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Network Virtualization as a Mean for Service Convergence for Future Communication Systems – What can we learn from Federated Experimental Facilities? K.

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Presentation on theme: "Network Virtualization as a Mean for Service Convergence for Future Communication Systems – What can we learn from Federated Experimental Facilities? K."— Presentation transcript:

1 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) Chair of Future Communication Prof. Dr. K. Tutschku Institute for Multimedia and Distributed Systems Faculty of Computer Science

2 Future Internet? ?

3 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

4 Access networks Core networks Internet under Pressure  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?

5 GSM Teletext Data service Service provider Network operator Services Applications class. national PTT POTSMobile ISDN Voice (wired) Voice (cellular) Reseller A X.25 / FR Networks under Change: Services  Limited convergence

6 GPRS Web IP service Service provider Network operator Services Applications A B C DE IP Service Provider POTSmobile ATM/ MPLS  Limit convergence  Internet Protocol (IP) is main converging layer Networks under Change: Services

7 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 broad- band internet?” (E2E-interest mailing list on April 26th, 2008); contracts prohibit change  No convergence; even technically infeasible

8 UMTS Web.Unified communication appl. IP Service xDSL WLAN PSTN Service provider Network provider Services Applications Multi-Network Services Voice Overlays (e.g. Skype) Video Messa- ging Data  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 A BCDE IP Service Provider Networks under Change: Services

9  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-*? ? ? provider at edge of network Data/ Service distributed centralized Network-based provider (server) Data/ Service consumer at edge of network Networks under Change: Services

10  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: Services

11 Head- quarter ATM E3 Management plane Remote office Service request (FAX, Web) „semi-manual“ provisioning Networks under Change: Transport Systems

12 Control Plane Head- quarter IP layer 100GE layer DWDM layer EPON auto. provisioning Management Plane  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? auto. Signaling Remote office Multi- Layer- Networks Networks under Change: Transport Systems

13 Success of the Current Internet  Efficient P2P-based, self-organizing content distribution networks  Ratio of data traffic types at public access node  Data traffic by IP TV P2P, 67,3% eMail, 1,2% FTP, 0,3% other, 23,3% Web, 7,9% Quelle: Telefonica (2003) 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 200025.000 US. Internet back bone at year end 19986.000 Quelle: CISCO (2008)

14 Multi-Source Download (eDonkey, BT) Publish X Query X Transfer of segment A Offers file X Peer Index server Looking for X Query X Transfer of segment B Publish X Offers file 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

15 Diversity I: Multi-Provider Environment  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 compe- tition are (theoretically) readily available! ☝ Network selection not available in current IP  no convergence  Any way: autonomous identi- fication of available resources needed (Thanks to Michael Menth für vsualization) East coast West coast

16 Diversity II: Multi-Quality Environment  25% of paths violate the triangle inequality (wrt. packet delay)  Measurements in PlanetLab by S. Banerjee et al. (2004) ➞ Internet routing is far from optimal ➞ Better paths exist; capazity is readily available ➞ Can be offered (competition) ➞ Again: autonomous identification of available resources needed ! „Multi-homing“ not really available current IP protocols A Triangle Inequality (TI): D(A,C) ≤ D(A,B) + D(B,C) BC direct connection Using an intermediate

17 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

18 Virtual Networks for Convergent Services  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 Convergence by Network Virtualization Diversity  Exploit diversity of resources by smart localization  Provide optimal resources OS virtualization  Strong isolation of resources  Consolidation and efficient operation  Enables local convergence Overlays  Overlays: application-oriented topology, addressing, and routing  Multi-Network Services  Self-operation of functions  Enables global convergence

19 Share Virtual Machine Guest OS Virtual CPU Virtual Memory Virtual I/O CPUMemoryI/O Virtual Machine Monitor Guest OS Virtual Machine Servic e Aggregation Load Balancer Servic e Logical Virtual Server Load Balancer Switch Physical Server A Formal Description for Virtualization  Virtual resources  Generation of logical resources  Sharing: one physical, multiple logical resources  Aggregation: one logical, multiple physical

20 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  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 A. Nakao T. Zinner, P. Tran-Gia

21 Concurrent Multi-Path Transfer Physical topology Overlays of provider I Overlays of provider II Aim: Very high and reliable throughput between two end hosts Aim:Very high and reliable transmission between two end hosts Solution: Transport Virtualization: Combine multiple paths (even from different overlays) pooled transport pipe POP

