1. 1 Mobile CORD and Proposed Use Cases August 2015 ON.Lab, SK Telecom, and AT&T

2. 2 Mobile Operators Wishes Reduce content delivery cost over mobile networks Open CPRI model: White-box, Disaggregated eNB, vRAN Distributed Core: EPC disaggregation Mobile resource slicing: local MVNO and enterprise Revenue cooperation with over the top Real-time analytics for network aware applications Improve QoE and drive service innovation Customized service chaining and policies

3. 3 ROADM (Core) Commodity Servers, Storage, Switches, and I/O PON OLT MACs Leaf-Spine Fabric BBUs (Multi -RATs) ONOS (Virtualization, Slicing) + OpenStack (Multi Domain) + XOS 4G Virtual infra + ONOS + mobile edge over multi-RAT 4G Virtual infra + ONOS + mobile edge over multi-RAT 5G Virtual infra + ONOS + mobile edge over multi-RAT 5G Virtual infra + ONOS + mobile edge over multi-RAT Residential Virtual infra + ONOS + vOLT, vCPE, vBNG, vCDN Residential Virtual infra + ONOS + vOLT, vCPE, vBNG, vCDN Enterprise Virtual infra + ONOS + VPN, TE, vCDN Enterprise Virtual infra + ONOS + VPN, TE, vCDN … Infra Slices Enterprise Metro Ethernet CORD and Target Domains of Use

4. 4 Mobile CORD: Big Architecture Picture Networking Fabric Front-haul Optical Switch CPRI (E) Disaggregated BBUs Edge Service Functions Distributed EPC CORD Platform Control Apps. Centralized EPC Backbone Switch Video Caching DNS Security SGW-D PGW-D XOS MME OpenStack ONOS PCRF SGW-D PGW-D vBBU Operator’s specific Applications Mobile Resource & Service Orchestration CORD Platform (ONOS + XOS + OpenStack) Radio Resource Scheduling Network Slices LTE,5G IoT Enterprise Real-time Analytics MBB MVNO Testbed Service Chaining SGW-C PGW-C SGW-D, PGW-D: Data plane of SGW/PGWSGW-C/ PGW-C: Control plane of SGW/PGW … Orchestration View Topology View

5. 5 POC For Mobile CORD

6. 6 POC Goals of Mobile CORD 1. Back-End: Bring service functionality of mobile core to the edge 2. Front-End : Realize the Values of eNB disaggregation Capex, Opex Data Plane Programmability Increased Radio Resource Optimization Unified QOS support Increased RAN Performance L4-L7 Service chaining at the edge Cache @ Mobile Edge Disaggregated EPC @ Mobile Edge Localized Service customization QOS Eliminate Inefficiencies Realize all Benefits of CORD Data Center Economics Agility of Cloud

7. 7 POC #1 Back-end POC :Services at Mobile Edge By bringing service functionality and disaggregated EPC to mobile edge under the framework of CORD, Improve operators’ agility, efficiency of network utilization and enhance users’ QoE POC #1

8. 8 Problem Statements  All traffics are gathered to the center of mobile core, which cause  Operators over-provision their infrastructure to cope with peak traffic ▫ It’s inefficient to have surplus systems to handle peak traffic ▫ Deploying new infrastructure takes long time; a couple of months ▫ Traffic surge varies with time and location ▶ Efficiency, Agility and Scalability are essential for operators to keep up with rapid growth and dynamic characteristics of mobile traffic ▫ load on backhaul, backbone transport and core systems like SGW/PGW ▫ waste of network resources from operators’ perspective ▫ deterioration on QoE from users’ perspective Video email Voice Edge Backhaul Core POC #1

9. 9 Solution and benefits ▶ Services at mobile edge - Certain contents like streaming of same video can be served at mobile edge without traversing from and to the mobile core ▷ Benefits : ▫ Decrease burden on backhaul and mobile core ▫ Increase QoE of users ▶ On-demand provisioning - Virtualized infrastructures can be deployed when and where they are to be consumed on demand ▷ Benefits ▫ Avoid inefficient provision of infrastructure ▫ Agile action for dynamic traffic request Local Traffic Non-local Traffic POC #1

