The Role of Big Data & Advanced Analytics in SDN/NFV. Moderated by Jim Hodges, Senior Analyst, Heavy Reading June 9, 2015

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1 The Role of Big Data & Advanced Analytics in SDN/NFV Moderated by Jim Hodges, Senior Analyst, Heavy Reading June 9, 2015

2 DAY 1 TUESDAY, JUNE 9, :00 4:00 PM BREAKOUT ROOM #4 VIRTUALIZATION The Role of Big Data and Advanced Analytics in SDN/NFV Moderator: Jim Hodges, Senior Analyst, Heavy Reading Panelists: Ashish Singh, GM/VP, Products, SK Telecom Scott Sumner, VP, Solutions Marketing, Accedian Networks Mike Heffner, Senior Director - Technical Product Marketing, Overture Networks John Govert, Chief Technologist, Network and Service Enablement, JDSU #BTE2015

3 Agenda Presentations (10 minutes) Panel Discussion (40 minutes) Q&A (10 minutes)

4 Big Data, SDN/NFV Transition from ARPU to ARPExperience

5 Business transformation with Big Data Build new revenue sources Service Usage Advertising Media Services Big Data Sources Optimize Experience Improve bottom line efficiency Increase Automation Eliminate redundancy Streamline Process 5

6 Big Data Maturity Model Level 0 Fragmented Point Solutions Overlapping Content Disparate Infrastructure Level 1 Managed Enterprise Data Warehouse Data silos and hubs with limited integration Limited Data Discovery Level 2 Systematic Standardized vocabulary across data source Consolidated infrastructure Enterprise level data definition Level 3 Advanced Industry standard metadata collection Agile and consistent reporting Enterprise scale data reservoir Level 4 Innovative Predictive and suggestive analytics Synchronous data collection and reporting Prescriptive process integration across the enterprise 6

7 Real-time data processing as 5G network foundation Provide insight on a specific event by analyzing large volume of multidimensional unstructured data Descriptive Analysis Predictive Analysis Prescriptive Analysis Improve network usability and performance using performance data from elements in real-time SON, sophisticated anomaly detection and network traffic congestion prediction using correlation on the edge 7

8 Network Intelligence RAN Analytics based Network Intelligence Ability in real-time to correlate RAN KPI s and manage service experience Small Cell RAN Access Network vra N en B Call Flow, RF Signal, Network Status, Resource Scheduler Big Data Analytics Platform RAN Analytics cases System Analytics Radio Analytics Protocol Analytics Traffic Analytics User/Service Analytics Congestion Analytics Anomaly Detection Service Agility Service Experienc e 8

9 VIRTUALIZATION: THE ROLE OF BIG DATA AND ADVANCED ANALYTICS IN SDN/NFV ACCEDIAN NETWORKS Company Confidential Scott Sumner, VP Solutions Marketing 2015-June-06

10 ACTIVATING ANALYTICS FOR SDN THE MISSING INSTRUMENTATION LAYER Supports use case SDN Controller Control Plane Network State+ Virtualized Performance Assurance Director Multiple services with unique needs share the same physical network: MME / MTSO Instrumentation Layer Data Plane Brings data plane performance to the control plane. Performance Assurance VNF Controller Smart Modules Standards-Based PM Reflectors Instrumentation Latency Sensitive Bandwidth Hungry Best Effort The Network State is not enough: Data Center Byte # Counters Hops Real-Time, Ubiquitous, Open Visibility Utilization Available Capacity Packet Loss Latency Delay Variation QoS/E KPIs SDN Controlle r ACCEDIAN NETWORKS Company Confidential

11 VIRTUALIZATION: The Role of Big Data and Advanced Analytics in SDN/NFV John Govert, Office of the CTO

12 JDSU End to End Vision JDSU and 3 rd Party Application Ecosystem 2015 JDS Uniphase Corporation JDSU CONFIDENTIAL AND PROPRIETARY INFORMATION 12

13 BIG DATA ANALYTICS FOR NFV & SDN Light Reading Big Telecom Event June Overture Networks. Proprietary and Confidential. Do not distribute without permission. June 15, 2015

14 Big Data Analytics Feeds Intelligent Orchestration Autoscale Graph-based Modeling VNF VNF Physical Network Function VNF VNF Service Lifecycle Host Intelligence Applications VNF Fault Mgmt Application API VM VNF VNF Host NW & Svc Perf Mgmt Data Correlation 3 rd Party Exernal APIs Big Data Repository OSS Orchestration Service Models VNF Catalog Service Catalog Data Ingestion API Data Ingestion API Data Ingestion API Data Ingestion API Data Ingestion API Policy Driven Workflow NFVO VNFM/ EMS OpenStack OSS/BSS Network / Service Assurance Data Channels Elastic Scaling SDN Control Dynamic Network Configuration Overture Networks. Proprietary and Confidential. Do not distribute without permission. June 15, 2015

15 Network Operators Will Gain Immediate Value From Deploying Network Data Analytics Solutions Today Yes, levels of IP network penetration today require powerful real-time capabilities to meet customer experience requirements and to support deployment of SDN and NFV. No, it will be crucial for 5G and M2M IoT support, but today probes and DPI are good enough.

16 Analytics Is a Vital Part of a Successful NFV Implementation Yes, it will be extremely difficult to meet QoS and QoE requirements and orchestrate VNFs without analytics. No, it s not required immediately since NFV rollout will be gradual and represents only a small percentage of live traffic for the next few years.

17 What Are the Highest-Value Analytics Use Cases for NFV? Service chain performance analytics Others?

18 What Are the Greatest Challenges in Deploying Analytics to Support NFV? Meeting physical and virtual network requirements Extracting data into meaningful formats Creating actionable analytics Monetizing the data Others?

19 Analytics Is a Vital Part of a Successful SDN Implementation Yes, analytics will be crucial to support dynamic service chains, service automation and detect security threats. No, it s not mandatory, SDN controller policies will be relatively static in early implementations. Analytics will only make SDN implementation more complex.

20 What Are the Highest-Value Analytics Use Cases for SDN? Dynamic network control Intelligent network provisioning Others?

21 What Are the Greatest Challenges in Deploying Analytics to Support SDN? Availability of standardized interfaces Operational requirements Performance scaling commercial networks Others?

22 Q & A

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