May 2013 Dmitry Kuptsov, HIIT Slide 1 doc.: IEEE 802.11-13/0494r0 Submission A Measurement Study of WiFi Backoff Protocols Date: 2013-05-14 N am e A ffiliations A ddress Phone em ail D m itry Kuptsov HIIT,A alto U niversity H elsinki Institute forInform ation Technology H IIT,P O Box 15600, 00076 Aalto,Finland +358 50301 2613 dm itriy.kuptsov@ hiit.fi BorisN echaev HIIT,A alto U niversity H elsinki Institute forInform ation Technology H IIT,P O Box 15600, 00076 Aalto,Finland +358 50384 1513 [email protected] A ndrey Lukyanenko CSE, A alto U niversity H elsinki Institute forInform ation Technology H IIT,P O Box 15600, 00076 Aalto,Finland +358 50384 1663 [email protected] A ndreiGurtov H IIT and C W C, U niversity ofO ulu H elsinki Institute forInform ation Technology H IIT,P O Box 15600, 00076 Aalto,Finland +358 40596 3729 G urtov@ hiit.fi Authors:
Doc.: IEEE 802.11-13/0494r0 Submission May 2013 Dmitry Kuptsov, HIIT Slide 1 A Measurement Study of WiFi Backoff Protocols Date: 2013-05-14 Authors:
Dec 16, 2015
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
May 2013
Dmitry Kuptsov, HIITSlide 1
doc.: IEEE 802.11-13/0494r0
Submission
A Measurement Study of WiFi Backoff ProtocolsDate: 2013-05-14
Name Affiliations Address Phone emailDmitry Kuptsov HIIT, Aalto University Helsinki Institute for Information
Technology HIIT, PO Box 15600, 00076 Aalto, Finland
+358 50301 2613 [email protected]
Boris Nechaev HIIT, Aalto University Helsinki Institute for Information Technology HIIT, PO Box 15600, 00076 Aalto, Finland
+358 50384 1513 [email protected]
Andrey Lukyanenko CSE, Aalto University Helsinki Institute for Information Technology HIIT, PO Box 15600, 00076 Aalto, Finland
+358 50384 1663 [email protected]
Andrei Gurtov HIIT and CWC, University of Oulu
Helsinki Institute for Information Technology HIIT, PO Box 15600, 00076 Aalto, Finland
+358 40596 3729 [email protected]
Authors:
May 2013
Dmitry Kuptsov, HIITSlide 2
doc.: IEEE 802.11-13/0494r0
Submission
Abstract
Despite much theoretical work, different modifications of backoff protocols in 802.11 networks lack empirical evidence demonstrating their real-life performance. To fill the gap we have set out to experiment with performance of exponential backoff by varying its backoff factor. Despite the satisfactory results for throughput, we have witnessed poor fairness manifesting in severe capture effect. The design of standard backoff protocol allows already successful nodes to remain successful, giving little chance to those nodes that failed to capture the channel in the beginning. With this at hand, we ask a conceptual question: Can one improve the performance of wireless backoff by introducing a mechanism of self-penalty, when overly successful nodes are penalized with big contention windows? Our real-life measurements using commodity hardware demonstrate that in many settings such mechanism not only allows to achieve better throughput, but also assures nearly perfect fairness.
May 2013
Dmitry Kuptsov, HIITSlide 3
doc.: IEEE 802.11-13/0494r0
Submission
Problem
Resources in IEEE 802.11 networks are allocated randomly with BEB
The allocation scheme is largely unfair The disparity is more prominent when stations are exposed in uneven
environment (e.g., stations have different spatial positions)
Can we improve resource allocation by Changing operation of IEEE 802.11 backoff protocol
Experimental evidence is missing
May 2013
Dmitry Kuptsov, HIITSlide 4
doc.: IEEE 802.11-13/0494r0
Submission
Standard backoff with modified backoff factors
Increase contention window exponentially after each failure CW=CW
0 r i-1
CW0=16
r=2
Up to i=7 retries before a frame is discarded
Vary r for different number of stations, N
May 2013
Dmitry Kuptsov, HIITSlide 5
doc.: IEEE 802.11-13/0494r0
Submission
Penalty backoff Change the CW depending on
whether the station is successful after first transmission attempt or not
If the station failed, continue with standard backoff protocol
If the station succeeded, assign largest contention window (CW=CW0 r6) for transmission
of the next frame
Vary backoff factor, r, depending on N
Rational: By penalizing too successful stations, we increase the chances of unsuccessful stations to transmit the frames
May 2013
Dmitry Kuptsov, HIITSlide 6
doc.: IEEE 802.11-13/0494r0
Submission
Rollback backoff
Reverse the standard backoff protocol: Exponentially decrease CW
on every failed attempt
Vary backoff factor, r, depending on N
Rational: Increase the odds of unsuccessful stations to access the channel by decreasing their waiting time
May 2013
Dmitry Kuptsov, HIITSlide 7
doc.: IEEE 802.11-13/0494r0
Submission
Backoff with fixed CW
Assign all stations with a fixed CW CW is not changed after failed or successful frame transmission
Vary CW depending on number of stations, N, only
Rational: If CWs are computed properly, channel access can be optimized leading to a better performance
May 2013
Dmitry Kuptsov, HIITSlide 8
doc.: IEEE 802.11-13/0494r0
Submission
Implementation
Open wireless firmware (OpenFWWF project)
Broadcom B43 wireless cards
Implemented 4 aforementioned backoff protocols in firmware
