Sense & Sensibility for Wireless Networks

Hari Balakrishnan Department of EECS and CSAIL

M.I.T. nms.csail.mit.edu/~hari

The Era of Truly Mobile Computing

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Desktop Users

Source: Morgan Stanley Research

5B mobile phones in the world Exceeds #people with shoes, toilets, electricity! 1B with “broadband” capability

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Gigabytes/user/m

onth  

Average  Demand  Per  Cellular  User  

Projection: Rysavy Research, 2010

Survey by TeleNav

1 hr netflix

1 hr HD video

Average wired broadband @home: US: 18 GB/mo (AT&T) UK: 17-19 GB/month (2011)

Mobile Apps All Around Us

Smart Homes

Public Safety

Entertainment & Social Lives

Healthcare Transportation

Sensor-rich systems

Apps demand robust, high-performance wireless networks Difficult as load and node density increase

Difficult as channel conditions change with time

Truly Mobile Devices

•  Often switch between static and mobile •  Exhibit a variety of mobility modes •  Move through different environments

Mobility à Time-varying Channels & Topology

Slow walk

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Bit

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How to determine the best bit rate to transmit a packet?

802.11n: 32 possible ���[constell’n X code X stream] ���

combinations

symbol sets (= constellation)

Example: 802.11a/g���8 bit rates: 6, 9, 12, 18, 24, 36, 48, 54 Mbps

Two possible codes���per constellation���

(Rate 1/2 or 3/4 conv. codes)

Bit Rate Selection

•  Measure wireless channel – Frame loss rate at different bit rates ���

[SampleRate, RRAA, ARF, …]

– Signal-to-noise ratio (SNR) ���[RBAR, CHARM, …, 3GPP]

•  Determine best bit rate given measurement

•  Problem: Measurements quickly outdated over time-varying channels

Accelerometer  

Proximity    Sensor   Camera  

GPS  

Compass  

Gyro  

Many,  many,  applications…  

The Big Idea: Sensors on Devices

Ambient  Light    Sensor   Microphone  

Applica<on  

Transport  

Network  

Link/MAC  

PHY  

Radio  

Protocol Stack

Accelerometer  

Proximity    Sensor   Camera  

GPS  

Compass  

Gyro  

Largely ignored by protocols!

The Opportunity: Sensors

Ambient  Light    Sensor   Microphone  

Applica<on  

Transport  

Network  

MAC  

PHY  

Radio  

Protocol Stack

GPS  

Compass  

Accl  

Gyro  

•  Position •  Movement •  Direction •  Speed

Use  hints  to  adapt  to  different  mobility  modes  differently  

Integrate Sensor Hints into the Network Stack

Mobility hint protocol Adapt  to  hints  from  neighbors  

Sensor  Hints  

Applica<on  

Transport  

Network  

MAC  

PHY  

Radio  

Protocol Stack

GPS  

Compass  

Accl  

Gyro  Rate  Selec<on  Movement  

Heading  AP  Associa<on  

Speed  

Vehicular  Rou<ng  

Walking  

Integrate Sensor Hints into the Network Stack

L. Ravindranath, HB, C. Newport, S. Madden, Improving wireless network performance using sensor hints, NSDI 2011

Applica<on  

Transport  

Network  

MAC  

PHY  

Radio  

Protocol Stack

GPS  

Compass  

Accl  

Gyro  Rate  Selec<on  Movement  

Heading  AP  Associa<on  

Speed  

Topo  maintenance  

Packet  Scheduling  

Power  Saving  Cyclic  Prefix  

Network  Monitoring  

Speed  

Walking  

Loca<on   Vehicular  Rou<ng  

Integrate Sensor Hints into the Network Stack

L. Ravindranath, HB, C. Newport, S. Madden, Improving wireless network performance using sensor hints, NSDI 2011

3-­‐axis  accel   Movement  

Reliably detect movement within 10-100 ms on ���

commodity Android devices

Is the device is static or moving?

Extracting Hints: ���Movement Example

Probability  that  packet  i  is  lost  given  packet  i-­‐k  is  lost  

Losses more bursty when node is moving than when static. RapidSample: protocol to adapt while moving (small history)

Static v. Mobile Loss Performance

Applica<on  

Transport  

Network  

Rate  Selec<on  

PHY  

Wireless  Radio  

Wireless Protocol Stack

Accl  

Movement  

•  RapidSample when moving���Quick response to channel changes

•  SampleRate when static ���Slower response to channel changes

Movement  

Hint-Aware Rate Selection

Use two different protocols, switching between them using sensor hints

Rate selection: 40-60% faster than previous protocols

Hint-­‐aware  Experimental Results

Sensor-Augmented Protocols: Results

Access point selection 40% fewer handoff disruptions than current scheme

Vehicular network routing 2-5x longer connection time

Mobile topology maintenance 20x reduction in probe bandwidth for

Scan   Scan  Infrequent  scans    (because  it  wastes  channel)  

Picking a Good Access Point (AP)

Walking-Aware Association

1. Static – Stop Scanning 2. Walking – Scan Periodically

3. Walking to Static – Scan once

How to maximize mobile throughput?

Heading-Aware Association

Heading  

How to minimize handoffs (disruptions)?

Use  direc)on  of  movement  to  pick  AP  Ø  Background  Android  applica<on  Ø  Training:  WiFi  scans  +  Heading  hint  Ø  Query  the  model  with  current  AP  

and  heading  hint  

Hint-Aware AP Selection

30% higher median throughput

•  Android implementation •  30 traces; Static + Moving

40% median reduction in handoffs

•  Throughput  •  #  handoffs  

•  Energy – Accelerometer, compass are cheap but GPS is not – Triggered sensing + adapt sample rates

•  Calibration across device types – Movement hint required no calibration – Walking hint required tuning

•  Why not network measurement (SNR/RSSI)? – Variable and hard to measure reliably

•  Privacy

Potential Concerns

Applica<on  

Transport  

Network  

MAC  

PHY  

Radio  

Protocol Stack

GPS  

Compass  

Accl  

Gyro  Rate  Selec<on  Movement  

Heading  AP  Associa<on  

Speed  

Topo  maintenance  

Packet  Scheduling  

Power  Saving  Cyclic  Prefix  

Network  Monitoring  

Speed  

Walking  

Loca<on   Vehicular  Rou<ng  

Sensor Hints���External Information in Network Protocols

L. Ravindranath, HB, C. Newport, S. Madden, Improving wireless network performance using sensor hints, NSDI 2011

•  Truly mobile devices will soon be dominant – Variety of mobility modes poses problems

•  Sensors on mobile devices give us a great opportunity to develop new protocols – On-going: apply activity abstraction more widely

•  Sensor-augmented protocol architecture – Senseless to design mobile networks any other

way! Acks: Lenin Ravindranath, Sam Madden, Cal Newport (collaborators), NSF, and Om Malik for the title idea (http://gigaom.com/2011/04/15/why-apps-need-some-sense-and-sensibility/)

Embed Sense into Wireless Protocols!