10. 10 POC Scenario RRH  Local video streaming service at mobile edge ▫ On-demand provisioning of vBBUs at cell sites near big sport match ▫ On-demand provisioning of video caching application(VM) for local video caching service ▫ Functions like DNS and DPI also need to be deployed locally for traffic classification ▫ Other traffic of spectators is treated same as before; travers from and to the Centralized Core vBBU Pool Edge Service EPC Local Traffic POC #1 Mobile CORD (Distributed DC)  Local communications hosted by distributed EPC ▫ Virtualized EPC can also be deployed to host local and internal communications - Communication between security staffs - Remote monitoring of Security CAM

11. 11  BBU: Servers hosting VMs of BBU function  Edge Service Functions: Servers hosting VMs of service functions like DPI, DNS and Video caching  Distributed EPC: Data plane of disaggregated EPC (possibly white boxes)  Control Applications: Control plane of disaggregated EPC as northbound applications of ONOS  Mobile CORD Platform: Servers hosting control S/Ws like XOS, OpenStack and ONOS  Mobile CORD Fabric: White-box switches networking mobile edge components POC Implementation POC #1 Networking Fabric Front-haul Optical Switch CPRI (E) Disaggregated BBUs Edge Service Functions Distributed EPC CORD Platform Control Apps. Centralized EPC Backbone Switch Video Caching DNS Security SGW-D PGW-D XOS MME OpenStack ONOS PCRF SGW-D PGW-D vBBU SGW-C PGW-C SGW-D, PGW-D: Data plane of SGW/PGWSGW-C/ PGW-C: Control plane of SGW/PGW

12. 12 POC Implementation (S/W Architecture)  XOS ▫ Orchestrate infrastructure services (by OpenStack) and control services (by ONOS)  OpenStack ▫ Responsible for provisioning VMs and virtual networks  ONOS ▫ Manages switching fabric ▫ Forwarding control: ‘video traffic’ to local edge service servers and distributed EPC and other traffic to centralized EPC  Applications ▫ Video content caching ▫ DNS ▫ DPI ▫ MME, PCRF, SGW-C, PGW-C POC #1

13. 13 POC Plan  POC Target: March 2016 (ONS Summit)  Detailed Plan: TBD Dec. 2015 OCT. 2015 Integration Solution Sourcing Implementation with partners Solution Sourcing Implementation with partners Design Lab Trial XOS modification ONOS modification (OF wireless extensions) OpenStack modification vBBU implementation Disaggregated EPC implementation Application modification Jan. 2016March 2016 Test POC Demo POC #1

14. 14 POC #2 Front-end POC :Realize the Values of eNB disaggregation

15. 15 Front-end Problem Statements  Today eNBs are proprietary and non-interoperable among vendors and expensive resources such as radio is at the mercy of proprietary vendor algorithms  Certain Control Functions such as schedulers are vendor specific  New Mobility Services introduction are not agile  Localization and adaptability to zones, time of day, and traffic behaviors are limited Compression Handover forwarding Ciphering Segmentation Retransmission HARQ Antenna & Resource Scheduling MCS MIMO Mobility Control Security Configuration Flow QoS Load Balancing Scheduling CoMP Power Control PDCP RLC MAC & PHY Data Plane Proprietary Control Plane POC #2

16. 16 CORD Interface ( OF Wireless Extensions) Physical Layer 5G, 4G, LTE, WiFi (Coding, Antenna, MIMO, OFDM, dark silicon, Power Mgmt, Probes, CPRI-End-Point …) Plug-in cards MAC Layer (ARQ, Burst Allocation, FEC, Probes, Converged Channel, CPRI-End-Points) Protocols, Tunnel Management …. Transport and IP Layers (TCP/UDP, IP, RTP, …) Scheduler Parameters: QCI Assignment, Buffers, … CORD Applications (Mobility Control, higher layer scheduler & traffic characterization, load Balancing & QoS functions, Handoff and Radio Resource Optimization, Congestion avoidance & Customer Care) BBU, RRU Resource Abstraction CORD BBU POC #2 eNB Disaggregation Model

