Internet of Things (IoT) - Universitetet i...
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Internet of Things (IoT) 1 INF5050 February 19, 2016
Transcript of Internet of Things (IoT) - Universitetet i...
Internet of Things (IoT)
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INF5050
February 19, 2016
Outline
• Internet of Things (IoT)
• Key Technologies
– RFID
– Mobile Cloud Computing
Things
• A real/physical or digital/virtual entity that exists and moves in space and time
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Examples
• computers, sensors, people, actuators, refrigerators, TVs, vehicles, mobile phones, clothes, food, medicines, books, passports, luggage,…..
Explosion of connected things (devices/terminals/phones/sensors)
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Internet of Things (IoT) Visions
• IoT allows people and things to be connected
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Anyone can use anything to access
any service and any network at
anytime any place
Q: is it challenging to make one sentence to include all these Any* words?
1995 2004 2005 2008 2009-6 future
IoTconcept U-Korea
IBM: Smart Planet
Sensing China
2009-8
Internet of Things –action plan for EU
《ITU Internet Report 2005：The Internet of Things》
U-Japan
IoT development
IoT Application: Connected Vehicles for driving safety
View for the driver in the 2nd yellow car
“road slippery” message can be transmitted from the first car to the last white car
Connected Road: addressable sensors on the road and can be networked
• Increase safety
– Road surfacetemperature
– Road condition
• ice/snow/rain/dry/wet
– Tyre pressure monitoring
• Estimate traffic
– Number of vehicles passed in 15 minutes
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Sensors on the road
Outline
• Internet of Things (IoT)
• Key Technologies
– RFID
– Mobile Cloud Computing
KEY TECHNOLOGY: RFID
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RFID (Radio Frequency Identification)
• In IoT, normally the first question is to identify whom you are. RFID can answer this question.
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• RFID principle: devices are wireless microchips used for tagging objects for automatic identification
• RFID can identify objects wirelessly line-of-sight or non line of sight
Line-of-Sight (LoS)
Non Line-of-Sight (NLoS)
transmitter receiver
RFID systems
• RFID systems consist of
– Readers: read and write tag data
– Tags: carry object identification data
– Back-end database: to manage and deal with data
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Reader
Tag
RFID Frequency
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Source: centrenational-rfid
LF (low frequency): • Reading range is
limited• Can penetrate thin
metal• Work well with
high-water content (e.g., fruit)
• Application: animal tagging
HF (High frequency): • work well on
metal • Application:
tracking library books, patient flow tracking
UHF (Ultra-high Frequency): • Long range, high
data rate• Cannot penetrate
metal or water • Application:
electronic toll collection; parking access control.
Tags
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Passive tags Semi-passive tags Active tags
Energy resource No Battery Battery
Communicationrange
Short, 10meters Long, 100m+ Long, 100+
Communication mode
Response only Response only Response or Initiate
Price Low Medium high
Communication mode: ResponseTag waits for reader’s signal and sends feedback
❶
❷
Communication mode: InitiateTag sends signal to reader instead of waiting
❶
❷
Which tags are used in the applications?Applications Active, Semi-passive or Passive Tags
Reisekort
Shipping containers
Large assets tracking
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Passive
Active
Active
Which tags are used in the applications?Applications Active, Semi-passive or Passive
Tags
Electronic toll
Tracking componentslike automobile partsduring manufacture
electronic product code
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Semi-Passive
Semi-Passive
Passive
Tag 1
reader
Tag 2
Tag 3
Reading range
Reader’s reading range
17Q: what can affect the reading range?
Reading range
Tag
Reader
Tags collision problem
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• Collision occurs when multiple tags respond to the same reader at the same time. The reader is unable to differentiate these signals.
• Tag collision results in wastage of energy, increases identification delays.
• Readers must use an anti-collision protocol to minimizecollisions and help reduce identification delays
RFID anti-collision protocols: Alohabased protocols
• Pure Aloha
• Slotted Aloha
• Framed Slotted Aloha
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An example of ALOHA
RFID anti-collision: Pure Aloha
• Easy to implement– If a tag has data to send, send
the data
– If the message collides with another tag, try resending "later“
– On collision, sender waits random time before trying again
• A tag responds after a random delay, and continues until identified.
• Efficiency: 18.4%
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Tag1
Tag2
Tag3
Tag4
Tag5
Tag6
Tag7
Tag8
Tag9
Tag10
Collision
Collision
Q: have we seen ALOHA in other networks?
time
S: time slotAn example of slotted ALOHA protocol
RFID anti-collision: Slotted Aloha
• S-ALOHA divides time into timeslots.
• Each tag can send out data at the beginning of a timeslot.
• A tag responds in synchronized slots after random delay
• Efficiency: 36.8%
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S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11
Tag1
Tag2
Tag3
Tag4
Tag5
Tag6
Tag7
Tag8
Tag9
Tag10
Collision
Collision
RFID anti-collision: Frame-Slotted Aloha
• A tag randomly selects a slot to respond only once in a frame. If there is a collision, tags respond in the next frame
22Frame 1 Frame 2 Frame 3
Tag 1
Tag 2
Tag 3
channel
collision
• Tags collision
• Q: Readers have collision problem?
