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Three mustketeers-swcs-2014-autoidlab-kaist-daeyoungkim
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Three mustketeers-swcs-2014-autoidlab-kaist-daeyoungkim

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Internet of Things Research at Auto-ID Lab KAIST

Internet of Things Research at Auto-ID Lab KAIST

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  • 1. The Three Musketeers, IoT, Cloud, and Big Data: One for All, and All for One 김대영 Daeyoung Kim Jan. 24, 2014 교수 Director 카이스트 전산학과 Auto-ID Labs, KAIST http://resl.kaist.ac.kr http://www.autoidlabs.org kimd@kaist.ac.kr
  • 2. 발표 내용 • Internet of Things 의 정의 및 시장 예측 • Expecting New Big Players • Internet of Things in Practice • ID(Identification) to Big data services • KAIST AUTO-ID LABS RESEARCH ACTIVITIES 2
  • 3. INTERNET 은 INTERNET OF THINGS 시대로 진화중 IOT 의 정의 (1/2) In 1999, the Internet of Things" was first coined by Kevin Ashton who cofounded the Auto-ID Center at the MIT Business Processes and Applications Software and Network Hardware 3
  • 4. INTERNET 은 INTERNET OF THINGS 시대로 진화중 IOT 의 정의 (2/2) No concrete consensus! What they commonly say is that “the Internet embraces everyday objects and lets them available anywhere, anytime.” People or systems are able to access real-world through the Internet. 4
  • 5. IF IOT IS REALIZED? • Internet상의 상태와 실세계의 상태가 일치 • 실시간으로 실세계의 다양한 상황 정보를 정확하고 세밀하게 제공 4인 3T, 소근소근 휴업 테이블 4, 조용 8인 2T, 조용 4인 3T, 시끄러움 2인 4T 4인 2T Full, 조용, 몬순 커피 4인 2T 2인2T Full, 시끄러움 검색: “어은동 카페” 5
  • 6. EMERGING TECHNOLOGIES HYPE CYCLE 2013 6
  • 7. IOT 에 관한 통계 및 시장규모 예측 IDC forecasts 15 billion devices by the year 2015" ABI Research’s study, “Wireless Sensor Networks,” analyzes IEEE 802.15.4 and which standards, such as ZigBee, Wireless HART, and ISA100.11a, will influence and drive the market, as well as emerging technology and competitive solutions such as Z-Wave, 6LoWPAN, Bluetooth Smart, and Low Power Wi-Fi. 850 Million IEEE 802.15.4 Chipsets to Ship in 2016, Despite Strong Competition from Bluetooth 7
  • 8. 사물(THINGS)의 범위 (NO LIMITATION) 수동형 사물 액티브 태그형 사물 무선센서형 사물 스마트가전형 사물 지식데이터 사물 스마트형 사물 8
  • 9. INTERNET OF THINGS 비전 / ARCHITECTURE One for All, and All for One Big Data Analysis Home Surveillance M2M networking of Home Devices Thing Information Internet Browsing Human Information Social Network Service for IoT Cloud Computing Cloud Computing Contextaware Services User log, Business activity logs, etc. Social Network Service Internet contents, SNS, etc. Everyday objects Multimedia (video, audio), etc. Future IT Eco-System Internet of Things Entertainment (Multimedia & Game) Augmented Reality Internet of Things 9
  • 10. EXPECTING NEW PLAYERS 10
  • 11. INTERNET OF THINGS IN PRACTICE Internet of Things는 새로운 분야이기 때문에 모든 기술과 제품을 새로 만들어 야 하나요? http://www.youtube.com/watch?v=wVOQc5rImqE&feature=share 11
  • 12. SMART ACCESSARIES (I) Eye-Fi Nemoto Dice+ Necomimi 12
  • 13. SMART ACCESSARIES (II) Instabeat Smart Sock Golfsense Scanadu Scout 13
  • 14. INTERNET OF THINGS IN PRACTICE Internet of Things 어떤 기술(전략)이 필요할까요? 14
