Wireless Data Networking Research: From Concept to Practice Songwu Lu UCLA.

Wireless Data Networking Research: From Concept to

Practice

Songwu Lu

UCLA

Drivers for Wireless Networking Research

Transport Layer

Network Layer

Link Layer

New Services, Architectures, Requirements

New Wireless Communications Technology

Top

Down Bottom

Up

Key Driver: Wireless Communications

• Many examples of them:– Sector Antenna, antenna arrays, Smart antennas – Adaptive modulation, MIMO, OFDM, UWB, .. – Cognitive radio, software radio, spectrum sharing, channel

management– Multiple radios, device heterogeneity– …

• many orthogonal dimensions– RF spectrum, antenna, data processing, …

• main goal: improve performance in terms of spectral efficiency

• Challenge: How to exploit these new PHY communication capabilities in the protocols?

Root Cause of Problems

two largely disconnected communities• speak different terminologies

– wireless communications:• Symbols, signals• probabilistic terms:

– information theoretic bounds– confidence factor on symbol reception, …

– wireless networking• Packets, bits• deterministic terms

– Correct/wrong binary reception

Root Cause of Problems (2)

Two largely disconnected communities• different methodologies

– wireless communications• solid theoretic foundation on information theory• a set of well known assumptions: noises, interferences, etc.• Theory Design-->Analysis-->prototype in chips-->experiments

– wireless networking• mostly on heuristics • network setting “ad hoc”: no agreed benchmarks/base settings• Heuristic Design-->Simulations--Network Prototype--

>Experiments

Perspective From Wireless Networking

• We are not on the driver’s seat so far– communication has driven the technology so far– we are followers

• No need to be sad– still plenty of space

• the direct communication almost NEVER works in reality at the 1st place!

– other brothers also facing similar situations sometime• Internet: PC/hardware industry• Cellular: mobile phones

Research Life Cycle in Traditional Wireless Networking Researcher

1. wait for new radio communication tech. to come to life

2. be the 1st to design networking solution to it3. not so lucky?

• understand the problem better• check other aspects/components in the system

4. apply the set of tricks in your bag5. claim credit/declare failure

• Experiments!!!!• Positive success: insights learned• Negative failure: lessons learned

Two Design Guidelines

2 most popular design principles used in the research community

1. Adaptation

high-dimension dynamics

2. Coordination

coherent system

Bag of Tricks in Adaptation• Model-referenced design

– Ideal model to capture expected behaviors under idealized situation

• e.g., error-free, static settings– Track the reference model under realistic conditions/scenarios

• Mobility, wireless channel dynamics, …

• Opportunistic design approach– Make each perform under peak conditions– Exploit the system population– Leverage system diversity

• Multiple receivers, multiple devices, multiple applications/flows, …

Bag of Tricks in Coordination

• Cross-Layer design– not integrated design cross layers– information sharing, informed decision at other

layers– …

• Coordination via “indirection”– Adaptation-aware proxy provides indirection: act

as converter/translator

Illustration Case: Rate Adaptation in Wi-Fi

Problem: Adapt transmission rate to channel quality

Sender Receiver

54MbpsSignal is goodSignal becomes weaker

12Mbps

•The 802.11 a/b/g/n standards allow for multiple rates based on adaptive modulation

–802.11b: 4 rate options (1,2,5.5,11Mbps)–802.11a: 8 options (6,9,12,18,24,36,48,54)–802.11g: 12 options (11a set + 11b set)

•unspecified by the IEEE 802.11 standard

As the Lucky, 1st Guy

• Driver: adaptive modulation• Good news: SNR based feedback not there!• Opportunity: packet-level information available• Solution:

– Hypothesis: packet loss indicates channel quality change

– Tricks: • Decrease transmission rate upon severe packet

loss• 10 consecutive successes → increase rate

Rules For Not So Lucky?

Understand the problem better– if a problem is not better understood, it is

probably best not to provide a new solution at all

– no rush for quick solutions• incremental improvement is #1 enemy in

research!

– do not improve on flawed design!!• adding gas into fire

Experiments to Discover (No) Problems

ARF AARF SampleRate Fixed Rate

UDP Goodput (Mbps)

0.65 0.56 0.58 1.46

SenderReceiverHiddenStation

Case: packet collision scenario?

The sender performs worse with Rate Adaptation!

• The sender should not decrease the rate upon collision losses– Decreasing rate increases collisions !

Find Root Cause

Severeloss

DecreaseTxrate

IncreaseTxtime

IncreasecollisionProb.