Changes to Linux kernel drivers
More on changes made: http://arxiv.org/pdf/1208.6318v2.pdf Source codes and installation instructions:
http://www.hiit.fi/u/kuptsov/penalty-backoff/
May 2013
Dmitry Kuptsov, HIITSlide 9
doc.: IEEE 802.11-13/0494r0
Submission
Experimental environment
Two testbeds used: Wireless nodes are close (~1m) to the access point (idealized environment)
Wireless nodes are scattered (~17m from the access point) around the office (normal environment)
A master node and 3 slave nodes (multiple wireless cards per slave node) Wired connection for sending control traffic (e.g., calibration packets – discussed later)
Wireless connection for experimental traffic
In total 12 wireless stations were used
May 2013
Dmitry Kuptsov, HIITSlide 10
doc.: IEEE 802.11-13/0494r0
Submission
Experimental Setup
May 2013
Dmitry Kuptsov, HIITSlide 11
doc.: IEEE 802.11-13/0494r0
Submission
Data collection and calibration
3 main traffic patterns used: bulky download and upload (from master node to slave nodes, and vice versa), delay sensitive UDP streams
Tools used to generate traffic: Wget (for upload from slave to master) and scp (for download from master to
slave) to generate bulky streams
Custom “C” application for generating periodic UDP packets
May 2013
Dmitry Kuptsov, HIITSlide 12
doc.: IEEE 802.11-13/0494r0
Submission
Data collection and callibration (cont'd)
Logging on slave nodes: For every wireless card using printk and debugging statements introduced in
wireless card driver we logged (on per frame bases): Transmission time
Number of retries
Acknowledgment flag (success or failure)
Frame size
Last used contention window and backoff interval
NOTE! printk uses ring buffer If not freed on time the logs get erased
Solution: Increased ring buffer size and dumped buffer every 0.1 second
May 2013
Dmitry Kuptsov, HIITSlide 13
doc.: IEEE 802.11-13/0494r0
Submission
Problem: How to merge logs from different slaves (note, clocks are not in sync for different slave machines) ? Merged logs are essential to study such performance metrics as:
Total throughput
Total collision rate
Fairness
Solution: Send calibrating beacons with unique id (over wired link) from master node to all slave machines every 10ms and then realign the logs according to beacons
Data collection and calibration (cont'd)
May 2013
Dmitry Kuptsov, HIITSlide 14
doc.: IEEE 802.11-13/0494r0
Submission
Data collection and calibration (cont'd)
To validate the precision of beaconing, we have computed the distribution of their interarrival times and differences between interarrival times for all slave machines Interarrival times turned to be sharply clustered around 10ms with rare outliers
The distribution of differences in interarrival times was clustered sharply around 0
May 2013
Dmitry Kuptsov, HIITSlide 15
doc.: IEEE 802.11-13/0494r0
Submission
Using the beacons we split the merged log into bins of 100ms
In each bin we calculated (per wireless station and total):
Number of packets successfully transmitted
Number of failed transmissions
Total number of bytes transmitted
For analysis we used only bins in which all stations where transmitting the packets:
We discarded all bins from the beginning of log file up to a bin in which all stations sent at least one packet
We discarded all bins from the end of the log file starting from bin in which one of the stations sent its last packet
We ensured that the trimmed log file was big enough providing statistically valid data
Data collection and calibration (cont'd)
May 2013
Dmitry Kuptsov, HIITSlide 16
doc.: IEEE 802.11-13/0494r0
Submission
Experimental results: Idealized environment, bulky upload
For all protocols we report:
Median throughput for different values of r (except for a backoff with fixed CW for which we report entire CDF)
Jain's fairness index
Median collision probability
Observations:
Penalty and rollback backoff protocols deliver 145% and 77% better throughput in comparison to standard backoff protocol for optimal values of r
Penalty and rollback backoff protocols significantly decrease the collision probability and show considerable improvement in fairness
Backoff protocol with fixed CW does not have highest throughput and fairness
May 2013
Dmitry Kuptsov, HIITSlide 17
doc.: IEEE 802.11-13/0494r0
Submission
Experimental results: Idealized environment, bulky upload
Penalty Fixed CW
Thr
ough
put
Fai
rnes
s
Standard
May 2013
Dmitry Kuptsov, HIITSlide 18
doc.: IEEE 802.11-13/0494r0
Submission
Experimental results: Normal environment
Nodes are scattered around the office ~15-16 meters away from the access point
Observation: The trends observed in idealized environment repeat for all protocols
Conclusion: Penalty and rollback backoffs deliver better performance in environment common to many real life deployments
May 2013
Dmitry Kuptsov, HIITSlide 19
doc.: IEEE 802.11-13/0494r0
Submission
Experiment with hidden stations Involved two wireless stations and
an access point operating in normal environment:
Wireless stations are hidden from each other One station has slightly
stronger signal
