Internet of Things (IOT) - Technology and Applications
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Keynote Presentation at UiTM WSN Seminar 2012
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Internet of Things (IOT) - Technology and Applications
- 2. Wireless Sensor Network (WSN) to IOT © 2012 MIMOS Berhad. All Rights Reserved. 2
- 3. Internet of Things : Anytime, anywhere, by anyone and anything – ITU, November 2005 Characteristics of IoT Internet of Things Computing Anytime Any content Content Anyone Anybody Collection Any Service Any Business Communication Any path Any Network Connectivity Any place Anywhere Convergence Anything Any device “We are heading into a new era of ubiquity, where the users of the Internet will be counted in billions, and where humans may become the minority as generators and receivers of traffic. Changes brought about by the Internet will be dwarfed by those prompted by the networking of everyday objects “ – UN report
- 4. Internet of Things (IOT) Definition © 2012 MIMOS Berhad. All Rights Reserved. Technology perspective: Things with identities & virtual personalities operating in smart spaces using intelligent interfaces to connect and communicate within social,environmental,and user contexts. Marketing perspective : Enable communication between devices to exchange useful information that create new value for human needs.
- 6. Rise of Machines © 2012 MIMOS Berhad. All Rights Reserved. Year 2020 scenario…… Internet connected devices 50B Utility meters 3B + Mobile consumers 7.6 B • People with chronic welfare diseases • Automotive & transportation 1B + Mobile Computing & M2M US$77B Connected life spending US$4.7T Annual mobile monitoring devices & services US$43B RFID US$20B Source: TrendsSpottting; IBM; Gartner; Ericsson
- 22. Ethernet ADSL Fiber HSDPA Deployment Scenario (WSN) HSDPA/ WiMAX/ LTE 6LoWPAN Network MIMOS MSCAN 2.4GHz 2.4GHz PAM Server MIMOS MSCAN - IOT Benefits: •Enabling end-to-end connectivity •Less processing and overhead = Less power consumption •Cheaper solution
- 23. Livestock Monitoring – Cow that “Tweets” WiWi Gateway Collar •Sensor Platform •Wireless Transmission Alert: SMS, custom application, twitter, etc Livestock Management System Handheld Device: local interrogation by farmer
- 26. IoT Technological Developments Development Areas Before 2010 2010-2015 >2015 Identification Technologies •Different Schemes •Domain specific IDs •ISO, GS1, u-code, IPv6, etc •Unified framework for unique identifiers •Open framework for IoT •URIs •Identity Management •Semantics •Privacy-awareness •“Things DNA” identifier IoT Architecture Technology •IoT architecture specification •Context-sensitive middleware •Intelligent reasoning platforms •IoT architecture developments •Network of networks architecture •Platforms interoperability •Adaptive, context based architectures •Self-* properties •Cognitive architectures •Experiential architecture Communication Technology •RFID, UWB, Wi-Fi, WiMax, Bluetooth, ZigBee, ISA100, 6LoWPAN •Ultra low power chipsets, system on chip •On chip antennas •Millimeter wave single chips •Ultra low power single chip radios •Ultra low power system on chip •Mobility •Heterogeneity •Wide spectrum and spectrum aware protocol •Unified protocol over wide spectrum Network Technology •Sensor networks •Self aware & self organizing network •Delay tolerant networks •Storage networks and power networks •Hybrid networking technologies •Sensor network location transparency •Network context awareness •Network cognition •Self learning, self repairing network Source: FP7 - Cluster of European Research Projects on the Internet of Things (CERP-IoT) - Strategic Research Agenda
- 27. IoT Technological Developments Development Areas Before 2010 2010-2015 >2015 Software and Algorithm •Relational database integration •IoT oriented RDBMS •Event-based platforms •Sensor middleware •Sensor network middleware •Proximity / localization algorithms •Large scale, open semantic software modules •Composable algorithms •Next generation IoT-based social software •Next generation IoT-based enterprise applications •Goal oriented software •Distributed intelligence, problem solving •T-to-T collaboration environments •User oriented software •The invisible IoT •Easy to deploy IoT software •Things to Human collaborations •IoT for all Hardware •RFID tags and sensors •Sensors build in mobile devices •NFC in mobile phones •Smaller and cheaper •MEMs technology •Multi protocol, multi standards reader •More sensors and actuators •Secure, low cost tags, sensors •Smart sensors (Bio-chem) •More sensors and actuators (tiny sensors) •Nano-technology and new materials Data & Signal Processing Technology •Serial data processing •Parallel data processing •Quality of services •Energy, frequency spectrum aware data processing, •Data processing context adaptable •Context aware data processing and •data responses •Cognitive processing and •optimisation Discovery and Search Engine Technology •Sensor network ontologies •Domain specific name services •Distributed registries, search and •discovery mechanisms •Semantic discovery of sensors and sensor data •Automatic route tagging and •Identification •Automatic route tagging and •identification management centres •Cognitive search engines •Autonomous search engines
