jerry sussmanpage 1 of 61 class discussion “analyzing the mac-levelbehavior of wireless networks...

Jerry Sussman of 61

Class Discussion“Analyzing the MAC-levelBehavior of

Wireless Networks in the Wild”

Discussion Guided byJerry Sussman

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Critique Guidance

• Critique Instructions:– Critique the paper, not the me!– All students should read the paper before class– Critique is due prior to the following week’s class– Discussion Leader MUST use slides to guide the

discussion– Critiques should be organized / structured per

website– This is a 300-level course….there should be a lot of

discussion.

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Critique Guidance• (10%) State the problem the paper is trying to solve. • (20%) State the main contribution of the paper: solving a new problem,

proposing a new algorithm, or presenting a new evaluation (analysis). If a new problem, why was the problem important? Is the problem still important today? Will the problem be important tomorrow? If a new algorithm or new evaluation (analysis), what are the improvements over previous algorithms or evaluations? How do they come up with the new algorithm or evaluation?

• (15%) Summarize the (at most) 3 key main ideas (each in 1 sentence.) • (30%) Critique the main contribution

– Rate the significance of the paper on a scale of 5 (breakthrough), 4 (significant contribution), 3 (modest contribution), 2 (incremental contribution), 1 (no contribution or negative contribution). Explain your rating in a sentence or two.

– Rate how convincing the methodology is: how do the authors justify the solution approach or evaluation? Do the authors use arguments, analyses, experiments, simulations, or a combination of them? Do the claims and conclusions follow from the arguments, analyses or experiments? Are the assumptions realistic (at the time of the research)? Are the assumptions still valid today? Are the experiments well designed? Are there different experiments that would be more convincing? Are there other alternatives the authors should have considered? (And, of course, is the paper free of methodological errors.)

– What is the most important limitation of the approach? • (15%) What lessons should researchers and builders take away from this

work. What (if any) questions does this work leave open? • (10%) Propose your improvement on the same problem. • Note: the purpose of this template is to serve as a starting point, instead of a

constraint. Use your judgment and creativity. Some advice through the resource link of the class can be helpful.

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Agenda

• Authors• Summary• Background• Wit• Theory Behind Wit• Implementation of Wit• Wit Evaluation• Inference versus Additional Monitors• Application in Live Environment• Conclusion

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Authors

Ratual Mahajan MicrosoftMaya Rodrig University of

WashingtonDavid Wetherall University of

WashingtonJohn Zahorjan University of WashingtonFunding NSF

Presented SIGCOMM’06September 11-15, 2006Pisa, Italy

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Summary First

• Paper Documents WIT– Passive Wireless Analysis Tool– Analyzes MAC-Level behavior on Wireless

Networks

• Paper Assesses WIT Performance– Based on Real & Simulated Data

• Authors tested WIT against live Wireless Network

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Why Is WIT Needed?

• ???

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Why Is WIT Needed?

– Understand how live networks communicate in different situations:• Highly loaded environment• Low load environments• Interfering wireless LANs, etc.

– Critical to knowing how to improve performance of wireless LANs.

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Background

• Measurement-driven analysis of live networks– Critical to understanding live performance

of networks– Critical to improving performance

• Measurement-driven refers to:– Part Measured / Collected data– Part ‘generated’ data

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Background

• Wireless Measurement-Driven Analysis– At time of paper publication, Lacking in:

• Software Collection/Analysis Tools• Performance data from wireless networks• Reasons:

– Based on Simple Network Mgt Protocol (SNMP) logs from AP

– AP logs» Low fidelity (i.e. course logs) of AP Side» No data from client view

– Packet traces from Wired hosts next to AP» Traces omit wireless retransmissions

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Background

• Unrealistic Solution– Instrument entire wireless network

• Proven Successful in control environments• Unrealistic and not a match for commercial application

• Only Realistic Solution– Obtain trace via passive monitoring

• 1 or more nodes declared “monitors”• Monitors placed in vicinity of wireless network• Record attributes of all transmissions

– Trivial to deploy

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Background

• Problems with “Passive Monitoring”– Data / Traces may be incomplete

• Packets dropped due to weak signal• Packets dropped due to collisions

– Difficult to know what packets are missing from a monitor

– Monitor stations can’t determine if destination properly received packets• Important for determining reception

probability

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Background

• This paper is trying to:– Find a way to assemble an accurate trace of

wireless environment for analysis• Use data from multiple monitoring stations• Determine missing packets• Re-create missing packets• Combine into single Trace file

– Determine Network Performance• How often do clients retransmit their

packets• Determine loss effects between two nodes• Effect of increased load on the network

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Background• Authors attempt to solve problem with

WIT:– Paper presents WIT, a tool for

Measurement-Driven Analysis.– WIT has 3 modules which solve key

problems identified earlier

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Wit

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Why Is WIT Needed?

