![Middleware
• Middleware
is
a
so/ware
layer
that
stands
between
the
networked
opera4ng
system
and
the
applica4on
and
provides
well
known
reusable
solu4ons
to
frequently
encountered
problems
like
heterogeneity,
interoperability,
security,
dependability
[Issarny,
2008]
• IoT
requires
stable
and
scalable
middleware
solu1ons
to
process
the
data
coming
from
the
networking
layers
17](https://image.slidesharecdn.com/8iot-180304134904/85/8-iot-17-320.jpg)
8 iot
- 1. Internet of Things (IoT) CSE237A Introduc1on to Embedded Compu1ng
- 2. Outline • Introduc1on to IoT • Enabling technologies • Open problems and future challenges • Applica1ons 2
- 3. What is IoT? • A phenomenon which connects a variety of things – Everything that has the ability to communicate 3
- 4. Connec1on of Mul1ple Visions 4 Source: Atzori et al. 2010
- 5. IoT Defini1ons • The Internet of Things, also called The Internet of Objects, refers to a wireless network between objects, usually the network will be wireless and self-‐configuring, such as household appliances. (Wikipedia) • The term "Internet of Things" has come to describe a number of technologies and research disciplines that enable the Internet to reach out into the real world of physical objects. (IoT 2008) • “Things having iden11es and virtual personali1es opera1ng in smart spaces using intelligent interfaces to connect and communicate within social, environmental, and user contexts”. (IoT in 2020) 5
- 6. IoT Evolu1on • Starts with only network and evolves into everything that can be connected with a network 6 Source: Perera et al. 2014
- 7. Any-‐X Point of View • The Internet of Things allows people and things to be connected Any1me, Anyplace, with Anything and Anyone, ideally using Any path/ network and Any service. 7 Source: Perera et al. 2014
- 8. Characteris1cs of IoT 1. Intelligence – Knowledge extrac1on from the generated data 2. Architecture – A hybrid architecture suppor1ng many others 3. Complex system – A diverse set of dynamically changing objects 4. Size considera1ons – Scalability 5. Time considera1ons – Billions of parallel and simultaneous events 6. Space considera1ons – Localiza1on 7. Everything-‐as-‐a-‐service – Consuming resources as a service 8
- 9. IoT Layered Architecture 9 Sensing And Communica>on Middleware and Applica>ons Source: ZTE
- 10. Networking and Communica1on • RFID to smallest enabling technologies, such as chips, etc. 10 Source: Qian Zhang. Lecture notes. 2013
- 11. RFIDs • The reduc1on in terms of size, weight, energy consump1on, and cost of the radio takes us to a new era – This allows us to integrate radios in almost all objects and thus, to add the world ‘‘anything” to the above vision which leads to the IoT concept • Composed of one or more readers and tags • RFID tag is a small microchip a`ached to an antenna • Can be seen as one of the main, smallest components of IoT, that collects data 11
- 12. Wireless Technologies • Telecommunica1on systems – Ini1al/primary service: mobile voice telephony – Large coverage per access point (100s of meters – 10s of kilometers) – Low/moderate data rate (10s of kbit/s – 10s of Mbits/s) – Examples: GSM, UMTS, LTE • WLAN – Ini1al service: Wireless Ethernet extension – Moderate coverage per access point (10s – 100s meters) – Moderate/high data rate (Mbits/s – 100s) – Examples: IEEE 802.11(a-‐g), Wimax 12 Source: Geert Heijenk. Mobile and Wireless Networking. Lecture Notes. 2014
- 13. Wireless Technologies • Short range: – Direct connec1on between devices – sensor networks – Typical low power usage – Examples: Bluetooth, Zigbee, Z-‐wave (house products) • Other examples: – Satellite systems • Global coverage • Applica1ons: audio/TV broadcast, posi1oning, personal communica1ons – Broadcast systems • Satellite/terrestrial • Support for high speed mobiles – Fixed wireless access • Several technologies including DECT, WLAN, IEEE802.16, etc. 13 Source: Geert Heijenk. Mobile and Wireless Networking. Lecture Notes. 2014
- 14. Sensor Networks (SNs) • Consist of a certain number (which can be very high) of sensing nodes (generally wireless) communica1ng in a wireless mul1-‐hop fashion 14Source: Perera et al. 2014
