Network Virtualization in the Future Internet

Network Virtualization in the Future Internet Concepts, Applications, and Challenges Andreas Fischer, University of Passau andreas.fischer@uni-passau.de

Table of Contents Introduction to virtualization Network virtualization Terminology and Concepts Applications Instantiation and Management Virtual Network Embedding Problem description Problem complexity Strategies Evaluation Conclusions 2

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 3

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 4

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 5

Guest OS Guest OS 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 VM VM VM Monitor Real Machine 6

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 7

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 8

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 10

Network Virtualization: Terminology (1) 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... A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 11

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 12

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 13

Router OS Router OS Router OS 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 VM VM VM VMM Real Machine Virtual Router 14

Router OS Router OS Router OS Router OS 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) VMM Real Machine Phys. Link Virtual Link VM VM VM VM RM Phys. Link VMM Real Machine 15

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 A. Fischer, Network Virtualization in the Future Internet, Oslo, Oct. 16

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 17

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 18

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 Maximum number of virtual resources hosted 19

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 20

Virtual Machine Migration for Resilience VM Hot state Cold state VM Hot state Cold state Migrate from unhealthy node to healthy node Requires health monitoring Requires failure prediction Cold state Disk image Hardware configuration Migration Hot state CPU state RAM contents Virtualisation Layer Real Machine Virtualisation Layer Real Machine 21

Migration phases Several distinct phases during migration Needs significant lead time Elaborate monitoring mechanisms Depends on type of challenges 2222

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 23

Application: Cloud data centres 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 Image source: Wikipedia 24

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 Image source: http://www.german-lab.de/ Vision: Seamless convergence towards a future Internet In Europe: FIRE initiative: http://www.ict-fire.eu/ 25

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 26

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 28

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? 29

VNE: Problem complexity 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 30

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! 31

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! 32

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 i and a set of objects, each with weight w j Can all objects be put into the bins without overflowing one of them???? ( Bin-packing ) 33

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) 34

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 i and 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 35

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 36

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 37

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? 38

Strategies: Different VNE algorithms in literature 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? 39

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? 40

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 41

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? 42

VNE Evaluation with ALEVIN 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 Software available on: http://alevin.sf.net/ Lots of metrics to compare (common and more exotic) 43

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 44

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 45

References Berl, A.; Fischer, A. & de Meer, H. Using System Virtualization to Create Virtualized Networks. Workshops der Wissenschaftlichen Konferenz Kommunikation in Verteilten Systemen (WowKiVS2009), EASST, 2009, 17 Berl, A.; Fischer, A. & de Meer, H. Virtualisierung im Future Internet - Virtualisierungsmethoden und Anwendungen. Informatik-Spektrum, 2010, 33, 186-194 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 Fischer, A.; Fessi, A.; Carle, G. & De Meer, H. Wide-Area Virtual Machine Migration as Resilience Mechanism. Proc. of the 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. Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2, USENIX Association, 2005, 273-286 Anderson, T.; Peterson, L.; Shenker, S. & Turner, J. Overcoming the Internet Impasse through Virtualization. Computer, IEEE Computer Society Press, 2005, 38, 34-41 Feamster, N.; Gao, L. & Rexford, J. How to Lease the Internet in Your Spare Time. ACM SIGCOMM Computer Communication Review, 2007, 37, 61-64 Wang, Y.; Keller, E.; Biskeborn, B.; van der Merwe, J. & Rexford, J. Virtual routers on the move: live router migration as a network-management primitive. SIGCOMM Comput. Commun. Rev., ACM, 2008, 38, 231-242 Chowdhury, N. M. K. & Boutaba, R. A survey of network virtualization. Computer Networks, 2010, 54, 862-876 Goldberg, R. P. Survey of Virtual Machine Research. Computer, 1974, 7, 34-45 Fischer, A.; Botero, J. F.; Beck, M. T.; De Meer, H. & Hesselbach, X. Virtual Network Embedding: A Survey. IEEE Communications Surveys and Tutorials, 2013, 15, 1888-1906 46