Analyzing the MAC-level behavior of wireless networks in the wild Ratul Mahajan (Microsoft Research) Maya Rodrig, David Wetherall, John Zahorjan (University.

Slides:

Advertisements

Similar presentations

Sherlock – Diagnosing Problems in the Enterprise Srikanth Kandula Victor Bahl, Ranveer Chandra, Albert Greenberg, David Maltz, Ming Zhang.

Advertisements

A simple coordination mechanism for interdomain routing Ratul Mahajan * David Wetherall Tom Anderson University of Washington ( * Microsoft Research)

Nick Feamster CS 4251 Computer Networking II Spring 2008

1 The Case for Heterogeneous Wireless MACs Chun-cheng Chen Haiyun Luo Dept. of Computer Science, UIUC.

Service Credit Online Certification and Correction Training By Paula C. Rhodes Created by: Martha Rosa Updated: 04/20/2007.

5/12/061 Modeling, Simulation, and Analysis of Variable Frequency Transformers Brian C. Raczkowski Peter W. Sauer.

Presentation to Orleans Levee District Lake Pontchartrain And Vicinity Levees LPV September 2006 Presentation to Orleans Levee District Lake.

CCTI HSTW Making High School/ Community College Transitions: Combine HSTW and CCTI Southern Regional Education Board Gene Bottoms Senior Vice President.

Conversational Technologies Using Speech Recognition for Speech Therapy A multimodal application for users with aphasia Deborah A. Dahl SpeechTEK August.

05/03/061 Web Development with HL7 Veterinary Telemonitoring Roland T. Craddolph.

The Mystery Machine: End-to-end performance analysis of large-scale Internet services Michael Chow David Meisner, Jason Flinn, Daniel Peek, Thomas F. Wenisch.

REfactor-ing Content Overhearing to Improve Wireless Performance Shan-Hsiang Shen Aaron Gember Ashok Anand Aditya Akella abc 1d ab 1.

Medium Access Issues David Holmer

E-MiLi: Energy-Minimizing Idle Listening in Wireless Networks Xinyu Zhang, Kang G. Shin University of Michigan – Ann Arbor.

CMP206 – Introduction to Data Communication & Networks Lecture 1 - Networking Fundamentals.

CMAP: Harnessing Exposed Terminals in Wireless Networks Mythili Vutukuru Joint work with Kyle Jamieson and Hari Balakrishnan.

Aruna Balasubramanian, Ratul Mahajan Arun Venkataramani, Brian N Levine, John Zahorjan Interactive WiFi Connectivity from Moving Vehicles University of.

Modeling and Throughput Analysis for SMAC Ou Yang

1 An Approach to Real-Time Support in Ad Hoc Wireless Networks Mark Gleeson Distributed Systems Group Dept.

A Scalable MAC Protocol for Next-Generation Wireless LANs Zakhia (Zak) Abichar, J. Morris Chang, and Daji Qiao Dept. of Electrical and Computer Engineering.

Sustaining Cooperation in Multi-Hop Wireless Networks Ratul Mahajan, Maya Rodrig, David Wetherall, John Zahorjan University of Washington.

Ratul Mahajan Microsoft Research John Zahorjan University of Washington Brian Zill Microsoft Research Understanding WiFi-based connectivity from moving.

Analysis of an IEEE Network Activity during a Small Workshop Zhe Zhou, Mark Claypool, and Robert Kinicki Computer Science, Worcester Polytechnic.

Dynamic Tuning of the IEEE Protocol to Achieve a Theoretical Throughput Limit Frederico Calì, Marco Conti, and Enrico Gregori IEEE/ACM TRANSACTIONS.

Distributed systems Module 1 -Basic networking Teaching unit 1 – LAN standards Ernesto Damiani University of Bozen-Bolzano Lesson 2 – LAN Medium Access.

CS541 Advanced Networking 1 Basics of Wireless Networking Neil Tang 1/21/2009.

KING FAHD UNIVIRSITY OF PETROLEUM AND MIERALS ELECTRICAL ENGINEERING DEPARTMENT MAC Protocols in ad hoc networks Rami Bakhsh Mohammed Al-Farsi.

Does the IEEE MAC Protocol Work Well in Multihop Wireless Ad Hoc Networks? Shugong Xu Tark Saadawi June, 2001 IEEE Communications Magazine (Adapted.

1 Sustaining Cooperation in Multi-Hop Wireless Networks Ratul Mahajan, Maya Rodrig, David Wetherall and John Zahorjan University of Washington Presented.

