Mobile-edge Computing

Transcription

1 Mobile-edge Computing Major strides towards RAN virtualization Nurit Sprecher 1 02/09/2014 Nokia Nurit Sprecher

2 Agenda Market drivers and requirements 2020 network architecture vision Cloud RAN Opportunities and challenges Transforming RAN architecture towards Cloud RAN Cloud RAN deployment scenarios A proof point: Mobile-edge Computing Introduction Examples of use cases Conclusion 2 02/09/2014 Nokia Nurit Sprecher

3 The thirst for mobile data will continue to grow exponentially. 3D, high and ultra-high definition screens Video integrated everywhere Digital universe continues to expand Everything from and on the cloud Billions of connected objects 3 02/09/2014 Nokia Nurit Sprecher

4 Challenges for operators Requirements for the network are constantly changing Need for: - Agility - Simplicity - Business value Become a valued service supplier in the new digital economy Develop and launch new services rapidly and cost effectively Have the business and technical agility to address new application requirements and business partnerships 4 02/09/2014 Nokia Nurit Sprecher

5 FutureWorks Nokia vision: Mobile networks will enable the profitable delivery of one gigabyte of personalized data per user per day. Key requirements for networks towards 2020 Support up to 1000 times greater capacity Reduce latency to milliseconds Teach networks to be self-aware Flatten total energy consumption Reinvent Telcos for the cloud Personalize network experience for profitability and a quantum leap in flexibility 5 02/09/2014 Nokia Nurit Sprecher

6 Cloud Computing, NFV and SDN FutureWorks Highly complementary, innovative, architectural concepts and paradigms that together have the potential to support a profound transformation regarding the way in which mobile broadband networks are implemented, deployed and operated Ecosystem for innovation Personalized experience Rapid introduction of new services Optimized TCO Agility Holistic end-to-end based management and control 6 02/09/2014 Nokia Nurit Sprecher *) IaaS, PaaS and SaaS: Infrastructure, Platform-and Software-as-a-Service

7 Drivers for network architecture evolution A fully automated and programmable mobile-broadband network, orchestrated over a network-wide, uniform cloud platform, is essential for survival. 7 02/09/2014 Nokia Nurit Sprecher *) NFV: Network Function Virtualization; SDN: Software Defined Networking

8 Mobile-network architecture transformation towards 2020 FutureWorks 8 02/09/2014 Nokia Nurit Sprecher

9 Cloud RAN expected capabilities It is envisioned that cloud computing and virtualization will affect the RAN, enhancing flexibility, agility and operability with existing and new RAN functions. 9 02/09/2014 Nokia Nurit Sprecher

10 Cloud RAN challenges, success factors and recommended approach Applying cloud technologies in line with the RAN s unique requirements FutureWorks Challenges 10 02/09/2014 Nokia Nurit Sprecher Success Factors

11 Transforming RAN architecture towards Cloud RAN A multitude of deployment options for operators should be supported, enabling them to minimize their RAN TCO and provide best performance. These should include: Highly heterogeneous landscape of viable X-haul transport technologies A wide range of deployments, from Distributed RAN (D-RAN) to Centralized RAN (C-RAN) (including distributed controllers in 2/3G) D-RAN C-RAN 11 02/09/2014 Nokia Nurit Sprecher Future-proofing networks to ensure forward compatibility with radio evolution

12 Nokia is building up experience with Centralized RAN Working with customers in different regions and on different scales FutureWorks From medium to large RAN installations... Reliability issues, costs, best practices Fronthaul Capacity, coverage and mobility gains via extended coordination. Network availability and reliability Performance Understanding the reality of financial savings versus today s optimized and distributed RANs TCO Numerous customer references in Japan, Korea, and US (commercial deployments and trials) Cases... to specialized high-traffic scenarios such as stadiums 12 02/09/2014 Nokia Nurit Sprecher

13 Operator considerations regarding Centralized RAN What are the benefits and is centralization future-proof? FutureWorks Short-term considerations Cost and performance benefits versus deployed distributed RAN with cost optimization Building of fronthaul* transport to RF sites while retaining TCO benefits The optimal scenario and scale for centralization Tackling reliability issues for the hotel site Possible real-time geo-redundancy Long-term considerations Ensuring that transport restrictions will not prevent us from adding spectrums or antennas at sites in the future Anticipated 5G requirements for spectrum bandwidth and prospects for massive MIMO If 5G achieves sub-ms radio access latency, will we need to return equipment to sites in 5-10 years? Implementing RAN trouble-shooting and upgrades across transport and RAN units *) Increase of bandwidth rates by x10+ compared to backhaul; ensures low-latency, minimal-jitter, and strictly symmetrical connectivity 13 02/09/2014 Nokia Nurit Sprecher

14 Enhancing radio access with cloud technologies Ensuring full deployment flexibility and preparing for 5G FutureWorks 14 02/09/2014 Nokia Nurit Sprecher

15 Innovations for Centralized RAN RAN architecture research and novel solutions within our industry FutureWorks For example, compression techniques & better support for packet switched networks Transport cost reduction For example, controllers in HetNet RAN, multi- RAT and Wi-Fi integration Explore new ctrl functions Flexi zone an advanced split- processing architecture for leaner Centralized RAN Zone AP AP Zone Controller Transport Core AP AP AP AP Offload Optimization of current and next generation RAN protocols and control functions provides enhanced centralization and cloudification 4G/5G 15 02/09/2014 Nokia Nurit Sprecher

16 Mobile-edge Computing: innovations for Cloud Enhanced RAN Transforming the base station into a value-creating engine strong industry commitment Launched at Mobile World Congress 2013: Delivers content where users connect Analyzes data at the source before it expands Contextualizes applications with real-time data Maximizes speed and interactivity through close proximity to the customer benefits Acceleration Operation and insight Innovative services Locating cloud-computing capabilities within the RAN Telco-grade robustness and security State-of-the-art middleware for highly distributed application environments Placing services close to the users is a step towards creating a network architecture that prepares mobile operators for content-heavy, performance-oriented service models that will be critical to competitive advantage in the future (Gabriel Brown, April 2013) Award winning technology 16 02/09/2014 Nokia Nurit Sprecher

17 Mobile-edge Computing use case: acceleration Increase responsiveness from the edge Responsiveness Speed UE RACS GW Content Capacity Large object delivery with Content Extender (optional core caching) Small object delivery with Site Accelerator through enb edge caching or local break-out Radio throughput guidance and real-time positioning for service optimization Efficient utilization of the radio frequency 17 02/09/2014 Nokia Nurit Sprecher *) RACS: Radio Access Cloud Server

18 Mobile-edge Computing use case: operations and insight Real-time network and service analytics FutureWorks Proactive maintenance of the customer s experience through efficient network and service operations 18 02/09/2014 Nokia Nurit Sprecher *) SON: Self-organizing networks

19 Mobile-edge Computing use case: innovative (vertical) services Agile application development and deployment FutureWorks Video surveillance and advanced analytics Video analytics edge Video analytics management IOC Cameras RACS with video analytics Video analytics management (IBM) Intelligent Operations Center (IBM) Video streams from connected cameras are sent to the RACS for processing. A centralized streams app further aggregates the data. Reports and necessary alerts are created. Patterns, shapes, colors, movements etc. are captured and converted to meta data. Additional sensor input can be used to improve accuracy. Appropriate decisions can be taken by the city /09/2014 Nokia Nurit Sprecher *) IOC: Integrated Operations Centre

20 Conclusion 20 02/09/2014 Nokia Nurit Sprecher

21 21 02/09/2014 Nokia Nurit Sprecher