17. 17 POC Solutions & Benefits CORD to enable dynamic CPRI switch for mobility dimensioning RAN abstraction and small cell splitting with auto interference control & discovery Intelligent access network selection and routing (multi-RATs) Vehicular secured VPN service Elastic Fixed LTE Service (Wireless fixed BW on demand with 8x8 MIMO ) Mobility Control Security Config Flow QoS Load Balancing Scheduling CoMP Power Control CORD Apps X1 over OF Interface RRH Wi-Fi hotspots RRH Compression Handover forwarding Ciphering Segmentation Retransmission HARQ Antenna & Resource Scheduling MCS MIMO BBU Racks CPRI Future(IQ over Ethernet) POC #2 Wi-Fi hotspots

18. 18 Hybrid, Programmable eNB Data Plane Mobility Control Security Configuration Flow QoS Load Balancing Scheduling CoMP Power Control Virtualization Layer Controller CORD interface Compression Handover forwarding Ciphering Segmentation Re-TX HARQ Resource Scheduling MCS MIMO Re-TX HARQ Resource Scheduling MCS MIMO Re-TX HARQ Resource Scheduling MCS MIMO COT S DSP RRH CORD BBU CORD-APP POC #2

19. 19 Implementation Approach BaseBand Plug-Ins Open OS Data Plane Func. Features Control plane Hardware Closed MOBILE CORD PLATFORM Control Apps Mgmt Apps Serv. Apps Features Control plane Hardware BBU Servers POC #2

20. 20  BBU: disaggregated control function from data plane Edge  Mobile CORD Platform: Mobility Treatment and traffic functions among  v BBUs Mobile CORD Fabric: White-boxes; LTE, 5G BBU signaling stack and RRC functional components Implementation L4-L7 Services ONOS, XOS, Open Stack eNB Control / Optimization Applications RRH Mobile Backhauls FrontHaul Optical Switch Leaf-Spine Fabric Operator’s specific Mobility Management Applications Scheduler Policies, QOS, Security, IOT, Load & congestion Policies, SON Mobile Resource & Service Management CORD Platform FPRF & FPGA Lime-micro Altera( CPRI-End-Point) Disaggregated BBUs CPRI (E) CPRI-O/E CPRI-End-Point POC #2

21. 21 RAN + EPC + Mobile NFV Virtualization Small Cells Macro RRU CPRI/ETHER Leaf-Spine Fabric Mobile Resource & Service Management BBUs EPC Services ONOS, XOS, Open Stack CPRI-O/E CPRI-End-Point POC #2

22. 22 CPRI Switching Scenario Mobile Edge Virtualized RAN/BBU sharing RRUs, and Micro Cells POC #2

23. 23 Longer Term Mobility Management Wish list Autonomous Load balancing among eNBs/BBUs Control eNB/BBUs treatment for different traffic types Controlled handover for best utilization of radio resources Minimize # of tunnels for mobile services Demonstrate opportunity for Mobility on Demand Demonstrate Multi-homing instead of single home Opportunities for different kinds of eNBs that are not bearer specific Demonstrate on demand analytics and instrumentation of probes for autonomous control, optimization, and customer care POC #2

24. 24 POC Plan Component 20152016 3Q4Q1H2H Disaggregated BBU ONOS Applications Solution Sourcing Modification / Develop Develop Modification / Develop  POC Target: `2Q, 16  Detained Plan: TBD Integration Test POC #2

25. 25 CORD Realization Benefits Summary 1.Data Center economy 2.Agility of Cloud 3.MVNO Model ( third Party) 4.Mobile Edge architecture maps nicely to CORD architecture 5.OF enabled eNBs can be architected like vCPE & vOLTe 6.Netconf enabled eNB can accept configuration and policy updates in real time 7.Edge Cloud can support emerging services such as IOT, Big data, social & internet 8.XOS Instrumentation as a service maps perfectly to Real-time network data analytics to Improve infrastructure’s efficiency, with more intelligent and optimized networks.

