All-IP 4G Mobile Networks and Beyond Kok-Kiong Yap Stanford University

WINLAB Seminar : July 2, 2010

Change is upon us • • • •

Mobile network is becoming all-IP



WiMAX and LTE are starting to be deployed

Mobile usage is increasingly data



Excitement and problems

But IP is poor in mobility and security! And we want low latency, high bandwidth and “perfect” coverage



And FREE? (shelved until 2nd part of talk)

The Promise of 4G • •

Low latency, high bandwidth & wide area coverage



Wait! Isn’t this the promise of 4G?

We study an incipient commercial WiMAX network to investigate

• •

No rate limits on traffic Result can be seen as informal upper bound on performance (because network is unloaded)

A 4G WiMAX Network •

Study of a commercial WiMAX network



Clear’s innovation network in Mountain View and Stanford



Production at the end of the year

Measurement Setup •

COTS equipments

• • •

Custom Python scripts

Driving Tests

• •

GPS, laptop and modem

Location, Time, CINR, RSSI

Static Tests



Location, TIme, CINR, RSSI, iPerf, RTT, Traceroute

Some numbers... • Driving test • 1.33 to 12.72 s each • average 21.8 readings



• Static test • 66.93 s (st.dev. 13.27 s)



• •

per min

per reading

Stanford 1837 driving readings 75 static readings

Mountain View



2961 driving readings

Signal Strength •

Average (± St.Dev.)

• • •

RSSI -72.5 (± 11.39) dBm

Deadspots are present but rare

• •

CINR 17.6 (± 9.0) dB

2.3% of locations surveyed

Usable (i.e., CINR > 10 dB) in 82.7 % of area surveyed

Goodput in Stanford •

TCP

• • •

0.81 Mbps up 2.49 Mbps down

UDP

• •

2.17 Mbps up 7.45 Mbps down

Latency in Stanford •

Jitter

• • •

19.14 ms up 4.98 ms down

RTT

• •

94.37 (± 77.90) ms Occasional spikes

Goodput & CINR/RSSI •

Correlation coeff : 0.876

CINR RSSI

TCP Uplink Downlink 0.037 0.938 0.045 0.902

UDP Uplink Downlink 0.823 0.933 0.729 0.896

UDP

Latency/Jitter & CINR • •

Fairly correlated RTT/Jitter

• •

Stable if CINR > 20 dB Corr. coeff. -0.564 to -0.791 with CINR for CINR < 20 dB

Tiers of Performance • • • • •

CINR < 0 dB : Unusable 0 dB < CINR < 10 dB : difficult/intermittent 10 dB < CINR < 20 dB : restrictive web surfing 20 dB < CINR < 30 dB : good access with min. jitter CINR > 30 dB : wireless is not the bottleneck

Variations of CINR • • •

Predicts variation of performance Temporal (Stable)

• •

avg. CINR of 21.7 dB has std. dev. 0.59 dB 0.18 dB per s change

Spatial

• •

0.18 dB per m with std. dev. 0.24 db per m Expect changes in seconds when moving

Footprint of Base-station •

Simple average path loss?

Mountain View

L = 10nlog10 (d) + C

Stanford

Footprint of Base-station •

Complex function of terrain, frequency, power, etc.

Summary of Survey • •

The good...

• •

Good bandwidth Wide area coverage

The not-so-good...

• •

Dead spots and variations High latency (at least compared to WiFi)

What should we do then? • •

Build another wireless network? What about stitching together networks today?

• •

Simple (and probably more obvious) method Typically we “see” many networks but off-limits

• •

multiple cellular networks numerous WiFi networks

WiFi cellular

First Step: Radio Agnosticism •

To cross the boundaries of networks, handover should be radio agnostic

• • •

Also allows future technologies Freedom to move and use the most appropriate network and technology

Simple idea of using FLOWS

• •

Cellular network already does so Brings concept of flows to Ethernet/WiFi



using OpenFlow

OpenFlow Wireless Aliceʼs Mobility Manager

Bobʼs Mobility Manager

NOX

NOX

FlowVisor OpenFlow Protocol

Your Experiment !!! NOX

A Demonstration •

Radio technology agnostic

• •

Shown how to handle between WiFi-WiMAX

Device/technology/application customizable

Stanford’s Deployment •



In School of Engineering

• •

100 WiFi APs



5 Ethernet switches

2 NEC WiMAX basestations

Used for group’s production traffic

as a Platform for Research • •

Why? OpenFlow Wireless as a platform for mobile research

• • • •

integrated management for Ethernet, WiFi and WiMAX simple API to control flows in the network

available publicly (both hardware and software) uses OpenFlow as its model of software defined networking

Hopes for Tomorrow

Service provider 1

Infra A

Service provider II

Infra B

Infra C

Credits • •

Clearwire Measurement



Clearwire, namely Jonathan Kaiser, Benson Zhu, Allen Flanagan, Ron Marquardt and John Saw



Nick McKeown, Guru Parulkar, Sachin Katti

OpenFlow Wireless



Masayoshi Kobayashi, Te-Yuan Huang, Rob Sherwood, Michael Chan, Nikhil Handigol, Nick McKeown, Guru Parulkar, Sachin Katti

Related papers can be found on http://stanford.edu/~yapkke or http://kkmobile.homelinux.com

Questions and Comments?

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