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Nomadic Virtual PC: A user Case for Network and Distributed Cloud Interworking

Nomadic Virtual PC: A user Case for Network and Distributed Cloud Interworking. Telefónica I+D. Key messages. Video and cloud computing demands are stressing the network. 1. Core network operation and capacity should be adapted to new services demands . 2.

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Nomadic Virtual PC: A user Case for Network and Distributed Cloud Interworking

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  1. Nomadic Virtual PC: A user Case for Network and Distributed Cloud Interworking Telefónica I+D

  2. Key messages • Video and cloud computing demands are stressing the network 1 • Core network operation and capacity should be adapted to new services demands 2 • New transport architectures based on E2E MPLS and optical transport will pave the path towards Cross Stratum Optimization and enable new services such as Nomadic Virtual PC 3

  3. Video and cloud services are stressing the whole network Data center C Core/Metro network Data center A Data center B • Intra Data Center connectivity • Use cases • DC resource and energy optimization • Distribute computation jobs • Characteristics • Elasticitytoefficientlyservethecomputingjobdemands • Hugenumber of connectionsbetween servers • Ultra highcapacity : “a data center with 100,000+ servers would require an internal network with 4 Petabits/sec”. Google OFC 2011 “The Emerging Optical Data Center” • Inter-Data Center connectivity • Use cases: • Content replication • Bulk transfers • Redundancy • Database sync etc. • Characteristics: • Flexibility to replicate content along the network • Few number of point to point high capacity connections • Bandwidthvariability • Lowlatency (e.gdatabasesync) Access Network • End-User to Data Center connectivity • Use cases: • Access to CDN End Point • Virtual Machines hosted in the cloud • Corporate Elstic VPNs • IPTV / VoD • Characteristics: • Huge number of connections • Multiservice • Low delay for cloud based services • Latency requirements for video based services Home users Enterprises

  4. Video and cloud connectivity requirements Capacity: Video traffic increase is driving a CDN based video network architecture “ There is a strong need for high-capacity as well as ultra-long haul unregenerated reach between Datacenters” [Google, OFC 2011 Drivers and Applications of Optical Technologies for Internet Data Center Networks Intra-cloud network bandwidth variability (8 case studies) Elasticity: Cloud traffic demands will have unprecedented bandwidth variability “Variable rate transmission has to be tightly integrated with the packet layer and managed at the system/network level to realize the overall throughput maximization”. [Google, OFC 2011 Drivers and Applications of Optical Technologies for Internet Data Center Networks Source: Towards predictable datacenter networks, SIGCOMM 2011 Virtual Machines deployments vs physical servers QoS: Traffic differentiation over the same infrastructure (video, data, voice, bulk, etc) Service experience in the Virtual Machines hosted in the cloud must be equivalent to the one perceived in a LAN

  5. Network operation and capacity should be adapted to new traffic demands Current Approach: Over-provisioning and static connectivity between Access Nodes and Data Centers Cloud Ready Network: Flexible connectivity services (e.g bandwidth variability) • CDN and cloud enabled networks must support: • …an extensive amount of requests from CDN and cloud data centers while the rest of traffic remains unaffected. • …BW and QoS assurance between end users and CDN/cloud data centers (e.g real time applications, data base sync, etc) • …flexible networking services enabling on demand fast data transfers between CDN/cloud data centers (e.g mirroring, redundancy, etc) • …high capacity and scalability • …costs optimization (data center and network) • …responsiveness to quickly changing demands • …enhanced service resilience (via cooperative recovery techniques between data centers and network) • …QoS enhancement (via better use of existing network and data center ) • High cost • Rigidness • Application unaware • Reduce cost (unused resources) • Flexibility • Application adapted • However current core connectivity services do not fulfill most of these requirements Connectivity services Core Architecture Cloud and Video Ready networks will enable flexible connectivity services specially adapted to CDN and Cloud requirements

  6. Key Technologies behind cloud ready networks MPLS, an intermediate IP layer, could be used to unify Transport and Aggregation segments, reducing E2E operation costs. Extension to Access segment will improve even more the network efficiency. Key Technologies: Seamless MPLS, MPLS-TP E2E MPLS IP/MPLS Network Coordination between Optical transport layer and IP layer faces traffic growth in an economically efficient way by better resources usage. Key Technologies: IP offloading, multilayer restoration, multilayer planning Routing, montitoring and automated IP configuration Routing, montitoring and automated Photonic network configuration Photonic Mesh is a real Network: it offers flexibility and scalability using a photonic control plane(like routing in IP networks) Key Technologies: GMPLS (Generalised Multiprotocol Label Switching),Hierarchical PCE (Path Computation Element), E-NNI (External Network to Network Interface) Photonic control plane GMPLS + PCE Multilayer Coordination Signalling Better transmission technologies will allow increase capacity of existing fiber links Key Technologies: Subwavelength Switching, elastic optical networks PHOTONIC MESH

  7. These network technologies will pave the path towards joint network and cloud optimization by enabling.. • Flexible service platform design since service nodes (VM server, IPTV head end, BRAS or even the CDN end/entry points) may be located anywhere in the network. • Automated connectivity between access and service nodes since access nodes will be able to automatically reach any service node (e.g CDN end points, cloud servers, etc) if required, enhancing the network reliability and survivability, and optimizing the traffic distribution. • There exist a standardization initiative within IETF “Cross Stratum Optimization” working on new control plane paradigms for a joint network and cloud optimization

  8. Example of Use case: The Virtual PC The service: End-userequipmentleverageshigh performance computation and storagecapacities of runningVMswithin a datacenter. The rational behind: Simplerterminals (e.gpowerefficientemobiledevices). VMsrunwithin a datacenterwithgrantedperformance and reliability. … Access node A Data Center Corenetwork The issues: Access Node B Massivepenetrationmayentail: - Network (Bandwidth) bottleneck at the Data Center - Difficulties in bandwithscalability - Multiplenetworksegmentsinvolved in eachconnectivityservice - High number of connectionsthroughthecore - Severalserviceclasses in thecore … High stress in thecorenetwork highcost

  9. Example of Use case: The Virtual PC A distributed data center makes up a sound business case Corenetwork (MPLS/Burstswitching) Distributingthe data center betweentheaccessnodesbringsend-user Vs. VM interactiontothenetworkedge, drivingto: AN AN AN • Lowdelay • Betterbandwidthscalability • Small packetsremain in theaccessnotthecore • A uniqueserviceclass in thecore • Overspillin thedynamicnetworkensuresservicecontinuity, restoration and data replication Provisioning of VM service

  10. E2E MPLS and photonic transport enable a smooth service deployment from initial centralized approaches towards distributed data centers (e.gcolocated with VoD servers) Example of Use case: The Virtual PC Data Center A Data Center B Bulk data transfer from DC A to DC B High network load toaccess DC A VM of nomadicuseristransferredto local AN Access Node D E2E MPLS photonicnetwork Access node A VM of nomadicuseristransferredto local AN Access NodeC Access Node B

  11. Example of Use case: The Virtual PC • Field trial in Crypus over Primetel network using Intunesubwavelength switching technologies among servers and access nodes www.ist-mains.eu

  12. In summary • Network architecture should be updated in order to fulfil the requirements in terms of capacity, QoS and elasticity from new video and cloud applications. A combination of E2E MPLS and photonic transport are the most efficient and mature solution available 1 E2E MPLS and photonic transport will pave the path towards joint network , CDN and cloud optimization 2 3 A distributed server approach makes up a sound business case for nomadic Virtual PC services 4 E2E MPLS photonic networks enable a smooth service deployment

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