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Skt.2013.innovation technology for future convergence network

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  • 1. Innovation Technology for Future Convergence Network KRnet 2013 Keynote Speech Jinsung Choi, Ph.D. EVP, Head of ICT R&D Division, SK Telecom
  • 2. Contents I. Key Trends Driving Network Evolution II. Innovation Technologies for Future Convergence Networks - Software & Cloud-based Network Architecture 1 - SUPER Cell III. Conclusion
  • 3. 1. Mobile & ConnectedI. Key Trends Driving Network Evolution 1. Mobile & Connected - Exploding data traffic growth originated from increased devices and LTE commercialization LTE promising wider data transmission bandwidthMore devices always connected to N/W The number of connected devices per person will be 3 times more in 4 years Mobile Data Traffic by Device More traffic induced by LTE user than by 3G users 3 Monthly Data Traffic per User 2 Source: Cisco VNI Mobile, 2012 Other portable devices (2.2%) M2M (4.7%) Home Gateways (4.8%) Non-smartphones (5.7%) Tablets (10.0%) Laptops & Netbooks (24.2%) Smartphones (48.3%) 2011 2012 2013 2014 2015 2016 5 Exa Byte/Month 10 Exa Byte/Month Source: SKT Internal ‘10 ‘11 ‘12 ‘13 1 2 3 3G 4G/LTE [Giga Byte/Month] Year
  • 4. 2. Multimedia ContentsI. Key Trends Driving Network Evolution 2. Multimedia Contents - Both demand and supply of multimedia contents are ever growing, mainly induced by LTE introduction and the emergence of contents platforms such as YouTube and Netflix Data Service Usage PatternVideo is major internet traffic 51% Video Traffic, 23% Web Traffic (2010) More multimedia traffic in LTE than 3G VIDEOOTHERS 3% Sep. 2012 3 1990 VIDEO Peer-to-Peer WEB 2000 FTP OTHERS NewsgroupDNS Telnet Email 51% 23% 23% 2010 3G (WCDMA) Multimedia (30%) Web (40%) App. Market (10%) SNS (7%) Etc. (12%) Multimedia (38%) Web (33%) App. Market (11%) SNS (7%) Etc. (11%) 4G/LTE Source: SKT InternalSource: CISCO based on CAIDA publication
  • 5. 3. Computing EvolutionI. Key Trends Driving Network Evolution 3. Computing Evolution - Applications of IT Infra techniques are being extended with the help of processor cost down and evolution of computing technologies Computing TechnologiesProcessor cost diminishes Processor cost halving time: 1.1 year Virtualization Distributed Processing Cloud Management 4 Cloud Management Open API Security MapReduce HDFS Crawler Visualization Parallel Computing In-memory Computing
  • 6. Mobile & Connected Multimedia Contents Software & Cloud-based Network Architecture Key Innovation TechnologiesI. Key Trends Driving Network Evolution • Always connected smart devices • High bandwidth LTE/LTE-A • M2M/IoT 【 Key Trends 】 【 Key Tech 】 5 Computing Evolution Network Architecture • Mobile IPTV services • Video streaming • UCC sharing • Cloud infrastructure and services • Analytics/Big Data • Personalized services SUPER Cell for Beyond LTE-A/5G Network
  • 7. II-1. Software & Cloud-based Network SDN/NFV SDN and NFV allow to design and manage networks having potential to increase operator agility, to reduce cost, and to disrupt the vendor landscape Encourages innovationInnovative “Open Innovation Platform” “Lower cost, raise efficiency and increase agility” Virtualized Network Functions DPI CDN WAN Accelerator PE Router P-GW/S-GW CG-NAT Network Function Virtualization (NFV)Software Defined Network (SDN) 6 Encourages innovation and competiveness among 3rd Parties CapEx/OpEx saving Data Plane Control Plane Innovative Network Apps from 3rd Parties Open Standards Firewall WAN Accelerator CG-NAT Standard/High-Volume Servers Standard/High-Volume Storage Standard/High-Volume Switches Orchestrated, Automatic & Remote Install
  • 8. II-1. Software & Cloud-based Network To-Be Image Migration to more efficient, agile, intelligent, but economic mobile network by exploiting disruptive future network technologies: SDN, N/W Virtualization, Cloud “Vendor-specific Hardware, Low Scalability, Simple Policy-based Operation” “Virtualized, Service-Oriented and Flexible Network” Orchestrator SDN/Cloud Controller Analytics Platform Software & Cloud based NetworkLegacy Network 7 RU#1 RU#2 RU#N #1 #2 #N Internet EPC DPI Video Opt. CDN Access Network Core Network DU Pool (A-SCAN) RU#1 RU#2 RU#N Internet DU #N DU #1 DU #2 S/W IMS EPC Video Opt. DPI CDN TCP Opt. S/W SDN/Cloud ControllerPlatform Analytics-based Control GPP, Standard H/W Virtualized/Cloudified Web Accel. PCRF