  • 15. ID(IDENTIFICATION) TO BIG DATA SERVICES ID & 네트워크 시스템 소프트웨어 • IDENTIFICATION • Small&Cheap H/W • RFID/NFC/WSN/CR • Operating Systems • Visual Sensor Networks • Smart Objects/Middleware • Future Internet • Web of Things • Tracking Technology 플랫폼 • Distributed File Systems and Database • IoT Platform 서비스 • Eco System • IOT Services • Cloud Computing • Big Data • Open APIs 15
  • 16. ID(IDENTIFICATION) 체계 (1/2) Heterogeneity How to name all of them? Ambiguity How to reach a single instance? Outnumbered? Global access! 16
  • 17. ID(IDENTIFICATION) 체계 (2/2) • 다양한 현재의 ID 체계 • • • • Uniform Resource Identifier (URI): http://myflowerpot.iot.kr/temperature Universally Unique Identifier (UUID): 550e8400-e29b-41d4-a716-446655440000 Digital Object Identifier (DOI): 10.1000/182 Global Trade Item Number (GTIN): urn:epc:id:sgtin:0614141.112345.400 • IDENFITICATION SYSTEM for the Internet of Things? ID on the WEB ID is registered to Identity provider and is used with associated party 17
  • 18. OPERATING SYSTEMS/SDK FOR SMART RESOURCE CONSTRAINED THINGS Tiny footprint Consumer goods OS for IoT • • Mid-level Consumer electronics Mini OS Consumer OS Enterprise Enterprise OS 소비자 가전, 서버시스템은 Linux를 중심으로 표준화 되는 추세 적은 메모리, 낮은 수행능력을 가진 소형 Smart Things를 위한 운영체제 및 개발환경 필요 가능성 있음 / FreeRTOS, uCOS-II등 기존 OS 18
  • 19. INTERNET OF THINGS를 위한 네트워크 기술 (FUTURE INTERNET 포함) • IoT 에서 IPv6의 필요성 • 사물의 주소 역할 • 충분한 주소 공간, Plug & Play, Mobile IPv6, IPSec , QoS • 이 기종 네트워크 통합 • 이 기종 네트워크 간의 Seamless한 통신을 위해 네트워크 통합 방법 필요 • 표준화 된 IPv6 를 이용하 여 이 기종 네트워크 통합 가능성 [ IP기반의 유무선 IOT 통합 네트워크 (글로벌 액세스) ] 19
  • 20. “MIDDLEWARE” SOFTWARE FOR THE INTERNET OF THINGS • a software platform defined as middleware, fundamentally providing abstraction to applications from the things, and offering multiple services [인용] Role of middleware for internet of things: A study S Bandyopadhyay, M Sengupta, S Maiti, S Dutta - airccse.org 20
  • 21. CLOUD COMPUTING FOR THE INTERNET OF THINGS • IoT에서는 사물이 생성하는 데이터를 저장하고 사물을 위한 computation power, 플랫폼, 그리고 소프트웨어 서비스 제공 • IoT + Cloud 융합 시도- Pachube • 전 세계의 센서 데이터를 수집하는 웹 기반 온라인 데이터베이스 서비스 • 사물, 디바이스, 빌딩 등으로부터의 에너지 및 환경 데이터를 수집 (1) 실시간 데이터 그래프를 생성 (2) Historical한 데이터를 가공하거나 (3) 사용자에게 alert을 전송하는 기능 21
  • 22. IOT GENERATES BIG DATA • Big Data의 효율적 저장/관리/처리를 위하여 Massive infrastructure 가 필요 “Machine-generated sensor data will be become a far larger portion of the Big Data world, according to a recent report by IDC. The research report, “The Digital Universe in 2020,” published in December, traces data trends from 2005-20. One of its forecasts is that machine-generated data will increase to 42 percent of all data by 2020, up from 11 percent in 2005.” Everyday objects in the Internet of Things 22
  • 23. WEB OF THINGS A Web of Things Application Architecture, Dominique Guinard 23
  • 24. IOT-BASED COMPANIES: OPEN API + CLOUD + CHEAP HARDWARE + APPS Xively Cloud Services™ The world’s first IoT Public Cloud 24
  • 25. 유럽 동향 : EU-FP7 & IERC (IOT EUROPEAN RESEARCH CLUSTER) Ideas Coordination and Support Action for Global RFID-related Activities and Standardisation. Cooper ation People Universal Integration of the Internet of Things through an IPv6based Service Oriented Architecture enabling heterogeneous components interoperability. Capaci ties Internet of Things at Work. Internet of Things Architecture. Internet of Things Initiative. Internet Connected Objects for Reconfigurable Ecosystems. Euratom JRC Internet of Things Environment for Service Creation and Testing. ETC. 25