26. 26 Backups

27. 27 Mobile CORD: Mapping to Future Infrastructure Centralized DC SGW-D DB HSS. Distributed DC PGW-D Control Platform & Applications

28. 28 Slice#1 Orchestration – CORD (XOS, OpenStack, ONOS) Centralized CORE HW/SW Resources (VNFs, MME, SGW, PGW, PCRF, SON, Mobile Control Applications) Mobile Edge HW/SW Resources RAN HW/SW Resources (BBU, RF, RRH, Spectrum Pool, Backhauls…) Slice#2Slice#3Slice#4 Mobile Edge HW/SW Resources Resource Recomposition vBBU, vRAN, vEPC, VNFs Distributed CORE HW/SW Resources (SGW, PGW, Edge Services / MME, PCRF, SON, Mobile Control Applications) Mobile CORD: Network Slicing example

29. 29 “Prior to the advent of software such as OpenBTS and OpenBSC, many would have deemed GSM to be too complex and arcane a technology for a community of open source developers to tackle. However, those who thought this to be the case have, like early Linux detractors, since been proved wrong thanks to a growing community of talented engineers who are committed to open source.” https://myriadrf.org/blog/open-source-lte/OpenBTSOpenBSC https://myriadrf.org/blog/open-source-lte/ “OpenLTE“OpenLTE is developed by Ben Wojtowicz and the first release was made in late 2011. At present GNU Octave code is available for test and simulation of downlink transmit and receive functionality, along with uplink PRACH transmit and receive. In addition, GNU Radio applications are available for downlink transmit and receive to and from a file, and for receive use with a selection of SDR hardware. More recently, a simple eNodeB application has been added.”GNU OctaveGNU Radio “The bladeRF is the first open source RF project to bring USB3.0 onto the board and combines the Lime FPRF chip with an Altera Cyclone IV FPGA. This combination allows it to create exceptionally complex networks on any mobile communications standard or frequency. The $420 board has been designed for both the hobbyist and the professional developer and is also USB2.0 compatible, allowing it to connect directly to the Raspberry Pi and the Beagle board too.?” Open Source References

30. 30 Use case Mobile CORD Use CaseRequirements 1) Performance KPIs: anomaly detection, RCA, and mitigation -Real-time or near real-time nature. Data should be available with low latency. -Granularity can be in seconds or minutes. -Identify anomalies in performance KPIs across time and space. Drill-down to specific root- cause. E.g., is only 1 eNB impacted or entire market? Is only one device class or service type impacted? Or is it not even a network issue, but end-point (service provider) issue. -Take corrective action to mitigate or eliminate the problem if possible. E.g. load balancing, power control, others. -Predict user performance/QoE before and after corrective action and choose best option. E.g. will a user be better served by hand-off or by changing QoS parameters.

31. 31 Use case Mobile CORD Use Case Autonomous Control Requirements 2) HotSpot Solutions: Identification of trouble-spots and solutions. -Real-time decisions to long-term planning -Granularity can be in seconds or hours/days. -Identify persistent hotspots with high usage/load based on historical trend. -Identify mitigation options for short-term (re-direct other base stations, load balancing, hand- offs, etc.) and impact on user QoE. -Identify transient hotspots and mitigation options. E.g. base stations along a freeway may be congested during commute times only. What is the cost-benefit analysis of adding new sites for such scenarios? -How to densify the network based on this hotspot info: what technology may be appropriate (small cells, DAS, WiFi, others), based on network and user information (user concentration, data or voice heavy, user mobility, etc.). Cost-benefit analysis of different approaches if possible.

32. 32 Use case Mobile Cord Use CaseRequirements 3) Admission control: Congestion detection & QoS solutions. -Real-time or near real-time nature. Data should be available with low latency. -Granularity can be in seconds or minutes. -In a given scenario (during peak congestion times, in high-cap venues, or presence of premium users), identify which apps/services can be given low priority based on service parameters, user preferences, network settings, etc. E.g., should we take resources from m2m users on the cell, or maybe delay email download or ftp session? -During congestion, identify which parameters can be tuned to better manage resources. E.g., priority based on ARP, resource allocation based on QCI, max speeds based on MBR, others. Analyze impact of multiple options in real-time and select best approach. -Help avoid dimensioning for peak loads or busy hours with intelligent traffic management.