1 Analyzing the MAC-level Behavior of Wireless Networks in the wild By: Ratul Mahajan, Maya Rodrig, David Wetherall, Zahorjan Presented by: Andy Cheng,

IEEE Wireless LAN: Capacity Analysis and Protocol Enhancement F. Cali, M. Conti, E. Gregori IEEE Wireless LAN: Capacity Analysis and Protocol.

11 Automating Cross-Layer Diagnosis of Enterprise Wireless Networks Yu-Chung Cheng Mikhail Afanasyev Patrick Verkaik Jennifer Chiang Alex C. Snoeren.

1. 2 Enterprise WLAN setting 2 Vivek Shrivastava Wireless controller Access Point Clients Internet NSDI 2011.

5-1 Data Link Layer r Wireless Networks m Wi-Fi (Wireless LAN) Example Problems m RTS/CTS.

MIMO and TCP: A CASE for CROSS LAYER DESIGN Soon Y. Oh, Mario Gerla Computer Science Dept. University of California, Los Angeles {soonoh,

1 How to apply Adaptation principle: case study in

MAC Reliable Broadcast in Ad Hoc Networks Ken Tang, Mario Gerla University of California, Los Angeles (ktang,

Jigsaw: Solving the Puzzle of Enterprise Analysis Yu-Chung Cheng John Bellardo, Peter Benko, Alex C. Snoeren, Geoff Voelker, Stefan Savage.

Computer Networks, Fifth Edition by Andrew Tanenbaum and David Wetherall, © Pearson Education-Prentice Hall, 2011 The Medium Access Control Sublayer Chapter.

Statistical Natural Language Processing. What is NLP?  Natural Language Processing (NLP), or Computational Linguistics, is concerned with theoretical.

Harnessing Mobile Multiple Access Efficiency with Location Input Wan Du * and Mo Li School of Computer Engineering Nanyang Technological University, Singapore.

Wireless Medium Access. Multi-transmitter Interference Problem  Similar to multi-path or noise  Two transmitting stations will constructively/destructively.

Qian Zhang Department of Computer Science HKUST Advanced Topics in Next- Generation Wireless Networks Transport Protocols in Ad hoc Networks.

Jerry SussmanPage 1 of 61 Class Discussion “Analyzing the MAC-levelBehavior of Wireless Networks in the Wild” Discussion Guided by Jerry Sussman.

A Cooperative Diversity- Based Robust MAC Protocol in wireless Ad Hoc Networks Sangman Moh, Chansu Yu Chosun University, Cleveland State University Korea,

Ethernet. Problem In an Ethernet, suppose there are three stations very close to each other, A, B and C. Suppose at time 0, all of them have a frame to.

AutoMAC : Rateless Wireless Concurrent Medium Access Aditya Gudipati, Stephanie Pereira, Sachin Katti Stanford University.

Measurement-based models enable predictable wireless behavior Ratul Mahajan Microsoft Research Collaborators: Yi Li, Lili Qiu, Charles Reis, Maya Rodrig,

Computer Networks, Fifth Edition by Andrew Tanenbaum and David Wetherall, © Pearson Education-Prentice Hall, 2011 The Medium Access Control Sublayer Chapter.

Written by Yu-Chung Cheng, John Bellardo, Peter Benko, Alex C. Snoeren, Geoffrey M. Voelker and Stefan Savage Written by Yu-Chung Cheng, John Bellardo,

MOJO: A Distributed Physical Layer Anomaly Detection System for WLANs Richard D. Gopaul CSCI 388.

November 4, 2003APOC 2003 Wuhan, China 1/14 Demand Based Bandwidth Assignment MAC Protocol for Wireless LANs Presented by Ruibiao Qiu Department of Computer.

Encouraging Cooperation in Multi-Hop Wireless Networks Ratul Mahajan, Maya Rodrig, David Wetherall and John Zahorjan University of Washington, June 2004.

Conformance Test Experiments for Distributed Real-Time Systems Rachel Cardell-Oliver Complex Systems Group Department of Computer Science & Software Engineering.

ECE 256: Wireless Networking and Mobile Computing

24 st Oct Correlated Coding: Efficient Network Coding under Unreliable Wireless Links Shuai Wang, Song Min Kim, Zhimeng Yin, and Tian He University.

X. Li, W. LiuICC May 11, 2003A Joint Layer Design Smart Contention Resolution Random Access Wireless Networks With Unknown Multiple Users: A Joint.

Performance Analysis of IEEE Distributed Coordination Function (DCF) Author : Giuseppe Bianchi Presented by: 李政修 December 23, 2003.

Medium Access Control protocols for ad hoc wireless networks: A survey 指導教授 : 許子衡報告者 : 黃群凱.

Wi-Fi. Basic structure: – Stations plus an access point – Stations talk to the access point, then to outside – Access point talks to stations – Stations.