- 28. IoT Technological Developments Development Areas Before 2010 2010-2015 >2015 Power and Energy Storage Technologies •Thin batteries •Li-Ion •Flat batteries •Power optimized systems •(energy management) •Energy harvesting (electrostatic, •piezoelectric) •Short and medium range •wireless power •Energy harvesting (energy conversion, •photovoltaic) •Printed batteries •Long range wireless power •Energy harvesting (biological, •chemical, induction) •Power generation in harsh •environments •Energy recycling •Wireless power •Biodegradable batteries •Nano-power processing unit Security and Privacy Technologies •Security mechanism and protocol defined (RFID & WSN) •Security mechanisms and protocols for RFID and WSN •devices •User centric context-aware privacy and policy •Privacy aware data processing •Virtualisation and anonymisation •Security & Privacy profiles based on needs •Privacy needs automatic evaluation •Context centric security •Self adaptive security mechanisms and protocols Material Technology •Silicon, Cu, Al Metallization •3D processes •SiC, GaN •Silicon •Improved/new semiconductor manufacturing processes / technologies for •higher temperature ranges •Diamond Standardization •RFID security •Passive RFID with expanded memory and read/write capability •IoT standardization •M2M •Interoperability •Standards for cross interoperability with heterogeneous networks Source: FP7 - Cluster of European Research Projects on the Internet of Things (CERP-IoT) - Strategic Research Agenda
- 29. 6LOWPAN
- 30. IEEE 802.15.4 • Specifies a wireless link for low-power personal area networks (LoWPANs) • 802.15.4 is widely used in embedded applications, such as environmental monitoring • These applications generally require numerous low-cost nodes communicating over multiple hops to cover a large geographical area, and they must operate unattended for years on modest batteries
- 32. IEEE 802.15.4 and IPv6 • Entire 802.15.4 MTU is 127 bytes • Low Bandwidth (250 kbps), low power (1 mW) radio • Small Packets to keep packet error rate low and permit media sharing • Often data payload is small • Standard IPv6 header is 40 bytes [RFC 2460] • IPv6 requires all links support 1280 byte packets [RFC 2460] 32
- 33. Benefits of 6LoWPAN Technology • Low-power RF + IPv6 = The Wireless Embedded Internet • 6LoWPAN makes this possible • The benefits of 6LoWPAN include: – Open, long-lived, reliable standards – Easy learning-curve – Transparent Internet integration – Network maintainability – Global scalability – End-to-end data flows
- 34. Why We Need It? • Open system based interoperability between devices • Leverage existing standards, rather than “reinventing the wheel” • Ability to work within the resource constraint of low- power, low-bandwidth and low-memory
- 35. Challenges in 6LoWPAN Deployment • No method exists to run IPv6 over IEEE 802.15.4 • Using IPv6 and other headers as it is may not fit – 40 bytes of IPv6, 20 bytes of TCP, 8 bytes of UDP + other headers • Existing routing protocol unsuitable • Current service discovery method too bulky • Fragmentation and reassembly layer • Limited configuration & management on sensors • Security issues • Network management – Memory, processor and packet size constraint of sensor, further investigation required on using existing network management protocol
- 37. Research Motivation • Interplanetary Internet (IPN) is a NASA research project led by Vint Cerf in 1998. • The basic idea is to try to make data communications in space/ between planets. • E.g. Communication between Earth and Mars – Communication is greatly delayed • The delay in sending or receiving data from Mars takes between three-and-a-half to 20 minutes at the speed of light. – Intermittent connectivity • Planetary movement • TCP is not suitable in space missions. • A new set of protocol is needed to tolerate large delay – IPN architecture was designed.
- 38. How to apply the IPN architecture to other situations in which communications were subject to delays and disruptions? -IPN researchers- Ø In 2002 - “Delay Tolerant Network Architecture: The Evolving Interplanetary Internet” was introduced for application on earth
- 39. Delay Tolerant Network (DTN) • DTN is a set of protocols that act together to enable a standardized method of performing store-carry-and- forward communications. • Characteristics of DTN: i. Intermittent connectivity – No end-to-end path between source and destination ii. Long variable delay – Long propagation delays between nodes A B B C C D Source Store Carry Forward Store Carry Forward Destination
- 40. Applications of DTNs Wildlife monitoring Communication in rural area Military Interplanetary internet
- 41. Wildlife Monitoring • ZebraNet – Goal: Track mobility patterns of zebras in Kenya, Africa. – Custom tracking collar with GPS (node) is put on the neck of the zebra. – Nodes record zebra’s location and stores in memory. – Nodes carry the data until meet another node. – Exchanges data with another zebra when in communication range. – Mobile base station (MBS) collects data from collars when researchers are in the field. - MBS is not fixed, rather it moves and is only intermittently available 41 P. Juang, H. Oki, Y. Wang, et al. Energy-Efficient Computing for Wildlife Tracking: Design Tradeos and Early Experiences with ZebraNet. In Proceedings of ASPLOS-X, Oct. 2002. Physical presence of the researchers is no longer required at the deployment site in order to collect and publish zebra mobility pattern data. ØNetwork connectivity is intermittent and opportunistic
- 42. Communications in Rural Areas • DakNet Goal: Provide low cost internet connectivity to poor rural areas in India A bus carrying a 802.11b access point Kiosks are built up in villages and are equipped with digital storage and short-range wireless communications. MAP transport data among public kiosks and a hub Ønon-real time(asynchronous)internet access Pentland, A., Fletcher, R. and Hasson, A. “DakNet: Rethinking Connectivity in Developing Nations”. IEEE Computer, vol. 37, no. 1 Jan. 2004, pp. 78–83.