Penalty and rollback increase the odds of accessing the channel for disadvantageous stations as r gets large enough (discussion can be found in Section VII in the paper)
May 2013
Dmitry Kuptsov, HIITSlide 20
doc.: IEEE 802.11-13/0494r0
Submission
Experiment with download trafficWireless stations performing
download from master node in normal environment
Comparable throughput for penalty, rollback and standard backoff protocols achieved
Penalty and rollback backoff show better fairness
May 2013
Dmitry Kuptsov, HIITSlide 21
doc.: IEEE 802.11-13/0494r0
Submission
Experiment with delay sensitive traffic
9 wireless stations perform bulky upload in in normal environment
1 station sends UDP packets every 10ms
Observation: Penalty and rollback backoff protocols do not increase significantly delays in comparison to standard protocol
May 2013
Dmitry Kuptsov, HIITSlide 22
doc.: IEEE 802.11-13/0494r0
Submission
Mathematical model: Optimal values of r as function of NGoal: Find optimal values of
backoff factor r as a function of number of active stations N
Solidify and corroborate empirical results
Are useful for dynamic backoff factor adaptationIn realistic networks
number of stations N can change frequently
Mathematical derivations and techniques used can be found in the paper
Theoretical vs. Empirical: optimalbackoff factor values for different number
wireless stations
May 2013
Dmitry Kuptsov, HIITSlide 23
doc.: IEEE 802.11-13/0494r0
Submission
Backoff factor adaptation algorithm:Metrics
1.We use two metrics to estimate the number of active stations:
i. Threshold-based (simple)
ii.Ratio-based (accurate)
2.Threshold-based metric: Count each station as active if it transmits longer than some threshold
3.Ratio-based metric: Count each station that fully saturate the channel, and aggregate the stations that do not fully saturate the channel
Please see paper for more details about the metric and its properties
May 2013
Dmitry Kuptsov, HIITSlide 24
doc.: IEEE 802.11-13/0494r0
Submission
Two previous metric work well when there is AP AP coordinates the selection of backoff factors
How to estimate number of active stations when no AP available, e.g., in mesh networks?
Or when multiple APs, working at the same channel, present in the environment?
Count idle slots as per IDLE SENSE Will not work when hidden stations present
Can we use consensus algorithms between stations to figure it out?
Future research direction!
Backoff factor adaptation algorithm:Metrics (cont'd)
May 2013
Dmitry Kuptsov, HIITSlide 25
doc.: IEEE 802.11-13/0494r0
Submission
Backoff factor adaptation algorithm: Evaluation Implementation:
Metrics are implemented in hostapd access point
Introduced new 802.11 management frame to convey optimal backoff factor to stations
Modified B43 driver to adapt the backoff factors of wireless card
Experiment:
12 wireless stations:
6 stations follow On/Off pattern and generate 40KB UDP stream every 30 seconds during 30 seconds interval
6 stations constantly upload large file using TCP protocol
May 2013
Dmitry Kuptsov, HIITSlide 26
doc.: IEEE 802.11-13/0494r0
Submission
Deployment How to deploy our protocol? At least two incremental deployment possibilities exist! Approach 1: Implement fall-back mechanism:
Similarly how a and b variants of 802.11 coexist today! If at least one station that does not support modified backoff
protocol attaches to network all attached nodes start to use standard backoff protocol
Simple and doable! Approach 2: The protocol can be readily used in mesh
networks: Use modified backoff for backbone links Use standard backoff for interacting with legacy clients Of course, backbone links and clients have to use different
channels!
May 2013
Dmitry Kuptsov, HIITSlide 27
doc.: IEEE 802.11-13/0494r0
Submission
Conclusions
Penalty and rollback protocols improve throughput and fairness
– Choose penalty over rollback backoff for slightly better performances in terms of throughput
– Choose rollback over penalty backoff for slightly better fairness
If hidden terminals exist, penalty and rollback protocols increase the chances of a disadvantageous wireless station to access the channel
Penalty and rollback backoff protocols do not increase the delays comparing to standard backoff protocols
In practice the optimal backoff factors for penalty and rollback protocols can be efficiently computed and distributed by an access point
May 2013
Dmitry Kuptsov, HIITSlide 28
doc.: IEEE 802.11-13/0494r0
Submission
References
• D. Kuptsov, B. Nechaev, A. Lukyanenko, A. Gurtov, A Novel Demand-Aware Fairness Metric for IEEE 802.11 Wireless Networks, Proc. of ACM SAC, March 2013.
• A. Lukyanenko, A. Gurtov, Performance analysis of general backoff protocols, Journal of Communications Software and Systems, 4(1), March 2008.
• A. Lukyanenko, E. Morozov, A. Gurtov, An adaptive backoff protocol with Markovian contention window control, in Communications in Statistics - Simulation and Computation, Volume 41, issue 7, 2012.
• D Kuptsov, B Nechaev, A Lukyanenko, A Gurtov, How Penalty Leads to Improvement: a Measurement Study of Wireless Backoff, arXiv preprint arXiv:1208.6318
Related Documents