• Quantify Wireless Network Performance

• Estimate # of competing stations• Assist in diagnosing wireless

network problems

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WIT Core Processing Steps

1. Merging procedure 2. Packet Reconstruction3. Determination of Network Performance

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Merging procedure{1st Core Processing Step}

• Combine incomplete traces from multiple, independent monitors

• Provides a complete trace for follow-on steps

• Based upon collected date– Not inferred or reconstructed

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Packet Reconstruction{Second Core Processing Step}

• Reconstructs packets not captured by any monitor– Strong inference engine– Determines if packet received at

destination– Again, provides more complete

trace for follow-on step

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Determination of Network Performance {Third Core Processing Step}

• WIT Calculates Network Performance

– Input:Constructed trace

– Output:• Typical simple network measurements• Packet reception probabilities• Estimates number of nodes contending for

medium – Not previously achieved according to authors

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Passive Monitoring Pipeline

Client

Client

Client

`

Monitor

`

Monitor

`

Monitor

MERGE InferDerive

Measurements

Incomplete Views / Traces

Merge Incomplete views into

one consistent

view

Determine and replace missing packets to form complete trace

Derive Network Level

Measurements

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WIT Evaluation

• After Development of WIT, Authors faced with Evaluation Task– Used mix of real and simulated data– Used WIT at SIGCOMM 2004 conference

• Multi-monitor traces captured• Uncovered MAC-layer characteristics of environment

– Network was dominated by period of low contention during which the medium was poorly utilized, even though APs were waiting to tx packets

» Suggests 802.11 MAC tuned for high traffic levels that are uncommon on real networks.

– Authors claim this can’t be obtained by other methods

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Now for the Theory behind WIT phases

{Implementation of Phases will follow….}

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3 Core Phases

• Merging of Traces• Inferring Missing Information• Deriving Measurments /

Performance

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Merging of Traces

Client

Client

Client

`

Monitor

`

Monitor

`

Monitor

MERGE



one consistent

view

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Merging of Traces

• Input:– Number of Packet traces– 1 Trace per monitor– Timestamps reflect local AP Receive Packet

time

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Merging of Traces

• Output:– Merge into single, consistent timeline for

all packets observed• Eliminate duplicates• Assign coherent timestamps to all

packets independent of monitor• Timestamp accuracy to a few

microseconds required.• Identify and Eliminate Duplicates

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Merging of Traces

• Timing, the critical element– Only few packets carry info guaranteed to

be unique over a few miliseconds– Only way to distinguish duplicates is by

time– Accurate timestamps are vital to creating

the merged trace– Reference packets are the key

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Merging of Traces

• Three Step Merging Process1. Identify the reference packets common

to both monitors– Beacons generated by APs as references

» Contain unique source MAC address» Contain 64-bit value of local,

microsecond resolution timer

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Merging of Traces

• Three Step Merging Process2. Use reference timestamps to translate

the time coordinates– Pair up two reference timestamps across two

traces– Time interval of secondary is altered to match

baseline trace– Constant added to align the two traces

between the two individual reference points– Resizing / alignment process adjusts for clock

drift and alignment bias between two monitors

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Merging of Traces

• Three Step Merging Process3. Identify and Remove duplicates

• Identify by matching:– Packet Type– Same Source– Same Destination– Time stamp that is less than ½ of

minimum time to transmit a packet

Note: The code for this would be straight forward however I suspect much time was spent reviewing the data and proving that the code/scheme worked.

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Merging of Traces

• Waterfall Merging Process– Merge two traces– Then merge third trace to baseline

trace• Approach is not most time efficient• Approach provides improved

precision:– New reference points continually added– Easier to find set of shared reference points as

more monitor traces merged

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3 Core Phases

• Merging of Traces• Inferring Missing Information• Deriving Measurments /

Performance

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Inferring Missing Information

Infer


Client

Client

Client

`

Monitor

`

Monitor

`

Monitor

MERGE



one consistent

view

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• Two Fundamental Purposes:1. Infer missing packets from collected &

merged data2. Estimate whether packets were received

by their destination

• Authors claim this is new

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• Key Technique:– Transmitted packets imply useful data

about the packets it must have received– Example:

• AP send ASSOCIATION RESPONSE only if it recently receive an ASSOCIATION REQUEST.

• If the merge trace contains the response but no request then we know request was successfully sent

– Also, sender and destination of missing request are known from response packet.

