Politecnico di Milano Advanced Network Technologies Laboratory. Course Mechanics

Transcription

1 Politecnico di Milano Advanced Network Technologies Laboratory Course Mechanics 1

2 The Course Team o Instructor n Matteo Cesana o matteo.cesana@polimi.it o o o Office Hours: Tuesday, o Teaching Assistant n Alessandro Redondi o alessandroenrico.redondi@polimi.it 2

3 Support Material and Syllabus o Course Web Site o Background papers to be provided 3

4 Slide Sources o Part of the slides used in this course are adapted from: n Ian F. Akyildiz, Sensor Networks, n/classes.html n D. Culler, Wireless Embedded Internetworking, o See also the source slides for the valuable contribution 4

5 Grading o Grade Composition n Written Exam: 26/30 n Project: up to 8/30 (100% by September 28, 2017, 50% by February 2018) o Must-Know Issues: n Students must be regularly and formally registered to an exam to have a positive grade registered (PoliSelf). n Grades obtained in a given exam (date) remain valid until the student submits a new final exam. n Grades can be registered in any exam date, provided that the student have regularly and correctly registered to the exam. 5

6 Exam Dates o June 26, 2017 (time TBD) o July 24, 2017 (timetbd) o September 7, 2017 (time TBD) o September 28, 2017 (time TBD) 6

7 Politecnico di Milano Advanced Network Technologies Laboratory Introduction and Impact 7

8 The Classical Internet User Terminals Access Networks Back Bone o Mostly Static Clients accessing Well Known services in the network 8

9 Transition Steps o Internet Clients are going Mobile (Cell Phones, PDAs), n 80% of twits coming from mobile devices 1 n 90% mobile user penetration in developed countries 2 o Mobile Clients with Sensing and Actuating capabilities n Client themselves become information/service producers 1 FierceWireless 2011, 2 ITU

10 The pulse of New York 10

11 Technology Push o o o o CMOS miniaturization Micro-sensors (MEMS, Materials, Circuits) n acceleration, vibration, gyroscope, tilt, magnetic, heat, motion, pressure, temp, light, moisture, humidity, barometric n actuators Communication n short range, low bit-rate, CMOS radios (1-10 mw) Power n Batteries (1,000 mw*s/mm 3 ), fuel cells 10x n solar (10 mw/cm 2, 0.1 mw indoors), vibration (~uw/gm), flow n 1 cm 3 battery => 1 year at 10 msgs/sec Source: Lecture slides of Wireless Embedded Internetworking, Prof. D. Culler 11

12 New Class of Computing log (people per computer) Mainframe Minicomputer Workstation PC Laptop PDA year 12

13 The new Internet Users o Tiny, cheap and unattended devices with sensing and communication capabilities spread all over n n n in the environment (ambient intelligence) in objects (embedded computing) on body (wearable computing) o The target is no longer reaching a specific IP but rather reaching a specific content/service Un mondo di smart objects 13

14 Ambient Intelligence Science Fiction Minority Report, 2002 Steven Spielberg 14

15 Ambient Intelligence- Reality Estimote 15

16 E-Health LAURA 16

17 Future Internet User Terminals Access Networks Back Bone EdgeNet 17

18 IoT: Several Definitions o Common Features: n Smart Objects n Data Capture n Pervasiveness n Seamless Communication o o o A global network infrastructure, linking physical and virtual objects through the exploitation of data capture and communication capabilities. This infrastructure includes existing and evolving Internet and network developments.. (CASAGRAS) A world where physical objects are seamlessly integrated into the information network, and where the physical objects can become active participants in business processes.. (Future Internet EU Initiative) A world-wide network of uniquely addressable interconnected objects, based on standard communication (ETP-EPOSS) 18

19 Rough Market Size o Current Internet n 700 Million hosts n 1.4 Billion users o 100+ Billion microcontrollers worldwide o 10 Billion shipments a year o The Internet of Things has the potential for a size in Trillions o By B connected devices (Cisco), 40ZB of data (IDC) 19

20 Traffic 2015: 1.2B vehicles (1 vehicle each 6 people) 1 Fonti: 1 R. L. Polk

21 Smart Parking Ingredients: Asphalt sensors and/or cameras Communication technologies Intelligence to manage the parking information End user Apps Ex: SFPark park meters spots -Dynamic pricing to incentivize virtuous users behavior 21

22 Environment Gestione rifiuti Energy efficiency Pollution 75% of GHG emissions due to cities Cities cover 2% of Earth surface 1 Source:

23 Waste Management Ingredients: Sensors in thrash cans Communication technologies/systems Intelligence to manage/optimize collection squads End-user Apps Control center 23

24 Smart Energy Ingredients: WSN to monitor power consumption and user profiles Algorithms to optimally schedule appliances Communication channel with the power supplier to get energy prices Communication channel with the Internet to get context data (meteo) End user App Energy Tariff Estimated Load & PV Production 24

25 IoT Building Blocks and Challenges SECURITY RELIABILITY/ROBUSTNESS Things Connectivity Data Analytics 25

26 IoT Challenges: Security SECURITY o Scenario 1 : n Bio-sensor detects heart attack and calls 911 n while waiting Messagge From: Loony Pharma Obj: new drug Try our new product! Message From: Health Insurance Obj: contract upgrade The contract fee was unilaterally increased of 50% 1 from John Barret, TED talks 26

27 IoT Building Blocks and Challenges RELIABILITY/ROBUSTNESS o Hardware level: n Data collected must be reliable/consistent n Device must live in harsh environment o Software level n Communication protocols must be robust to failures, changing topologies, interferences, etc. n Self healing, self configuration functionalities needed 27

28 IoT Challenges: Things Things o Cost reduction o Miniaturization o Energy Efficiency o Resiliency o Design, H&M interfaces 28

29 IoT Challenges & Core Blocks: Connectivity Connectivity o What communication technologies? n Energy efficiency is a must n Single-hop vs Multi-hop o What communication protocols? n Classical protocols not suited n The integration issue 29

30 IoT Challenges & Core Components: Data & Analytics Data Analytics Scale (# devices) o CISCO(2011): 50B o Gartner (2013): 26B o MK (2011): 75B 30

31 Course Plan & Objectives o To give you a comprehensive view of the Internet of Things o To analyze the core components to make it happen n Focus on Things, Connectivity ; we ll see also something about Data & Analytics o Hands on activities n Guidelines on how to operate things in the Internet of Things 31

32 The Course in a Nutshell o The IoT n n Definition, Applications and Challenges Enabling Technologies (WSNs and RFIDs) o Handling Embedded Devices n Hardware Abstractions, Design Constraints, PHY alternatives o IoT Connectivity n n Low Power Long Range Solutions: LoraWAN Low Power Short Range Solutions: ZigBee and 6LowPAN o IoT Application Layers n COAP and MQTT o Radio Frequency Identification n n Applications and Available Technologies Collision Arbitration 32

33 Hands On Activities o Operating Networks of Embedded Devices n Playing with TinyOS/NesC n Playing with Contiki n Playing with ThingSpeak/SixthSense/NodeRed o Calendar (Tentative, keep checking web site): n March 29 n April 12 n April 26 n May 10 n May 17 n May 31 33