Fail to handle hidden-station!

Solution?

• Straightforward idea: RTS/CTS

• more thinking: make RTS/CTS adaptive– reduce overhead– infer collision levels

• Performance: ~80% throughput gain

Software

Hardware

PHYfeedba

ck

802.11 MAC

AdaptiveRTS

Loss EstimationRate Selection send

RTSOption

RRAA

Now MIMO Case?

• Driver: 802.11-pre-n MIMO

• Good/Bad News: SNR feedback to some extent– more direct & timely information on channel

quality?– Loss-based design obsolete?

SNR vs Rate vs Throughput

•SNR vs rate vs thruput are non-monotonic in fine grain•main trend can still be correct

•RF Chamber experiments

Solution in MiRA

• using SNR pre-selects a range of rates– determine a rate window [minRate, maxRate].

• Loss-based best rate choice within the window – play old tricks using loss-based design

Experiments on Static Clients: UDP

Gains in blue arrows refer to MiRA vs. Atheros RA

Static Clients Scenario: TCPGains in blue arrows refer to MiRA vs. Atheros RA

Broader View on Well-Known Areas

• look at other systems component the design works with

• illustrative example: Network Coding– hot topics– several papers on top conferences, from groups

@ MIT, Microsoft Research, …

– what can I do?

Network Coding in Reality: Wi-Fi Nets Multicast/broadcast (a XOR

b) @ 6Mbps Base rate without RA Used in COPE, Wi-Fi

broadcast

NC is worse ! Xmit time w/o NC

2L/54 + 2L/24 Xmit time with NC

L/54 +L/24+L/6

Conclusion: NC works but loses without any RA!

AliceBob

a b

a XOR b

54Mbps 24Mbps

Native NC (@ base rate) May NOT gain at all !

NC Gain May Vanish

Simple multicast RA solution: multicast = min

(rate_receiver) NC gain reduces

NC: 25% (4 tx ->3 tx) In the literature

Actual gain (11a): 5% NC tx time: 2*L/6+L/54 No NC: 2*L/54+2*L/6

802.11b: 1/24 (11M&1M) Root cause: NC cannot

exploit rate diversity!

AliceBob

a b

a XOR b

54Mbps 6Mbps

NC gain (@ optimal rate) may reduce in rate diversity case!

My View on New Frontiers

• no need to get squeezed in crowded traditional areas

• bag of tricks grow much slower!

• problem space is wild wide west!

Wireless Networking on a Chip

• 1000s of cores Systems on a Chip

• wired interconnect: latency, physical wiring constraints• High-speed wireless shortcuts

Composable Wireless Networking

• composable & modular from radio to networking

• Radios become dynamically loadable modules– no clear separation of multi-radios – Software Defined Radios platforms

“Green” Wireless Infrastructure

• infrastructure is power hungry – asymmetric design in cellular network

• more complexity @ base stations– from radio communication, to signaling, to higher

layers

• lots of energy-saving proposals @client side– no on the infrastructure

Resilience-Oriented Design

• mostly performance driven for wireless networking so far

• resilience as the 1st principle– not as patches– learn the success from the Internet

• still early to have a nice try

Still Unhappy? Looking Up• New requirements

– Security, privacy, robustness/dependability, distributed management

• New applications and services– MMS, P2P image/video sharing, IP TV streaming, …– (Location-based, context-aware, personalized,

pervasive) services

My View on Pervasive Cloud Computing

• Data stored in the “Cloud”• Data follows you & your devices• Data accessible anywhere• Data can be shared with others

music

preferences

maps

newscontacts

messages

mailing lists

photo

e-mails

calendar

phone numbers

investments

“Anytime, Anywhere, Any device” Data Service

Research Sub-areas

1. Data Center Networking: Improving the Cloud Infrastructure

2. New Services For Mobile Devices– Security: Virus detection– Location-based Service,– social networking,…

3. Better Access for the Client1. Improving Wi-Fi, 3G+, … for user access2. Opportunistic Client-Client Service

Final Words

• Life can be good or bad in wireless networking research– It is more about your choice

• You are part of inventing the artifact for wireless networking

Acknowledgments

• most real work is done by the real heroes in projects:– Students:

• Innaois Yannis, Suk-Bok Lee, Starsky Wong, Hao Yang, Haiyun Luo,…

– Colleagues: • Lixia Zhang, Mario Gerla, Chuanxiong Guo,

Jacky Shen, Yongguang Zhang, Shugong Xu, …