  • 26. IOT 관련 표준화 단체 IPv6 over Low power WPAN (6lowpan) NFC(Near Field Communication) standards ETSI TC M2M Architecture for ICT 3GPP MTC (MachineType Communication) Internet Protocol (IP) for Smart Object communications standards M2M Service Layer standards Information and communications technology (ICT) standards IoT RFID(Radio Frequency Identification) standards ZigBee(IEEE 802.15.4) standards Electronical Tech. standards communication protocols and interoperable systems standards IP(Internet protocol) standard BOSS(Business Operation Support System) standards Telecommunication standards 26
  • 27. INTERNET OF THINGS AT KAIST Internet of Things 연구 소개 27
  • 28. GS1 DIGITAL – ID ON THE WEB (AUTO-ID LABS) 28
  • 29. GS1 DIGITAL – ID ON THE WEB 29
  • 30. IP-WSN IN THE INTERNET OF THINGS Entertainment & Social Net. Service User Experience with IoT Service • The IP-WSN technologies breathe life into the things by enabling IP connectivity between humans and things as well as between things themselves. • Device Browsing & Mashup 6LoWPAN technology is one of such upcoming networking technologies which enable IP connectivity over resource-limited, low-power, and lowrate networks. Big Data Analysis Internet of Things SNAIL Node (6LN) IEEE 802.15.4 Btle SNAIL Node (6LN) IEEE 802.15.4 Btle SNAIL Node (6LN) SNAIL Border Router (6LBR) SNAIL Node (6LN) 30
  • 31. OPEN STANDARD FOR IP-BASED WSN • Standardization Activities for IP-based Wireless Sensor Networks • IETF 6LoWPAN WG : IPv6 over Low power WPAN • IETF ROLL WG: Routing Over Low power and Lossy networks • IETF CoRE WG: Constrained RESTful Environments Formed to adapt IPv6 technology over IEEE802.15.4 networks - RFC 4944: “Transmission of IPv6 Packets over IEEE 802.15.4 networks” - RFC 4919: “6LoWPANs: Overview, Assumptions, Problem Statement, and Goals” - RFC 6282: “Compression Format for IPv6 Datagrams over IEEE 802.15.4-Based Networks” Formed to define IP layer routing protocol independent of layer 2 - RFC 5867: “building Automation Routing Requirements in Low-Power and Lossy Networks” “Home Automation Routing - RFC 5826: Requirements in Lower-Power and Lossy Networks” - RFC 5678: “Industrial Routing Requirements in Low-Power and Lossy Networks” - RFC 6206: “The Trickle Algorithm” - RFC 5548: “Routing Requirements for Urban Low-Power and Lossy Networks” Formed to realize the REST architecture in a suitable form for the most constrained nodes and networks - draft-ietf-core-coap-07: “Constrained Application Protocol (CoAP)” - draft-ietf-core-block-04: “Blockwise transfers in CoAP” - draft-ietf-core-link-format-07: “CoRE Link Format” 31
  • 32. SNAIL (SENSOR NETWORK FOR AN ALL-IP WORLD) SINCE 2007 • Supported Protocols • • • • • • • Interoperability between IPv4/v6 domains and the IEEE 802.15.4 Lightweight IPv6, ICMPv6, MIPv6, NEMO, UDP, TCP, SSL Dual-Mode gateway and SNAIL Adaptor HTML5, Web browsing (HTTP/TCP) Mesh routing in adaptation layer, RPL, Hierarchical Addressing Fast and Seamless Mobility management, Global Time Synchronization, Security Web Browsing architecture, Pretty Cloud Service 32