- 15. Sensor Networks (SNs) • SNs generally exist without IoT but IoT cannot exist without SNs • SNs have been designed, developed, and used for specific applica1on purposes – Environmental monitoring, agriculture, medical care, event detec1on etc. • For IoT purposes, SNs need to have a middleware addressing these issues: – Abstrac1on support, data fusion, resource constraints, dynamic topology, applica1on knowledge, programming paradigm, adaptability, scalability, security, and QoS support 15
- 16. Example: Indoor Localiza1on • An indoor positioning system (IPS) is a solution to locate objects or people inside a building using radio waves, magnetic fields, acoustic signals, or other sensory information collected by mobile devices. • For indoor localization: – Any wireless technology can be used for locating – GPS, WiFi, Bluetooth, RFID, Ultrawide band, Infrared, Visible light communication, Ultrasound 16
- 17. Middleware • Middleware is a so/ware layer that stands between the networked opera4ng system and the applica4on and provides well known reusable solu4ons to frequently encountered problems like heterogeneity, interoperability, security, dependability [Issarny, 2008] • IoT requires stable and scalable middleware solu1ons to process the data coming from the networking layers 17
- 18. Service Oriented Architecture (SOA) 18 • Middleware solu1ons for IoT usually follow SOA approaches • Allows SW/HW reuse – Doesn’t impose specific technology • A layered system model addressing previous issues – Abstrac1on, common services, composi1on Source: Atzori et al. 2010
- 19. Other Middleware Examples • Fosstrak Project – Data dissemina1on/aggrega1on/filtering/interpreta1on – Fault and configura1on management, lookup and directory service, tag ID management, privacy • Welbourne et al. – Tag an object/create-‐edit loca1on info/combine events collected by antennas • e-‐Sense Project – Middleware only collects data in a distributed fashion and transmits to actuators • UbiSec&Sens Project – Focuses on security à secure data collec1on, data store in memory, etc. 19
- 20. Open Problems and Challenges • Lack of standardiza1on • Scalability – Addressing issues – Understanding the big data • Support for mobility • Address acquisi1on • New network traffic pa`erns to handle • Security/Privacy issues 20
- 21. Standardiza1on • Several standardiza1on efforts but not integrated in a comprehensive framework • Open Interconnect Consor1um: Atmell, Dell, Intel, Samsung and Wind River • Industrial Internet Consor1um: Intel, Cisco, GE, IBM • AllSeen Alliance: Led by Qualcomm, many others 21
- 22. Scalability • Number of devices increasing exponen1ally – How can they uniquely be tagged/named? – How can the data generated by these devices be managed? 22
- 23. Addressing Issues • Incredibly high number of nodes, each of which will produce content that should be retrievable by any authorized user – This requires effec1ve addressing policies – IPv4 protocol may already reached its limit. Alterna1ves? – IPv6 addressing has been proposed for low-‐power wireless communica1on nodes within the 6LoWPAN context • IPv6 addresses are expressed by means of 128 bits à1038 addresses, enough to iden1fy objects worth to be addressed • RFID tags use 64–96 bit iden1fiers, as standardized by EPCglobal, solu1ons to enable the addressing of RFID tags into IPv6 networks 23 Encapsulation of RFID message into an IPv6 packet. Source: Atzori et al. (2010)
- 24. New Traffic to Handle • The characteris1cs of the smart objects traffic in the IoT is s1ll not known – Important à basis for the design of the network infrastructures and protocols • Wireless sensor networks (WSNs) traffic characteriza1on – Strongly depend on the applica1on scenario – Problems arise when WSNs become part of the overall Internet – The Internet will be traversed by a large amount of data generated by sensor networks deployed for heterogeneous purposes à extremely different traffic characteris1cs – Required to devise good solu1ons for suppor1ng quality of service 24