Collisions
RFID readers collision (I)
• Reader-to-Tag
– When a tag enters an overlapping area of two readers, transmitted signals will collide and tags will be unable to answer readers queries
A B
Reader A’s reading range
Reader B’s reading range
Tag
RFID readers collision (II)
• Reader-to-Reader
A B
Reader A’s reading range
Reader B’s reading range 𝑅𝑟
Reader B’s interference range 𝑅𝑖 = (1 + 𝛼)𝑅𝑟
Tag
Coverage based approach for Readers Anti-collision
• The reading ranges of readers are adapted dynamically to reduce the overlapped areas between adjacent readers
• Advantage: increases the space re-used ratio• Disadvantage: needs a central node to calculate the
distance between two readers and adjust their reading ranges, which will increase the complexity of realization and cost of the system
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A B
Reader A’s reading range
Reader B’s reading range Rr
Tag
Scheduling based Readers Anti-collision
• Resources (e.g., frequencies and time) are allocated properly among readers to prevent readers from transmitting simultaneously
• Advantage: reduce readers collision effectively • Disadvantage: requires the system to maintain information
over the network, which will be time and energy consuming
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A BTag
-Reader A transmits-after some time, e.g., 1sec-Reader B transmits
KEY TECHNOLOGY: MOBILE CLOUD COMPUTING
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MCC = Mobile + Cloud Computing
Cloud
Mobile network
Cloud computing
4G/wifi
Q: can you name some MCC services that we use everyday?
Motivations for MCC
• Internet traffic explosion; while smart phones generate more than half of mobile data traffic
• Internet-of-Things Vision of anything connected
• Mobile devices still lack in resources compared to a conventional device such as laptops or powerful servers in cloud– battery lifetime
– network bandwidth
– storage capacity
– processor performance
Mobile Devices/Terminals/Machines
• Smart phones• Laptops• Tablet (e.g., Apple iPad, Samsung Galaxy Tab, Sony
Xperia)• Sensors, actuators, robots• Embedded systems (e.g., RFID readers and tags)• Vehicles• Glasses• Satellites
• and many more…
MCC definition
• According to Mobile Cloud Computing Forum
• In plain language– MCC moves data processing and storage from mobile
phones to cloud
Mobile Cloud Computing at its simplest refers to an infrastructure where both the data storage and the data processing happen outside of the mobile device. Mobile cloud applications move the computing power and data storage away from mobile phones and into the cloud, bringing applications and mobile computing to not just smart phone users but a much broader range of mobile subscribers
MCC 1st Perspective: using mobile devices to access cloud
• Infrastructure mode
• Example: using your mobile phone to access gmail, dropbox, facebook etc.
Mobile Device
Mobile Clone
Execution Engine
ApplicationServer
ApplicationOffloading
TaskDelegation
Data Storage
MCC 2nd Perspective: mobile devices are cloud
• Ad hoc mode: use mobile devices for a self-organized cloud
• Share resources (computation, storage) among devices
• Run cloud services by mobile devices
• Q: any example?
Online Services
Mobile Media
Urgent Tasks
Vehicular Cloud: example
• Hundreds cars unused for hours on a typical workday– Vehicles can share
computation/storage resources
• Storage resource sharing (e.g., Storage as a Service)
– Computers in cars have on-board storage
– Data center in airport parking lot
MCC advantages
• Extending battery lifetime
– Voice recognition, e.g., Siri, is computation intensive
• Improving data storage capacity and computation capability
• Improving data reliability and security
MCC challenges
• Wireless Communication side– Limited radio bandwidth– Network latency– Availability
• Device side– Limited energy
• Computation side– Computation offloading– Data access efficiency– Context-aware cloud services
OFFLOADING FOR MOBILE CLOUD
Computation Offloading
• Offloading: sending heavy computation to resourceful servers and receiving the results from these servers.
• Q: do you believe: using WiFi in IFI instead of 4G is offloading?
Cloud
Computation request
Result: 6
❶
❷
❸
Computation in cloud
Offloading schemes for energy-saving in mobile phones
Energy usage when computing is done in mobile phones
• Pc: the energy cost when the mobile phone is doing computing
• C: the computation needs C instructions • M: the speed of mobile device to compute
Energy usage when computing is done in cloud
• Pi: energy cost when the mobile phone is idle.• Ptr: energy cost when the mobile transmits the data• S: the speed of cloud to compute• D: the data need to transmit• B: the wireless bandwidth
Saved energy by using offloading
Energy-efficiency in offloading schemes
• Suppose the cloud is F times faster—i.e., S = F ×M. Then, saved energy is
• Energy is saved when this formula produces a positive number.
• The formula is positive if
Observations
• Offloading is beneficial when a task needs
– large computation C
– relatively small communication D
K. Kumar and Y. Lu: Cloud Computing for Mobile Users: CanOffloading Computation Save Energy?. IEEE Computer 43(4): 51-56 (2010)
Large C Small D
But, offloading does not help when wireless channel has low quality
• Service areas in – Tunnel
– Subway
– Q: other examples?
• In these scenarios, – the bandwidth B is very small,
D/B approaches infinite.
– cloud computing does not save energy.
B0; then, D/B ∞
Application may benefit from offloading: photo retrieval as an example
• Search and retrieve images in photo sharing databases
• D is large since considerable data must be sent; hence D/B might be too large
Condition• Only if the bandwidth B is
very large, offloading saves energy (Q: why?)
Real-time Navigation
• When D is very large, offloading may not save energy
Q: what should be considered to use partitioning computation?
• Partitioning computation between the mobile phone and the cloud may reduce energy consumption.
Partitioning Computation
• We need to determine– whether to offload – which units of computation
should be moved to the cloud
• We need to consider– Computation cost– Communication cost– Energy consumption– Communications quality: data
between devices and cloud may be lost
Cloud
70% tasks moved to cloud
30% tasks donein mobile phone