  • 33. MULTI-GW BASED LOAD BALANCING SCHEME High portion of traffic is focused on a few Gateways Internet Internet Gateway bottleneck GW 1 GW InternetFairly distributed traffic load GW 1 GW 3 GW 2 GW 3 GW 2 Multi-Gateway Network w/ load balancing Multi-Gateway Network w/o load balancing Single Gateway Network • Imbalanced Data Traffic without load balancing MLEq virtually model 3D-terrain with reflecting traffic load, hop distance from Gateway, link quality, and capacity. • All the node (gateways and routers) dynamically and in distributed way update their virtual height level (VL). Level: 2 5 Level: 1 6 5 Lower Traffic load 6 Internet Balanced Traffic load 0 0 4 Internet Higher Traffic load 0 GW2 GW1 GW1 GW2 2 3 Level: 0 3 1 3 5 2 4 2 0 2 2 3 3 GW MR 1 2 3 3 Number: VL 4 4 2 4 3 3 Gateways 4 5 5 3 4 GW1's Service domain 3 2 2 2 3 3 1 2 2 1 0 1 2 2 2 1 1 2 GW2's Service domain 6 GW1's Service domain GW2's Service domain Routers (6LRs) Intersection Node Intersection area Previous Intersection area 33
  • 34. MULTI-GW BASED LOAD BALANCING SCHEME • Performance Evaluation (compared with RPL) – ns-2 Simulation 34
  • 35. MOBILITY MANAGEMENT PROTOCOL • MARIO includes movement detection, handoff management, and location management schemes. 0 Timeline Poll Req. Time t 0 Data Req. Poll confirm POLL Interval Poll Req. Time t 1 # of Poll Req. Fail : 1 # of Poll Req. Fail : 2 Retransmissions Data Req. # of Poll Req. Fail : 3 Retransmissions Data Req. { NET MAC Total 12 da ta requests are transmitted to detect MN's movement MN Movement Detection MAC MR Success Fail LUReq ② Each MR calculates τslot Distance MRA<->MRB=1 MRB<->MRC=1 MRC<->MRD=1 MRD<->MRE=1 MRC<->MRE=2 MRD IMR3 MR2 Movement Detection Poll fail MR1 MN { Poll fail Poll Req. Movement Detection RSSI from MN MR2 > MR3 > MR1 > MR4 Strong < - > Weak Reachability Test Forwarding Pointer MR1 MR4 Calculated Time to send realignment command { Poll fail Poll Req. Trajectory of MN τslot MR2 MR3 ACK Data Req. Retransmissions Time t 2 MacResponseWaitTime Nslot MN MRA ① Send Orphan notification Candidate MRs ③ Each MR sends ={MR1, MR2, MR3, MR4} realignment command MR3 in its own τslot MR4 ④ The MN performs handoff to the MR which sent realignment Signal Strength command first. Handoff Management MRB MN Initial K=0 MRC MRE IMR2 IMR1 AMR MN IMR4 MN MPFS success MPFS success K=1 K=2 MN MPFS success K=4 Location Management 35
  • 36. WEB-BASED VISUALIZATION • Smart devices and consumer electronics are equipped with web/CoAP servers that can response directly to requests from the Internet • Presentation Cloud provides rich web contents to support those embedded web servers • Sensing data and Actuation commands/results are retrieved directly from web browser and display on top of rich web interface, either in numbers or in graphs Web-based Interface Rich Web interface for userfriendly Visualization Device Control Internet Power Consumption information Consumer Electronics Pricing information Presentation Cloud which stores rich web interface Smart Metering Devices 36
  • 37. SNAIL ARCHITECTURE FOR IPV6 CONNECTION 37
  • 38. [DEMO] IOT INTERACTION WITH SMART DEVICES 38
  • 39. COGNITIVE RADIO & SDR • Slow Hopping MAC (SH-MAC) protocol • A coordinator-based architecture • Improved aggregate throughput by concurrent medium access System model Evaluation Result (without PU) Operation of SH-MAC Evaluation Result (with PU) 39