22 Path oracle One-hop Source Router (SOR) Routing Overlay (= P2P Multi-Source Download) Implementation: routing overlays Gummadi et al (2004):Scalable “One-Hop” (= intermediate) routing overlays Nakao, Tutschku, Zinner:Consideration of multiple paths (2008) ! 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? 1 Divert selected endhost packets 2 Request Paths for Diverted Packets 3 Encapsulated, send using path 4 Decapsulate, egress to destination

23  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 prede- fined lifetime GENI: The Global Environment for Network Innovation

24 Appealing Idea: Federation Backbone #2 Compute Cluster #1 Backbone #1 Compute Cluster #2 Wireless #1Wireless #2Access #1 Corporate GENI suites Other-Nation Projects Other-Nation Projects My experiment runs across the evolving GENI federation. NSF parts of GENI My GENI Slice (Slide by Chip Elliot)

25 What resources can I use? Components Aggregate A Computer Cluster Components Aggregate B Backbone Net Components Aggregate C Metro Wireless Offer GENI Clearinghouse Researcher Aggregates publish resources, schedules, etc., via clearinghouses Resource Discovery (Slide by Chip Elliot)

26 GENI Clearinghouse Components Aggregate A Computer Cluster Components Aggregate B Backbone Net Components Aggregate C Metro Wireless Create my slice Clearinghouse checks credentials & enforces policy Aggregates allocate resources & create topologies Slice Creation (Slide by Chip Elliot)

27 Components Aggregate A Computer Cluster Components Aggregate B Backbone Net Components Aggregate C Metro Wireless Experiment – Install my software, debug, collect data, retry, etc. GENI Clearinghouse Researcher loads software, debugs, collects measurements Experimentation (Slide by Chip Elliot)

28 Components Aggregate A Computer Cluster Components Aggregate B Backbone Net Components Aggregate C Metro Wireless Make my slice bigger ! GENI Clearinghouse Allows successful, long-running experiments to grow larger Slice Growth & Revision (Slide by Chip Elliot)

29 Components Aggregate A Computer Cluster Components Aggregate B Backbone Net Components Aggregate C Metro Wireless Make my slice even bigger ! GENI Clearinghouse Components Aggregate D Non-NSF Resources Federated Clearinghouse Growth path to international, semi-private, and commercial GENIs Federation of Clearinghouses (Slide by Chip Elliot)

30 Components Aggregate A Computer Cluster Components Aggregate B Backbone Net Components Aggregate C Metro Wireless GENI Clearinghouse Federated Clearinghouse Components Aggregate D Non-NSF Resources Always present in background for usual reasons Will need an ‘emergency shutdown’ mechanism Oops Stop the experiment immediately ! Operations & Management (Slide by Chip Elliot)

31 Routing Overlay used path Routing Overlay pooled ressource Routing Overlay I Routing Overlay II pooled ressource Federation for Transport Virtualization Path selection Path selection for concurrent use Path selection in federated networks  convegence of networks

32 Transmission Model p 1,1 dst Assumption: use k parallel paths on m overlays p 1,n1 p m,1 p m,nm src k pooled paths With paths Data stream divided at router into segments with k parts 1 k 2 k parts have arrived k parts are send in parallel at time t k-1 each provider will offer a set n i of parallel paths (i = 1…m)   1 k overlay 1 overlay m  Buffer occupancy? Reassemble data stream from obtained parts Re-sequencing buffer of size L  Scheduling?

33 So far: Simulation Experiment Input: Number of paths Scheduling Output: Re-sequencing buffer occupancy distribution  Search for path selection strategies; future on-line selection for convergence Path delay distributions Path capacity SourceDestination

34 Impact of Type of Delay Distribution I Types of distributions: Uniform: artificial behavior Truncated Gaussian: mathematical tractability Bimodal: two modes of a path Investigation of different influence factors Delay

35 Impact of Type of Delay Distribution II Two synchronous, equal capacity paths Three synchronous, equal capacity paths Buffer  Highly non-linear  careful and complex path selection Buffer

36 Current Work: Perform Real-World Measurements  Measurement set-up  Gain realistic parameters and strategies

37 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

38 Thanks for your attention! Questions?


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