Technology Trends and Issues in ICT Research & Development or “How to achieve your dream?” Lee Kang-Won, PhD. ICT Synergy R&D Dept. September 2014 2 Table of Contents • • • • • • Introduction – About Me About IBM, SKT What is good R&D? Major trends in ICT Possible research directions About R&D attitude About Me • Joined SKT (April 2014) • Joined IBM Research as RSM (August 2000) • Ph.D. Computer Science, UIUC (2000) – – – – Thesis: Multicast for Heterogeneous Packet Flows Kookbi Scholarship from Korea Government C. G. Gear Outstanding Graduate Student Award KFAS Scholarship • Military Service at ROK Air Force (1994 – 1996) • M.S. and B.S. Computer Engineering, SNU – Merit Scholarship – Student President – Magna Cum Laude 4 Technical • • • • • • • • • 100+ publications in premier journals and conferences IBM Master Inventor KSEA Engineer of the Year (2013) ACM Distinguished Scientist & Senior Member IEEE Senior Member IBM OTAA (TPC), RDA (PMAC, ITA) Book Author on Policy Technology (w/ D. Agrawal et al.) Keynote speaker: IEEE Sarnoff 2012 Invited talks: UIUC, Columbia, Samsung, SNU, KAIST, … 5 Projects Managed - ITA Program • Summary – Fundamental research in Network Science – IBM-led consortium funded by US Army and UK MOD – 10 Year Program (5 + 5) • Funding Structure – Basic research: $100M total – Transition contracts additional ITA Technical Scope – Tech – Tech – Tech – Tech Area Area Area Area 1: 2: 3: 4: Network Theory Security Sensor Information Processing Coalition Decision Making – My Role: Technical Area Leader for Tech Area 1 (Network Theory) 6 Projects Managed – Cloud Computing • Funding Agency: NIST – 3 year (2010 – 2012) • Goal – Develop algorithms and mechanisms for management of large scale cloud computing systems • Team – IBM: ITW, BAMS, STR, SWR – Cornell University • Output – Science: 15 papers published top venues (INFOCOM, PODC, Allerton, SMPTS, AISTATS, KDD, CLOUD); several patents – Biz Impact: Anomaly Detection (TASP GA) Predictive Analysis (NSN demo, Streams GA) – Standard Impact: SPEC Cloud Benchmark 7 Technology Transfer: IBM TPC • Background – Configuration errors are one of the leading causes of SAN disruptions and maintenance costs (w/ Almaden) Before • Configuration Checking Utility for TPC v3.2 – Validates the correctness of SAN configuration by checking it against best practices and policies from field practitioners – Diagnoses across multiple devices and hardware/software /firmware components • Outstanding Technical Achievement Award, 2008 – Still available in Version 5 (4:30) 8 After Warning: host can see both tape and disk Tech Transfer: Spatiotemporal Analytics • Motion processing: Geofencing, Hangout, Ma p matching, Compression • Fast Indexing for query: New algorithm using prefix matching; efficient for KV stores – 10x – 1000x speed up depending on applications • Full Earth operations: handles large objects (e .g., cargo ship, satellites), any location (e.g., ar ound poles) • Transferred to SPSS, G2, Informix • In plan for DB2, BigInsight, Streams • Applications: Connected cars, (1:00) Insurance, Location-specific monitoring, Digital billboards, etc. 9 9 About IBM Quiz: How old is IBM? • Hint: MS is 39 years old. • • • • A: 65 years B: 81 years C: 92 years D: 103 years Quiz: How old is IBM? • Hint: MS is 39 years old. • • • • A: 65 years B: 81 years C: 92 years D: 103 years (founded in 1911) Quiz: What does IBM stand for? Quiz: What does IBM stand for? Quiz: What does SK mean? Quiz: What does SK mean? • 선경 (鮮京) Quiz: What biz did SK start? Quiz: What biz did SK start? • Textile (선경직물, 1953) A little more about IBM • In 2012 – – – – – No. No. No. No. No. 2 4 1 2 1 largest employer in the U.S. largest in terms of market cap company for leaders (Fortune) most respected company green company IBM Research • 12 labs worldwide • Milestones – – – – – – – DRAM, HDD Fractal FORTRAN RISC architecture Relational DB Deep Blue Watson (1:00, 2:51, 6:30, 9:40) • 5 Novel Prizes • 4 Turing Awards A little more about SK telecom • First and best LTE-A LTE HSPA+ WiBro HSDPA S-DMB 1x EV-DO WCDMA IS-95A/B 1996 2G 2006 HSUPA 2010 2013 2011 Domestically First LTE Domestically First Data network HSPA+ Paradigm Shift World’s first HSUPA for 2007 2005 1x/EV-DO 2.5G 3G 3.5G 4G 2014 300 Mbps World’s first 5.76Mbps World’s first HSDPA with CDMA 2000 1X World’s firstHandset 2003 Satellite World’s firstDMB 2000 WCDMA R4 Provide new experience to customer with high-level service World’s first such as high-rate data, video telephony and Global roaming CDMA 2000 World’s first CDMA 3CA Ⅲ. SK Telecom R&D Focus