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A Location-Based Management System for Enterprise Wireless LANs Ranveer Chandra, Jitendra Padhye, Alec Wolman and Brian Zill Microsoft Research.

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Presentation on theme: "A Location-Based Management System for Enterprise Wireless LANs Ranveer Chandra, Jitendra Padhye, Alec Wolman and Brian Zill Microsoft Research."— Presentation transcript:

1 A Location-Based Management System for Enterprise Wireless LANs Ranveer Chandra, Jitendra Padhye, Alec Wolman and Brian Zill Microsoft Research

2 2 Wireless Network Woes Corporations spend lots of $$ on WLAN infrastructure –Worldwide enterprise WLAN business expected to grow from $1.1 billion this year to $3.5 billion in 2009 Wireless networks perceived to be “flaky”, less secure than wired networks –Users complain about: Lack of coverage, performance, reliability Authentication problems (802.1X protocol issues) –Network administrators worry about Providing adequate coverage, performance Security and unauthorized access Better WLAN management system needed!

3 3 Typical Questions Asked by Network Administrators Are all areas of the building covered? Are there areas in the building where clients repeatedly switch between APs? Are there locations with very high loss rates? Where do most of the clients use the wireless network from? –Conference rooms? Offices? Many problems are location-specific

4 4 Two Key Requirements for WLAN Management Systems Integrated, accurate location system Dense array of sensors –Complex, time-varying signal propagation indoor environments –Many channels need to be monitored

5 5 State of the Art AP-based monitoring [Aruba, AirDefense…] –Pros: Easy to deploy (APs are under central control) –Cons: Can not detect coverage problems using AP-based monitoring Single radio APs can not be effective monitors Specialized sensor boxes [Jigsaw, WIT – SIGCOMM 06] –Pros: Can provide detailed analysis –Cons: Expensive, not scalable Monitoring by mobile clients [ClientConduit - Mobicom 04] –Pros: Inexpensive, suitable for un-managed environments –Cons: Unpredictable coverage, client locations not known, battery power may become an issue

6 6 Observations Desktop PC’s with good wired connectivity are ubiquitous in enterprises Outfitting a desktop PC with 802.11 wireless NIC is inexpensive –Wireless USB dongles are cheap As low as $6.99 at online retailers –PC motherboards are starting to appear with 802.11 radios built-in Combine to create a dense deployment of wireless sensors DAIR: Dense Array of Inexpensive Radios + Details: HotNets’05, MobiSys’06

7 7 Commands Wired Network Database AirMonitor Summarized Data Commands and Database Queries Data from database Data to inference engine Summarized data from Monitors AirMonitor Inference Engine DAIR Architecture Other data: AP locations, Floor Map, AP BSSIDs AirMonitor

8 8 Advantages of DAIR Architecture Dense deployment of sensors –Without excessive cost –Robustness: Can tolerate loss of a few sensors –Can use very simple algorithms for analysis Stationary sensors: –Help build simple, yet accurate location system –Permit historical analysis

9 9 Testbed 98 meters x 32 meters 150 offices and conference rooms. Typical office size: 3 meters x 3 meters Full-height walls. Solid wood doors 59 AirMonitors.

10 10 Example Application Estimate transmission rate obtained by clients at various locations on the floor –Study impact of distance between AP and client on transmission rate –Useful for detecting areas of poor coverage Design questions: –Which channels should the AirMonitors listen on? –What information should each AirMonitor record, and how to analyze the information? –How to locate clients?

11 11 Which channels should the AirMonitors listen on? What information should each AirMonitor record, and how to analyze the information? How to locate clients?

12 12 Channel Assignment Six APs (Aruba) –Known, fixed locations –Known, fixed BSSIDs But not fixed channels … –APs change channels (roughly once or twice a day) –Dynamic channel assignment by Aruba’s centralized controller Can’t assign AirMonitors to listen on fixed channels

13 13 AP Tracking AirMonitors “track” AP nearest to them –Start by scanning all channels –Once AP is found, stay on that channel –If no beacons are heard in 10 seconds, scan again Why nearest AP? –Most of the traffic near an AP is likely to be on the channel that the AP is on Other schemes possible: –Strongest signal –Scanning

14 14 Testbed Map with AP Assignment

15 15 Which channels should the AirMonitors listen on? What information should each AirMonitor record, and how to analyze the information? How to locate clients?

16 16 Information Gathering Reporting every packet to database not scalable. –Jigsaw and WIT [SIGCOMM 06] –Can overwhelm wired network and database. Each AirMonitor submits summary information –Aggregate packets for each pair –For each pair record aggregate statistics: Average signal strength, total number of packets and bytes –Submission intervals randomized to avoid load spikes 30-60 seconds.

17 17 Advantages and Disadvantages of Aggregation Advantage –Scalability: < 10Kbps traffic per AirMonitor Disadvantage: –Can’t perform packet-level analysis like Jigsaw/WIT –Difficult to combine observations from multiple AirMonitors Problem solved to some degree by density of sensors

18 18 Collecting Transmission Rate Data 1000 bytes Client AP SndrRcvrRate History CAP 1000 bytes (54, 1000) 1000 bytes (54, 2000) 300 bytes SndrRcvrRate History APC(54, 1000) AP C (6, 300) SndrRcvrRate History APC(6, 300) AM1 AM2 AM3 (6, 300)

19 19 Correlating the Data Each AirMonitor has an incomplete view of the “reality” Simple technique: –For each direction (uplink or downlink), use data from AirMonitor that heard the most packets AirMonitorSenderReceiverRate History AM1ClientAP(54, 2000) AM1APClient(6, 300) AM2APClient(54, 1000) (6, 300) AM3APClient(6, 300)

20 20 Advantages and Disadvantages Advantages: –Scalable –Requires only coarse-grained time synchronization –Accuracy improves with density of sensors Disadvantages: –Accuracy degrades at lower density –Does not permit packet-level analysis

21 21 Which channels should the AirMonitors listen on? What information should each AirMonitor record, and how to analyze the information? How to locate clients?

