Wireless “ESP”: Using Sensors to Develop Better Network Protocols Lenin Ravindranath Calvin Newport, Hari Balakrishnan, Sam Madden Massachusetts Institute.

Wireless “ESP”: Using Sensors to Develop Better Network Protocols

Lenin RavindranathCalvin Newport, Hari Balakrishnan, Sam Madden

Massachusetts Institute of Technology

Big Changes in Access Devices

• 172M smartphones sold worldwide in 2009– 25% of US phone market; 50% in two years

• Smartphones and tablets will exceed PC sales by 2011

• Mobile Internet growing at a tremendous pace

Big Changes in Access Devices

Dominant mode of data access in the future

“Truly Mobile” Devices• Often switch between static and mobile• Exhibit a variety of mobility modes• Move through different environments

• Protocols need to adapt to different settings – Mobility mode impacts wireless performance

The Problem

• Most protocols optimized for static settings– They perform poorly during mobility

• Protocols that compensate for mobility are not optimal in static settings

Static vs. Mobile• Channel constantly changing

– Channel assessments quickly outdated– Protocols should not maintain long

histories

• Channel relatively stable– Protocols can average estimates– Ignore short-term variations

• Topology is hardly changing– Probe for links less frequently– Compute routes over long time scales

• Topology changing rapidly– Probe for links more often– Compute routes over shorter time scales

Static vs. Mobile

Current Wireless Protocols

• Do not differentiate between mobility modes • Attempt to adapt to both settings implicitly

using measurements of packet loss, SNR, BER• Leading to suboptimal performance

• Lack of explicit knowledge about prevalent mobility mode

• Can we do better?

Proximity Sensor Camera

Ambient Light Sensor Microphone

Accelerometer

GPS

Compass

Gyro

Accelerometer



GPS

Compass

Gyro

Many, many, applications…

Accelerometer



GPS

Compass

Gyro

Ignored by Protocols!

Application

Transport

Network

MAC

PHY

Wireless Radio

Wireless Protocol Stack

Accelerometer



GPS

Compass

Gyro

Ignored by Protocols!

Application

Transport

Network

MAC

PHY

Wireless Radio


Accelerometer

GPS

Compass

Gyro

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl

Gyro

Hints

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl

Gyro

Hints

• Movement• Direction• Speed

Use hints to adapt to different mobility

modes differently

Hints Protocol

Adapt to hints from neighbors

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl

GyroRate AdaptationMovement

HeadingAP Association

Speed

Vehicular Routing

Walking

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl



Speed

Disassociation

Packet Scheduling

Power SavingPreamble

Network Monitoring

Speed

Walking

Location Vehicular Routing

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl



Speed

Walking

Vehicular Routing

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl


Accl

Movement

Reliably detect movement within 100ms

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl


Rate Adaptation in Wireless Networks

6 Mbps9 Mbps12 Mbps18 Mbps24 Mbps36 Mbps48 Mbps54 Mbps

802.11a/g bit rates

Packet encoded at a particular bit rate

Rate Adaptation:Finding the best bit rate to transmit a packet

Static vs. Mobile Performance• Static and walking traces

– Cycle through bit rates

• 4 different environments– 80 traces, 20 seconds long

• Trace-driven simulation– TCP throughput

Static Sample Rate 85 – 99%

RRAA 80 – 97%

RBAR 70 – 80%CHARM

MovingSample Rate 33 – 59%

RRAA 45 – 63%

RBAR 60 – 75%CHARM

Compare to optimal throughput

Static vs. Mobile Loss PatternsProbability that packet i+k is lost given packet i is lost

10 ms

Losses are more bursty when a node is mobilethan when a node is static

k



RapidSample


1. After a single loss Reduce rate

2. History - 10 ms Don’t retry a failed rate Or any higher rate

3. Channel not degrading, probably improving After few successes, sample

higher rate not failed If wrong, come back to the

original rate

[failed – within last 10ms]

[failed – within last 10ms]

RapidSample, when device is moving

Up to 75% better throughput than SampleRate25% better than other protocols

• Trace driven (ns3)• 30 traces• 20 seconds long• TCP throughput

But when static…

Up to 30% lower throughput than other schemes

• Trace driven (ns3)• 30 traces• 20 seconds long• TCP throughput

Application

Transport

Network

Rate Adaptation

PHY

Wireless Radio


GPS

Compass

Accl

Gyro Movement

• RapidSample when movement

• SampleRate when static

Movement

Hint-Aware Rate Adaptation

Hint-Aware Rate Adaptation

40-50% better than other schemes

• Trace driven (ns3)• 10 traces• 20 seconds long• Static + Moving• TCP throughput

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl



Speed

Walking

Vehicular Routing

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl

Gyro


Walking

AP Association

Scan Scan ScanInfrequent scans

AP Association

Suboptimal Association

Static

Movement-Aware Association

1. Static – Stop Scanning

2. Moving – Scan Periodically

3. Moving to Static – Scan once

Movement-Aware Association

On median, 40% more throughput

• Android implementation• 30 traces• Static + Moving• Throughput

Heading-Aware Association

Minimize Handoff

Training based approachHeading

Heading-Aware Association

40% median reduction in handoffs

• Android implementation• Training (30 traces)• 30 traces• # Handoffs

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl



Speed

Walking

Vehicular Routing

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl

Gyro

Heading

Speed

Vehicular Routing

Routing in Vehicular Mesh Networks

“V2V”


• Longevity of links useful – avoids expensive repairs

• Link between nodes heading in the same direction tend to last longer

Connection Time Estimate (CTE)• Use heading, speed and

position to predict connection duration


Heading [0, 9) [10, 19) [20, 29) [30, 180] All Links

Link Duration (s) 66 32 15 9 16

• Empirical evaluation on taxi traces• 15 networks, 100 vehicles each

Links with similar heading lasted 4 to 5 times longer than the median duration over all links

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl



Speed

Walking

Vehicular Routing

Application

Transport

Network

MAC

PHY

Wireless Radio


GPS

Compass

Accl



Speed

Disassociation

Packet Scheduling

Power SavingPreamble

Network Monitoring

Speed

Walking

Location Vehicular Routing

Related Work

• Wireless power saving– WakeOnWireless, Cell2Notify, Blue-Fi

• Vehicular networking – use GPS– AP association

• Mobisteer, Breadcrumbs

– Rate adaptation• CARS: Adapt rate based on speed and heading

• Very recent work– Accelerometer-assisted rate adaptation

Take-Away Message

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

wireless protocols• Sensors on these devices give us a new

opportunity to develop network protocols• Protocol architecture using sensor hints can

significantly improve MAC, link, network layers

Backup

Probing

How frequently should nodes probe?

Delivery Probability• ETX, ETT

Probes

Infrequent Probing

Inaccurate link estimation leads to poor throughput

Frequent Probing

Probing wastes bandwidth

Delivery Probability

Mobility causes delivery probability tofluctuate with bigger jumps

Static vs. Mobile

Mobile case requires 20x more probesto maintain acceptable estimation error

Adaptive Probing Protocol

• Adapt probing based on movement hints• When a node is static

– Probe infrequently (1 probe every 2 seconds)• When a node is mobile

– Probe frequently (10 probes per second)

Adaptive Probing

Tracks the link accurately with fewer probes

Pruning association

Wireless “ESP”: Using Sensors to Develop Better Network Protocols Lenin Ravindranath Calvin Newport, Hari Balakrishnan, Sam Madden Massachusetts Institute.

Documents

mobile slide

future slide

wireless esp

current wireless protocols

static settings slide

mobility protocols

tremendous pace slide

stable protocols