33. 33 Use case Mobile CORD Security Use Case Big Data Analytics Requirements 4) Security anomaly detection-Fine-grained data required. 5) End-to-end flow detection and classification-How do we track a flow across multiple servers/VMs? -Is there any impact on flow performance from compute/network/storage performance? -What happens to user data when VMs go down or fail? Impact on QoE?

34. 34 ONOS Application Examples  RAN management Application Examples: ▫ Load balancing ▫ Power Control ▫ Interference coordination  Virtualized eNB ( Basebands) are programmed to send network events over X1/OF ▫ CSI and flow state records to ONOS controller ▫ Controller maintains network graph, link quality, CSI and flow demand tables  RAN management applications to program the ONOS wireless graph abstractions (eNBs) to coordinate the use of the shared radio resource and implement functions such as CoMP, Interference mitigation, Radio optimization

35. 35 Source: Sachin Kathy ONOS Controller ↔ Data Plane Interface  Interface is match/action, where: ▫Match: Matches on UE IDs, GTP Tunnel IDs and Flow IDs ▫Action: Is a packet processing pipeline that has to be executed for the matched set of packets Spans PDCP to L1 Specifies handover forwarding rules (if any), segmentation parameters, resource block (spectrum) assignments, MIMO streams and the L1 stack to be used for processing the packet Enables precise control over how the radio resource is allocated and used

36. 36 RRH Distributed DC Virtualized BBU Pool eNB Data SON SDN Controller Backhaul Existing Solution New Area Back-Bone Transport Fronthaul  SON & Fronthaul/Backhaul Control Today, SON has been focused on the optimization of Remote Radio Head only Intelligent control of Fronthaul/Backhaul could be achieved by making full use of analytics derived from SON Main Features; -Neighbor Mgmt. -H/O Optimization -Fault Mgmt. -Diagnosis  All those are for RRH Mgmt. Possible Features; - BW Scheduling of Backhaul - On-demand BW allocation - Failure(of vBBU) Mgmt. Useful Analytics can be used for Fronthaul/Backhaul control SDN combined with SON

37. 37  Networks for the Customers’ needs (SLA) Traditional: One network for all purpose with same architecture and configuration Trend: Network Slices to meet specific demands of customers and services (Network as a Service) [ Concept References ] ※ Reference: NGMN ※ Reference: SK Telecom Key Enablers for Network Slicing - Abstraction of network functions -Programmability of Networking -End to End Orchestration NFV SDN Network Slicing

38. 38 [ Traditional EPC Architecture ] [OpenFlow enabled EPC Architecture ]  CP/UP Separation For the full Flexibility of Packet Core in handing ever-growing traffic, UPs must be separated from CPs and White-Boxes may replace them. eNB (BBU) Distributed GW (SGW-U) PGW-CMMESGW-C Internet eNB (BBU) SGW PGW MME Internet HSS PCRF S1-MME S6a S1-U S5 S11 Gx SGi (Dotted line) Control I/F (Solid line) User Traffic Control/User Plane Integrated GW OpenFlow* Distributed GW (SGW-U) Distributed GW (SGW-U) Distributed GW (PGW-U) SGi User Plane of Distributed GW (SGW) User Plane of Core GW (PGW) Decoupled Control Plane of SGW/PGW Enhanced- OpenFlow (Solid line) User Traffic SDN Controller PCRF Control plane is tightly coupled with Data plane(User plane) Limited Scalability of Data plane Distributed Management High CapEx/OpEx Disaggregate Control plane and User plane Logically centralized control and Programmable White-box User plane. Scalable with data traffic growth Reduce CapEx/OpEx EPC disaggregation (UP/CP decoupling)

39. 39 Sd L7 Traffic Classification Virtualization Platform User Profile & Policy Control  L4-L7 Service Aware Chaining Traffic is steered through the appropriate L4-L7 network functions for a given flow, based on service type, user profile, traffic patterns, or other characteristics. 3GPP defined Sd interface between PCRF and TDF to detect service traffic and to apply policy TDF PCRF Service Aware Chaining