  • 9. II-1. Software & Cloud-based Network Use Case 1): Dynamic Service Chaining SDN Network To-BeAs-Is SDN Use Case: Dynamic service chaining enables a highly scalable and cost-efficient network structure Low Scalability - Most traffic passes through every service node every time Large CAPEX/OPEX Low Flexibility - Manual & static policy control & enforcement More efficient N/W Operation & Time-to-market - Per-subscriber, per-application, per device differentiated data services 8 Gi Service Network Device InternetEPC SDN Network Device Internet On Context A On Context C EPC On Context B SDN Controller Dedicated appliances performing specific network functions Virtualized network functions running on standard H/W - Manual & static policy control & enforcement - Lack of flexibility and agility
  • 10. Monitoring for Network Control & BillingSeamless Subscriber Mobility II-1. Software & Cloud-based Network Use Case 2): Seamless Subscriber Mobility Use Case 3): Monitoring Network Control & Billing Innovator’s Dream: SDN is capable of providing logically centralized control plane and common control protocol SDN provides centralized and common control protocol working across different technologies - e.g. 3G, LTE, WiMax and Wi-Fi Packet handling rules in SDN switches can efficiently monitor traffic at different level of granularity - Per-subscriber/per-service statistics are collected easily at each SDN switch - Enable real-time control and billing 9 - Enable real-time control and billing SDN Controller N-generation network N+1-generation network eNB 1 eNB 2 SDN Switch
  • 11. MME HSS PCRF S1-MME S6a DPI? ? ? II-1. Software & Cloud-based Network SDN Requirement For the integration with mobile networks, 3GPP-compliancy, subscriber-awareness, service- awareness and controllability are required 10 UE MME PCRF Internet Evolved Packet Core eNB RAN S1-U SDN Controller S/P-GW Control Plane S11 Gx S-GW Data Plane SGiP-GW Data Plane SDN Protocol
  • 12. 10 G 100 G .11ac .11ad 5G II-2. SUPER Cell Motivation 5G has gained lots of attention for future radio access on developing LTE/LTE-A tech. Target - 100Gbps maximum cell capacity (1000 times larger than LTE) - 1000 times lower energy consumption - 1000 times higher capacity for connected devices 111995 1995 2005 2010 2015 Year 100 k 1 M 10 M 100 M 1 G GSM CDMA WCDMA HSDPA LTE LTE Advanced Cellular 802.11 .11b .11g .11a .11n .11ac Wireless LAN 4G 3G 2G
  • 13. Vision Smart • Mobility/capacity enhanced by control/data separation Unified Smart • Mobility/capacity enhanced by control/data separation UnifiedEnergy Efficient Performance Optimized 【 SUPER Cell Vision】 SUPER Cell is the SKT’s future network architecture combined of key elements from efficient radio resource utilization, smart cell-split, and new frequency bands II-2. SUPER Cell 12 Unified • Cloud architecture in heterogeneous network Performance Optimized • Dynamic interference coordination and management Energy Efficient • Green architecture and functions for power saving Reconfigurable • N/W operation mode changes interworking with SON Unified • Cloud architecture in heterogeneous network Performance Optimized • Dynamic interference coordination and management Energy Efficient • Green architecture and functions for power saving Reconfigurable • N/W operation mode changes interworking with SON Unified RAN (Cloud and Heterogeneous) Energy Efficient (Power Saving) Reconfigurable (Adaptive Management) MobilitySupport High Rate Support Smart (Hierarchical Scheduling) SON: Self-Organizing Network, RAN: Radio Access Network
  • 14. 100 times capacity enhancement and 10 times cost reduction compared to current LTE N/W 【 100x Capacity Enhancement】 【 10x Cost Down】 100×××× Capacity↑ 10×××× Cost↓ TargetII-2. SUPER Cell 13 f1 Freq. f2 fn … foffload UE#1 UE#2 UE#3 Massive MIMO Small Cell MC TD-LTE Wi-Fi Analytics ServerSON Optimization MIMO: Multiple Input Multiple Output, UE: User Element 1. Higher Radio Resource Efficiency 2. More Cell Splitting 3. More Frequency Bands 4. Lower Operation Cost
  • 15. III. Conclusion - To come up with mobile data traffic explosion, SK Telecom has developed future convergence smart networks enforced by 1) SDN/NFV 2) SUPER Cell - R&D collaboration among university, industry and research organization is indispensible for global leadership and the successful development of future 14 indispensible for global leadership and the successful development of future convergence networks [SUPER Cell demonstration in MWC2013]

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