Search Engine using Web Mining COMS E Web Enhanced Information Mgmt Prof. Gail Kaiser Presented By: Rupal Shah (UNI: rrs2146)

KAIS T Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Network Wei Ye, John Heidemann, Deborah Estrin 2003 IEEE/ACM TRANSACTIONS.

Optimization Problems in Wireless Coding Networks Alex Sprintson Computer Engineering Group Department of Electrical and Computer Engineering.

2012 1/6 NSDI’08 Harnessing Exposed Terminals in Wireless Networks Mythili Vutukuru, Kyle Jamieson, and Hari Balakrishnan MIT Computer Science and Artificial.

FD-MMAC: Combating Multi-channel Hidden and Exposed Terminals Using a Single Transceiver Yan Zhang, Loukas Lazos, Kai Chen, Bocan Hu, and Swetha Shivaramaiah.

Copyright © 2003 OPNET Technologies, Inc. Confidential, not for distribution to third parties. Wireless LANs Session

Wireless LAN Requirements (1) Same as any LAN – High capacity, short distances, full connectivity, broadcast capability Throughput: – efficient use wireless.

Isolating Physical PER for Smart Rate Selection in Malik Ahmad Yar Khan and Darryl Veitch ARC Special Centre for Ultra-Broadband Information Networks.

Subject Name: Adhoc Networks Subject Code: 10CS841

E-MiLi: Energy-Minimizing Idle Listening in Wireless Networks

Presentation transcript:

Analyzing the MAC-level behavior of wireless networks in the wild Ratul Mahajan (Microsoft Research) Maya Rodrig, David Wetherall, John Zahorjan (University of Washington)

ratul | sigcomm | '062 Understanding the MAC of an operational network How often clients retransmit packets? Are hidden terminals common? Does RTS/CTS help? Is the capture effect common? Does the MAC use the medium efficiently? How does performance vary with offered load?

ratul | sigcomm | '063 Approaches to measure operational networks ApproachLimitation Collect packet logs at APsNot enough detail Instrument stationsImpractical in many settings Passively monitor the network Incomplete information of unknown quality

ratul | sigcomm | '064 Why is analysis based on passive monitoring hard? 1. Inherently incomplete view of network activity 2. Missing packet reception information 3. Missing network-level information

ratul | sigcomm | '065 Overview of Wit Merge ( halfWit) Infer ( nitWit) Derive measures ( dimWit)

ratul | sigcomm | '066 Merging with halfWit halfWit Trace from Monitor 1 Merged trace: consistent, unified view Trace from Monitor 2 Trace from Monitor N......

ratul | sigcomm | '067 Inference with nitWit Observation: logged transmissions can reveal both pieces of information nitWit Merged trace Enhanced trace with: 1.packet reception status 2.missing packets

ratul | sigcomm | '068 Formal-language approach to inference If the protocol is a language packets are language symbols logical protocol exchanges are sentences Trace contains interleaved, partial sentences Our task: infer matching complete sentences we use an FSM-based inference engine

ratul | sigcomm | '069 Non-deterministic walk reveals reception status Start S1S3 ? DATA ACK Marker S2S3 Accept DATA (rcvd) ACK (rcvd) Marker

ratul | sigcomm | '0610 Augmented FSM enables fast inference of missing packets ACK Marker Start S2S3S5 Accept DATA (rcvd) ACK (rcvd) Marker

ratul | sigcomm | '0611 Accuracy of nitWit % of pkts captured by the monitors % of correctly predicted pkt reception statuses

ratul | sigcomm | '0612 Deriving measures with dimWit # of stations contending for the medium is a measure of instantaneous offered load estimation challenge: missing relevant state approach: view transmissions through the lens of MAC rules dimWit Trace enhanced by nitWit Measures of MAC behavior: goodput, #contenders, etc.

ratul | sigcomm | '0613 Accuracy of estimate of #contenders (actual – dimWit ) cumulative % of pkt transmissions CDF of error in the estimate of # contenders

ratul | sigcomm | '0614 Monitoring the SIGCOMM 04 network 3 days, 500+ users, 5 official APs, 5 monitors Focus on analyzing Channel 1 in this talk estimated 90% pkts captured in the merged trace

ratul | sigcomm | '0615 Example results on MAC behavior at the SIGCOMM 04 network # contenders medium use (%) # contenders reception ratio Poor medium usage at low contention High contention did not reduce reception ratio # contenders % of packets Low contention was dominant

ratul | sigcomm | '0616 Conclusions Wit enables detailed MAC-level analysis of operational wireless networks merging produces a single, consistent view inference helps complete that view the enhanced trace enables many new analyses Code and trace data: networking/wireless/