: Hidden hops
Some embeddings may
cause nodes to be active just to forward data
Energy efficient
embedding avoids such situations
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
VNE Evaluation with ALEVIN
Difficulty: Lots of parameters to control
Size and topology of networks Distribution of resources
Many scenarios Lots of time
spent during evaluation
Which metrics to evaluate?
Acceptance ratio: What is the
ratio of accepted VNRs?
Revenue / cost: What is the
ratio of realized virtual demands vs. spent substrate resources?
Running time: How much time did the algorithm take to embed
a particular set of VNRs?
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
VNE Evaluation with ALEVIN
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Create networks
Arbitrary topologies Any size Support various
resources
Link and node
Beyond just CPU and
bandwidth
Run VNE algorithms
Framework supports huge number of experiments
Lots of metrics to compare (common and more exotic)
VNE Evaluation with ALEVIN:
Energy efficiency
Modify existing VNE algorithm to take
energy efficiency into account
Savings possible due to hidden hop
avoidance
Avoid nodes powered only for virtual links Original algorithm
produces lots of hidden hops
High potential for
optimization
Parameters:
● SN with 100 nodes
● 5 VNs with 5-15 nodes each
● Substrate resources: 1-100
● Virtual resources: 1-50
● Power consumption: 100-500W
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
Conclusions
Network Virtualization is important concept for the Future
Internet
Increase network flexibility and manageability Provide separation of concerns
In some areas already in use today
Companies, Cloud Data Centres, Future Internet Testbeds
Virtual Network Embedding is the primary algorithmic
problem for Network Virtualization
Lots of work already done Lots of work still to do
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
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Berl, A.; Fischer, A. & de Meer, H. „Virtualisierung im Future Internet - Virtualisierungsmethoden und Anwendungen“.
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Fischer, A.; Botero, J. F.; Duelli, M.; Schlosser, D.; Hesselbach, X. & De Meer, H. “ALEVIN - A Framework to Develop, Compare, and Analyze Virtual Network Embedding Algorithms”. Electronic Communications of the EASST, Proc. of the Workshop on Challenges and Solutions for Network Virtualization (NV2011), EASST, 2011, 37, 1-12
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International Workshop on Network Resilience: From Research to Practice (WNR2011), IEEE, 2011
Clark, C.; Fraser, K.; Hand, S.; Hansen, J. G.; Jul, E.; Limpach, C.; Pratt, I. & Warfield, A. “Live migration of virtual mac hines”.
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A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 2014