22 22 Self-Configuring Location Service Distinguishing features: –Heuristics to automatically determine AirMonitor locations –Automatic profiling of environment –Can locate any Wi-Fi transmitter (including uncooperative ones) –Office-level accuracy How it works: 1.AirMonitors locate themselves 2.AirMonitors regularly profile the environment to determine radio propagation characteristics 3.Inference engine uses profiles and observations from multiple AirMonitors to locate clients

23 23 How do AirMonitors Locate Themselves? Monitor machine activity to determine primary user Look up ActiveDirectory to determine office number Parse office map to determine coordinates of the office –Assume AirMonitor to be located at the center of the office Verify and adjust coordinates by observing which AirMonitors are nearby May not be available in all environments

24 24 Database Inference Engine Profiling the Environment AM1 AM2 AM3 FromToSignal Strength AM1AM2 60 AM2 AM3 AM1 AM3 AM2 55 33 39

25 25 Profiling the Environment y = 60*e -0.11x y = -1.4 x + 35.7 0 10 20 30 40 50 60 010203040 Distance Normalized Signal Strength Profile is used to calculate expected signal strength

26 26 Locating a Client Observed: 35 Observed RSSI: 50 Observed: 52 Observed: 35 Distance: 3, Expected RSSI: 43 Distance: 0, Expected RSSI: 60Distance: 6.5, Expected RSSI: 31 Distance: 7.2, Expected RSSI: 27 Distance: 1.3, Expected RSSI: 52 Distance: 1.1, Expected RSSI: 53 Distance: 6, Expected RSSI: 31 Distance: 6.2, Expected RSSI: 30 ? Adjust location to minimize error

27 27 Two Simpler Algorithms that Do Not Require Profiling StrongestAM –Client Location estimated as the location of AirMonitor that heard the strongest signal –Can be used if there is one AirMonitor in every office Centroid –Find AirMonitor that heard the strongest signal –Find all AirMonitors that heard signal within 85% of strongest signal strength –Client location estimated as the centroid of this group –Works well for our deployment

28 28 Accuracy of Location Estimation 21 locations, laptop client connected to corporate network, 802.11b/g

29 29 Which channels should the AirMonitors listen on? What information should each AirMonitor record, and how to analyze the information? How to locate clients? Example application Study Impact of client/AP distance on transmission rate

30 30 Bug! Downlink transmission rate was always 5.5Mbps regardless of client location Notified IT department Problem resolved after AP firmware was upgraded

31 31 Impact of Distance on Transmission Rate Oct 2-6, 2006, 15 minute intervals 802.11g clients Byte-averaged transmission rate (Mbps) 10m < dist <= 20m dist <= 10m dist > 20m 0 0.2 0.4 0.6 0.8 1 544536271890 0 0.2 0.4 0.6 0.8 1 544536271890 Byte-averaged transmission rate (Mbps) Downlink Uplink

32 32 Impact of distance on Loss Rate Downlink loss rates substantially higher than uplink loss rates Downlink Uplink

33 33 Area of Poor Coverage Median downlink frame loss rates ~50% Clients rapidly switch between 5 APs

34 34 System Scalability Additional load on desktops < 2-3% Wired network traffic per AirMonitor < 10Kbps

35 35 How many AirMonitors are needed? Depends on environmental factors, AP placement etc. In our environment: –With 59 AirMonitors: Median packet loss is 1.85% Max packet loss is 7% –Results degraded significantly with less than 44 AirMoniors

36 36 Conclusion Effective Wi-Fi monitoring systems need: –Integrated location service –Dense deployment of Wi-Fi sensors DAIR architecture creates dense deployment of Wi-Fi sensors without excessive cost Built a practical Wi-Fi monitoring system using DAIR

37 37 Questions?

38 38 Backup slides

39 39 Monitor Architecture

40 40 Association vs. Distance Majority of the clients do not connect to the nearest AP –Median distance between client and AP is 15 meters

41 41 Requirements for a WLAN Management System Integrated location service Complex signal propagation in indoor environment Many orthogonal channels Asymmetric links Multiple monitors Dense deployment Mobile Clients Problems may be location-specific Cope with incomplete data Scalable Self-configuring

42 42 Other analysis Correlation between loss rate and distance –Calculating loss rate is complicated –Requires each AirMonitor to perform “address matching”, as ACKs do not contain sender’s address –Estimating downlink loss rate is especially challenging, since each AP talks to multiple clients Detection of RF holes –Locations from where clients repeatedly sends probe requests, but get no probe response from corporate APs AP “flapping” –Clients repeatedly switch between several APs –Usually because they get poor service from all of them –Indicative of bad AP placement

43 43 Sample results One week of data (October 2006) –Monday to Friday, 8am to 8pm 59 AirMonitors System is currently operational, and our IT department uses the data ….

44 44 Frame Loss Rates – Downlink Median loss rate 43% when distance between client and AP > 20 meters. (20% when distance <= 20 meters)


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