  • 40. COGNITIVE RADIO & SDR • SH-MAC implementation in high-performance CR/SDR platform • SH-MAC demonstration in CR/SDR platform which aims to achieve • Improved computing power by using embedded multi-processors • Improved data bandwidth between baseband processor and front end H/W by using USB 3.0 to Gigabit serial I/F Block diagram of CR/SDR platform Protocols PU GNU radio Ubuntu ARM Cortex-A15 MCs RF front-end/ IF processor base-band processor SH-MAC demo scenario in CR/SDR platform SUC PU SH-MAC basic functions test SU SU 40
  • 41. GROCERIES TRACE FRAMEWORK • Goal • To develop a cloud-based RFID framework for smart fridges. RFID framework over Cloud infra. Third-party apps Browsing my fridge 41
  • 42. GROCERIES TRACE FRAMEWORK: ARCHITECTURE OVERVIEW Data flow Pointer (e.g., URL) BizApp. EPCIS Query control interface Tag Data Standard (TDS) EPCIS (v1.0.1) ALE v1.1.1 implementation (F&C middleware) LLRP LLRP ALE Capture interface D-EPCIS (Distribution EPCIS) M-EPCIS (Manufacturer EPCIS) Cassa ndra Capturing Apps. Core Business Vocabulary (CBV) Discovery Service D-EPCIS Capture interface Tag Data Translation (TDT) ONS (v2.0.1) EPCIS Query callback interface Other EPCISs ALE LLRP v1.1 Other F&C Middleware LLRP FridgeApp +RFID Readers Interface Outside of Cloud infra Inside of Cloud Infra 42
  • 43. EPC NETWORK ON THE CLOUD RFID reader EPCN Admin F&C (ALE) external 2 cloud (incoming) src ip addr, src port dst private ip, dst port cloud 2 external dst ip addr, dst port src private ip, src port 5. configure CapApp to receive EC reports from F&C 2. configure LRspec F&C F&C A A F&C RFID reader RFID reader (flow mapping) RFID reader (DDNS for cl oud infra) Accessing App 7. V* dispatches tag data to the corresponding EPC components according to flow mapping CapApp CapApp CapApp 6. subscribe (EC report) EPCIS EPCIS A A EPCIS Datastore EPCDS EPCDS A A EPCDS Datastore 43
  • 44. PERFORMANCE MEASUREMENT RESULTS (SELECTED) • EPCIS with Cassandra Datastore • Improved response time with Cassandra (3-5 times faster) Contents EPCIS event capture performance comparison (Cassandra vs MySQL) EPCIS event query performance comparison (Cassandra vs MySQL) 44
  • 45. THE CURRENT SMART THING INFORMATION SERVICES (STIS) IN IOT6 – EPC SENSOR NETWORK Accessing App. DS Query interface DS Query interface ONS Geo-distance discovery service (ElasticSearch) STIS Query callback interface STIS Query control interface (e.g., Manufacturer) Filtering and collection (F&C) middleware CoAP/ JSON(oBix) CoAP/ JSON(oBix) ALE ALE Other STISs Other F&C Middleware LLRP Pointer (e.g., URL) oBix device 6LoWPAN Mobile phone Capture interface STIS Capturing Apps. Capture interface Cass andra EPC standard CoAP/JSON( oBIX) 45
  • 46. SCALABLE STIS ARCHITECTURE FOR THE CLOUD OF THINGS Document-based NoSQL DB for Geo-distance and text search, analytics, etc. For time-series data with frequent insertion Domain-specific applications Geo-distance Discovery Services Smart Things Information Service (static and dynamic information) Actuation Interface Object orchestration and organization management ALE LLRP RFID Reader (e.g., passive tags) LLRP Sensor Interface Oracle Spatial and Graph Graph database organization relationship management Sensor Interface Sensor F&C&CEP middleware Actuation interface Object Sensor Interface Wireless ID and Sensor networks (e.g., active tags) Sensor Interface Actuation Interface Sensor Network Actuator Networks (e.g., smartphone phone) (e.g., consumer electronics, appliance) Federated Systems RFID Filter & Collection Middleware Object Decentralized Systems ONS Relational DB for structed MasterData Sensor & Actuator Networks 46