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• Processing the merged trace– Scan each packet and process

• Classify each packet type• Generate markers

– Ex: Ongoing conversation end

• Formal Language Approach (FSM)– Infer Packet Reception– Infer Missing Packets– Construct Packets as Required

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3 Core Phases

• Merging of Traces• Inferring Missing Information• Deriving

Measurements/Performance

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Deriving Measurements / Performance

DeriveMeasurements

Derive Network Level

Measurements

Infer


Client

Client

Client

`

Monitor

`

Monitor

`

Monitor

MERGE



one consistent

view

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• Merged Trace Can Be Mined:• Many ways to study detailed behavior

– Packet Reception probability– Estimate number of stations that are

competing for medium per snapshot in time

– Requires access to ‘State’– ‘randomly selected backoff values

– DATA & DATAretry packets

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Now for the Implementation of WIT

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WIT Implementation

• WIT Implented in 3 Components– halfWit– nitWit– dimWit

• Half, Nit, & DIM correspond to three pipeline phases discussed earlier

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WIT Implementation

• halfWit– Merge phase

• 1st Insert all traces into database• Database used to merge data as defined

earlier• Database also used to pass final merged

trace to nitWit• Uses merge-sort methodology

– Traces handled like queues

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WIT Implementation

• nitWit– Inference phase

• nitWit take output of halfWit• Determines and recreates missing

packets• Annotates captured and inferred packets

– Critical annotation for each packet is whether it was received.

– Retry packet fields are tracked

Note: Original implementation did not ‘merge’ captured and inferred packets because exact timing uncertainty. Different than theory writeup section.

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WIT Implementation

• dimWit– Derived Measures Component

• dimWit take output of nitWit• Produces summary network information• Produces number of contenders in the

network• Implemented to analyze tens of millions

of packets in a few minutes.

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Wit Evaluation

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Wit Evaluation

• Purpose of Evaluation:– Understand how well each phase works– Key questions to be evaluated:

• Quality of time synchronization?• Quality of merged product?• Accuracy of inferences?• Fraction of missing packets inferred?• Number of Contenders – accuracy?• Analyze improvement from more monitors or

more inference?

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Wit Evaluation

• Reality of this type of evaluation:– Comparing against ground truth unrealistic

• Too much detail• Unrealistic to create absolute controlled

environment

– Reduced to simulation as primary validation method

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Wit Evaluation

• Simulated Environment:– 2 Access Points (AP’s)– 40 clients randomly distributed on a grid– Packet Simulator

• Reception probability based on: – signal strength– Transmission rate– Existing packets in environment– Random bit errors

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Wit Evaluation

• Simulated Environment (continued):– 10 randomly distributed monitors– Detailed logs of simulated packet

generation and simulated packet collection.

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Wit Evaluation

• Merging– Check correctness & characterize quality of

time synchronization• Basis for waterfall merging

• Inference– Check ability to infer packet reception

statuses and missing packets

• Estimating Contenders– Run dimWit on merged traces and compare

against logs

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Wit Evaluation

• Results– Will Limit results here to high priority end-result…

the Contenders.• Worst case simulation with 90% packets

captured, dimWit is within +-1 87% of cases• In smaller simulation with 98% packets

captured, estiates are within +- 1 for 95% of the cases.

• Closer study reveals:– High error values tend to correspond to

cases with high number of contenders

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Inference Versus Additional Monitors

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Inference Versus Additional Monitors

• Both more inference and more monitors increase quality of results

• Can’t Increase Both In Real Life• Which Has More Bang-for-the-

Buck?– Test show diminishing returns as number

of monitors increase – Expected Result

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Applying To Live Environment

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• SIGCOMM 2004 Conference wireless environment– 4 days– 550 attendees– Large / busy setting– 5 Access Points– Channels 1 and 11– Internet via DSL access lines– Interfering Wireless Networks

• Number of transient wireless networks• Hotel Wireless Network• Private Wireless Network on Ch 6

– Montoring 24/7 During Conference

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• Results:– Successful merge trace produced for each

channel– One monitor didn’t have enough references in

common with merged trace so it was excluded• Lesson Learned: Placement of monitors

– Significant overlap in what each monitor ‘hears’

– Additional monitors increases number of unique packets in each trace• True even when two monitors right next to

each other• Therefore, even dense array of monitors

will miss packets

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• Results:– nitWit inferred that 80% of unicast packets

were received by their destination– nitWit inferred that 90% of total packets

were captured by the monitors– dimWit determined that Uplink to the AP

was more reliable than the downlink – Medium was inefficiently utilized– Reception probability did not decrease with

contention– Performance was stable at high contention

levels

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Concluding Remarks

• Wit implementation provides wireless live data not previously available

• Measurement-driven analysis, implemented by Wit, successfully evaluated

• Further Study warranted– Will lead to increased efficiency of

Wireless LANs