Areas NETWORK TECHNOLOGY INFORMATION TECHNOLOGY -LTE/LTE-A, 5G, -Location-based service -Context-awareness -Network-enabled cloud -Big data analytics -Internet of Things -Security CONVERGENCE TECHNOLOGY HEALTHCARE -Storage technologies -Quantum Crypto -Video/audio analytics -In-vitro Healthcare -Personalized healthcare *eICIC: enhanced Inter-Cell Interference Coordination 22 What is Good R&D? What is Good R&D? • “If we knew what it was we were doing, it would not be called research, would it?” – Albert Einstein Pasteur’s Quadrant What is Good R&D? • Important Problem – Real world issue • Ingenious Solution – Trade Secret or Patent • Biz Impact – Can make money Major Trends in ICT Trend 1. Network is increasingly being dominated by data Trend 1. Network is increasingly being dominated by data • Bandwidth vs. response time vs. availability – SNS, multimedia, search, VR, AR • More variable, dynamic, integrated – Real-time OSS/BSS Trend 2. Big opportunities for big data Quiz: How much data generated between 1993 – 2012? • Hint: 5 exabytes* generated between 3000 BC – 2003 * 1 Exabyte = 10^18 bytes = 1 M Terabytes Quiz: How much data generated between 1993 – 2012? • Hint: 5 exabytes* generated between 3000 BC – 2003 • Answer: 4000 exabytes * 1 Exabyte = 10^18 bytes = 1 M Terabytes Quiz: If we stack books containing 4000 exabytes, how high will they be? • Hint: Think BIG Quiz: If we stack books containing 4000 exabytes, how high will they be? • Hint: Think BIG • Answer: 80 roundtrip times between Earth and Pluto (160 x 5.9B km) Trend 2. Big opportunities for big data but … • Didn’t crack it yet – MNOs vs. OTTs • Privacy: Customer sentiment – plus regulations • Other obstacles – End-to-end encryption Trend 3. IoT can provide new opportunities • IoT is a $19 trillion opportunity – John Chambers Trend 3. IoT can provide new opportunities but … • Innovation is happening elsewhere – Nest, drones, watch, self-driving cars • Selling “circuits” vs. solution? • What about security and privacy? Direction 1. Virtualization to the rescue • No constraints from physical assets – NFV, SDN, Network-enabled cloud • “Capacity breathing” – Auto-scaling, self-scaling – Predictive • Dynamic – At any granularity, at any time scale • Point-to-point, multicast – Based on usage Direction 2. Mining the Data • More than just “big data” – Synergy between MNO & OTT? • Mining, sieving, refining, distilling – What is the purpose? – What are you looking for? – Intelligence, Insight • New tools – Graph DB, column store, big table, stream processing – Privacy-preserving, delegated computing Businesses are “dying of thirst in an ocean of data” 46 90% 80% 20% of the world’s data was created in the last two years of the world’s data today is unstructured amount of data traditional systems leverage today 1 in 2 83% 2.2X business leaders don’t have access to data they need of CIOs cited BI and analytics as part of their visionary plan more likely that top performers use business analytics How to handle Big Data? • Maybe we need “data refinery” Oil refinery Data refinery Unstruct ured Data User Intent Spatiote mporal Context Data Structur ed Data Purchase History CDR Billing Network Intelligence Raw Data User Sentiment Social Net Data How to ensure safe data analysis? How to ensure safe data analysis? • Privacy Homorphism: One of 10 Emerging Technologies (MIT Technical Review 2012) Direction 3. Rich IoT • Extreme scale • MNO has a unique peering point – Sees traffic, location, ubiquitous • Can provide value-added solutions to customers – Built-in analytics, security, AI – AaaS, SaaS, AIaaS What is Good R&D? • Important Problem • Ingenious Solution • Biz Impact What is Good R&D? • • • • Important Problem Ingenious Solution Biz Impact Solves the Problem Completely – Google vs. Alta Vista, Lycos, Bing, etc. – Facebook vs. MySpace, Cyworld, etc. – Amazon vs. Best Buy, Walmart, etc. Wait, this is overwhelming… About R&D Attitude (1) • Develop core strength; buzzwords come and go Buzzwords come; buzzwords go • Big data – data mining, parallel computing, dist. computing • IoT – device, processor, sensor, communications • Cloud – system software, virtualization, optimization, networks • Cognitive computing – AI, machine learning, neural network, NLP About R&D Attitude (2) • Put enough time, effort, and attention About R&D Attitude (2) • Put enough time, effort, and attention About R&D Attitude (3) • Execution is the key. About R&D Attitude (4) • Don’t give up so easily Brian Acton: Co-Founder of WhatsApp So, what is your dream? Want to hear your thoughts. Thank you!