- 44. Give it to me, I have 1G bytes phone flash. I have 100M bytes of data, who can carry for me? I can also carry for you! Thank you but you are in the opposite direction! Don’t give to me! I am running out of storage. Reach an access point. Internet Finally, it arrive… Search La Bonheme.mp3 for me Search La Bonheme.mp3 for me Search La Bonheme.mp3 for me There is one in my pocket…
- 45. In 2006, Lilien, Kamal, and Gupta have developed a similar paradigm as DTNs with the name of Opportunistic Networks (OppNets) L. Lilien, Z.H. Kamal and A. Gupta (in cooperation with V. Bhuse and Z Yang), "Opportunistic Networks: The Concept and Research Challenges," Department of Computer Science, Western Michigan University, Kalamazoo, Michigan, February 9, 2006.
- 46. Issues in DTN • Mobility Model – Network highly mobile and dynamic in nature • What is the mobility pattern? • Mobility patterns of assigned "carrier nodes” • Routing – The most challenging problem therefore lies in finding the route between two disconnected devices. • Trust – Finding “carriers nodes" network that trust • Most of the time we assume that the nodes cooperate with each other (i.e. hosts do not refuse to deliver messages) 46
- 47. Random Movement Random Walk Random Waypoint Mobility model Random movement Human behavior based movement Map-constrained random movement - each mobile nodes starts at a random location and staying there for a certain period of time (pause time) and at the end of the pause time, the nodes select a random destination and move to the selected destination at a random speed. - each mobile nodes starts at a random location and then move to a new location by randomly choosing a direction and speed.
- 48. Map-Constrained Random Movement e.g. KLCC (A) to KL Pavilion (B) Random Map-Based Movement Shortest Path Map-Based Movement Routed Map-Based Movement - move from stop to stop using shortest paths - nodes follow certain route (e.g. bus) Mobility model Random movement Human behavior based movement Map-constrained random movement 1 2
- 49. Mobility model Random movement Human behavior based movement Map-constrained random movement EKMAN, F., KER¨A NEN, A., KARVO, J., AND OTT, J. Working Day Movement Model. In Proc. 1st ACM/SIGMOBILE Workshop on Mobility Models for Networking Research (May 2008). -bring more reality of human movement patterns during a working day - It produces similar Inter-contact times and contact durations as real world traces - All nodes move on a real world map - There are three major activities: 1) Staying at home – node wake up in the morning 2) Working at the office - go to the office and works 8 hours 3) Doing some activity with friends in the evening - Use different transportation between activities (bus, car or walking) Working Day Movement Model (WDM) Human Behavior Based Movement
- 50. This is for Mrs. Wilson I will give the copy to everyone I meet, and hopefully it will reach her Concept: Floods messages into the network Goal: Maximize message delivery rate Disadvantages: - High resources usage (buffer) - High overhead Epidemic: Epidemic Routing for Partially Connected Ad Hoc Networks A. Vahdat and D. Becker. Epidemic Routing for Partially Connected Ad Hoc Networks. Technical Report CS-2000-06, CS. Dept. Duke Univ., 2000. Epidemic Spray and Wait Routing protocol Spray and Focus Prophet 50 Mrs. Wilson
- 53. Security & Privacy Opportunity Gaps © 2012 MIMOS Berhad. All Rights Reserved. Source : SRI Consulting Business Intelligence Intelligent Thing vs. Human Business impact Innovation opportunities High Low HighLow • Context awareness • Human-like inferences & decisions • Act on behalf of people Thing/Device • Miniaturization • Energy efficiency • Tagging & identification • System-in-package • Edge processing Network Encourage vs. discourage interaction and automation Governance policy • Market demand rely on affordability & attractiveness • Conversion cost : IoT investment vs. low-cost source of human labour • Adaptive network • Interoperability • Ad-hoc network mgmt.