  • 47. IOT MASHUP AS A SERVICE CLOUD • IoT Mashup as a Service Cloud • 사물 매쉬업 서비스 모델을 기반으로 런타임 IOT 서비스 생성을 지원하는 클라우드 기반 플랫폼 • 사물 매쉬업 서비스 모델: 사물, 소프트웨어, 컴퓨팅 리소스의 조합으로 이루어진 서비스 모델로서 엔드 유저가 런타임에 세 가지 요소를 선택하여 커스터마이징이 가능함 • 엔드 유저, 매쉬업 서비스 디자이너, 클라우드 제공자, 소프트웨어 개발자, 사물 소유자 등으로 이 루어진 에코시스템 Low Traffic Computation Resource Selection Thing Selection Processing Logic Selection 47
  • 48. IOT MASHUP AS A SERVICE CLOUD • IoT Mashup as a Service Cloud (Lightweight Cloud on Smartphones, IoT App.) 48
  • 49. IOT SNS PLATFORM • Lilliput – IOT SNS • • • • IoT를 위한 소셜 네트워킹 플랫폼 Smart Thing Middleware + Online Social Network 유연한 그래프 구조를 통해 실 세계의 정보와 소셜 정보를 함께 제공 온라인 소셜 네트워크와 스마트 디바이스를 다루는 부담을 경감시키고 응용 개발자에게 추상화된 API를 제공하는 미들웨어 • Social 관계에 기반한 Access Control 기능 IoT Social Networks User Researcher Application Developer Internet of Things Online Social Networks 49
  • 50. IOT SNS PLATFORM • Lilliput – IOT SNS • Sorcerer’s Book – IoT SNS Application, Lilliput API를 이용한 응용 서비스 Application Application Application Lilliput APIs x Unacceptable Request Acceptable Request Security Manager Lilliput Architecture Graph Utilization Manager Querying Reasoning Manager Manager Modification Manager Rules IoT-Social Graph Manager Smart Thing Service Manager Entity Manager Query Engine IoT Social Model Sorcerer’s Book Access Controller IoT Soci al Graph Relationship Manager Sync. Manager Reasoning Engine Two Space Reflection Manager Chg. Notif. Manager Lilliput Reflection Manager Graph Builder Element Extractor Thing Service Invoker OSN Publisher Notification Receiver External Components Web Service Interface Real world context Metadata, etc Service Invocation e.g. Air-conditioning IoT Platforms Personal profiles social relations hips, etc Pub lish in g message Upd ating relationships Online Social Networks Smart Thing Lilliput Architecture 50
  • 51. 비주얼 빅데이터의 분석을 통한 인간의 시각을 뛰어넘는 인지능력 확보 VISUAL SENSOR NETWORKS - SEAHAVEN 51
  • 52. SEAHAVEN 52
  • 53. IOT 테스트베드 AT KAIST DNS Port: 53 1. Lookup IP address of EPCIS (DNS Protocol) Object Naming Service (ONS) 2002:8ff8:6a87::8ff8:6a87 On-Demand Service Usage Beam Projector Windows Mobile 7 iPhone Powerful Server I o T Client Object Naming Service (ONS) Accessing Application Port: 80 IPv6 Network ALE Administrator Laptop 6to4 Tunneling Composited Service (Service Specification) F&C Port: 8081 /ALEService /ALELRService CoAP Client EPC Information Service(EPCIS) 2002:8ff8:6a89::8ff8:6a89 Capturing Application Port: 10300 ALE report subscription EPC Information Service(EPCIS) Filtering and Collection (F&C) Filtering and Collection (F&C) 2002:8ff8:6a6c::8ff8:6a6c CoAP LLRP poll 2001:220:806:20::1 LLRP Port: 5084 SNAIL Gateway RFID Reader FX7400 2001:220:806:22::1 143.248.106.220 PRETTY Cloud Servers Sensor Nodes RFID Tagged Devices Seahaven 53
  • 54. IOT CAN MAKE IT HAPPEN 54
  • 55. 55

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