- 25. Security 25 Man in the middle attack Source: Atzori et al. (2010) • Data integrity – Data should not be modified without the system detec1ng it – A`acks on the node • Memory protec1on – A`acks over the network • Keyed-‐Hash Message Auth. Code • The components spend most of the 1me una`ended – It is easy to physically a`ack them • IoT components are characterized by low capabili1es in terms of both energy and compu1ng resources – They can’t implement complex schemes suppor1ng security • Authen1ca1on problem – Proxy a`ack, a.k.a. man in the middle a`ack problem
- 26. Privacy • How is it different than tradi1onal privacy? – Legisla1ve issues – Ethics issues • Easy for a person to get involved in IoT even if he/she does not know • Data can be stored indefinitely • Current solu1ons are not enough – Encryp1on, pseudo-‐noise signal, privacy broker 26
- 27. Again -‐ Overall Picture 27 Source: “What the Internet of Things (IoT) Needs to Become a Reality,” White Paper, by K. Karimi and G. Atkinson
- 28. Applica1ons • Several different domains – Transporta1on and logis1cs – Healthcare – Smart environment (home, office, etc.) – Personal and social domain 28
- 29. Applica1on Domains and Scenarios 29Source: Atzori et al. 2010
- 30. Healthcare Applica1ons • Various sensors for various condi1ons • Example ICP sensor: Short or long term monitoring of pressure in the brain cavity • Implanted in the brain cavity and senses the increase of pressure • Sensor and associated electronics encapsulated in safe and biodegradable material • External RF reader powers the unit and receives the signal • Stability over 30 days so far 30 Source: Qian Zhang. Lecture notes. 2013
- 31. Healthcare Applica1ons • Other applica1ons: – Na1onal Health Informa1on Network – Electronic Pa1ent Record – Home monitoring and control • Pulse oximeters, blood glucose monitors, infusion pumps, accelerometers – Bioinforma1cs • Gene/protein expression • Systems biology • Disease dynamics 31Source: Qian Zhang. Lecture notes. 2013
- 32. Environmental Applica1on: Ci1Sense • Air quality monitoring project in UCSD CSE • Environmental applica1on • Electrochemical sensors, microcontroller for data collec1on and transmission to an Android app • Actua>on: air quality is immediately reported, as well as retransmi`ed to a backend for larger-‐scale analysis 32
- 33. Transporta1on Applica1ons • Vehicle control: Airplanes, automobiles, autonomous vehicles – All kinds of sensors to provide accurate, redundant view of the world – Several processors in cars (Engine control, break system, airbag deployment system, windshield wiper, door locks, entertainment system, etc.) – Actua1on is maintaining control of the vehicle – Very 1ght 1ming constraints and requirements enforced by the plarorms 33
- 34. Example Transporta1on Scenarios 1. A network of sensors in a vehicle can interact with its surroundings to provide informa1on – Local roads, weather and traffic condi1ons to the car driver – Adap1ve drive systems to respond accordingly 2. Automa1c ac1va1on of braking systems or speed control via fuel management systems. – Condi1on and event detec1on sensors can ac1vate systems to maintain driver and passenger comfort and safety through the use of airbags and seatbelt pre-‐tensioning 3. Sensors for fa1gue and mood monitoring based on driving condi1ons, driver behavior and facial indicators – Ensuring safe driving by ac1va1ng warning systems or directly controlling the vehicle 34Source: Qian Zhang. Lecture notes. 2013
- 35. Smart Home Applica1ons • Smart meters, hea1ng/cooling, mo1on/temperature/ ligh1ng sensors, smart appliances, security, etc. 35
- 36. A Futuris1c Applica1on: Shopping • When entering the doors, scanners will iden1fy the tags on her clothing. • When shopping in the market, the goods will introduce themselves. • When paying for the goods, the microchip of the credit card will communicate with checkout reader. • When moving the goods, the reader will tell the staff to put a new one. 36Source: Qian Zhang. Lecture notes. 2013
- 37. An exci1ng future! 37