Characterizing Home Wireless Performance: The Gateway View Ioannis Pefkianakis* H. Lundgren^, A. Soule^, J. Chandrashekar^, P. Guyadec^, C. Diot^, M. May^, K. Doorselaer^, K. Oost^ HP Labs*Technicolor^

Today’s Residential WLANs Wireless gateway WiFi repeater Tablet Wireless baby monitor Wireless gateway Laptop Smartphone Microwave oven Multitude of Wi-Fi devices running high-bandwidth apps

ISPs Strive to Understand Wi-Fi Home Nets What and how many devices dominate the traffic? What is the wireless performance? How often do users experience poor performance? What is behind poor performance?

Existing Approaches on Understanding Home Nets’ Performance The customized-AP approach allows for fine time scale measurements from all the devices connected to the AP –[WiSe, MOBICOM’13], [Papagiannaki et al., INFOCOM’13], [BISMark] –Small-scale deployments of technically inclined volunteers The end-host measurement tools run as apps and collect feedback at the client side –[Home Net Profiler, PAM’13] –One shot measurements, limited application-level feedback Our approach: Collect data from the home gateways of the subscribers of a large ISP under normal service operation

Outline Measurement infrastructure and deployment Metrics Wi-Fi environment and traffic dynamics Wireless performance Root cause of performance bottlenecks

Measurement Infrastructure Broadband Network Dashboard Controller Data storage WiFi repeater Tablet Wireless baby monitor b/g/n wireless gateway OSGI Bundle Passive measurements from subscribers’ gateways

Why Home Gateways? Gateways offer a complete view of the home network –Continuously monitor all the devices connected to the gateway –Observe neighboring Wi-Fi networks –Capture both wireless link performance and traffic dynamics Using existing infrastructure allows for large-scale, more diverse deployment

Dataset 167 gateways (71% fiber, 29% ADSL) in 10 different cities gateways report every 30 seconds 4-month (June-September 2013) collection campaign 1328 Wi-Fi devices detected

Metrics What we have –PHY rate Performance indicator –RSSI Wireless coverage metric –Traffic counters –Neighboring SSIDs and their RSSI’s What we miss –Frame losses –Channel contention –We cannot capture the actual wireless throughput

How to Capture Wireless Problems? Coverage Interference Wireless gateway Tablet weak signal (low RSSI) Map RSSI to Speed (in RF chamber) RSSI (dBm)Expected PHY rate (R E ) [min, -88]6.5 Mbps …… [-70, max]65 Mbps Wireless gateway Tablet Wireless baby monitor loss PHY rate R drops but RSSI remains the same RateGap = Rate_index(R E )-Rate_index(R)

Metrics: Putting Everything Together High R E Low R E High R good performancepoor performance (RA dynamics) Low R poor performance (interference/RA dynamics) poor performance (poor coverage)

Wireless, Mobile Networks : advanced capabilities Rate adaptation base station, mobile dynamically change transmission rate (physical layer modulation technique) as mobile moves, SNR varies QAM256 (8 Mbps) QAM16 (4 Mbps) BPSK (1 Mbps) SNR(dB) BER operating point 1. SNR decreases, BER increase as node moves away from base station 2. When BER becomes too high, switch to lower transmission rate but with lower BER

Outline Measurement infrastructure and deployment Metrics Wi-Fi environment and traffic dynamics Wireless performance Root cause of performance bottlenecks

Wi-Fi Environment High penetration of the newer n devices –0.5%.11b, 42.5%.11g, 45.5%.11n 1x1, 11.5%.11n 2x2 Diversity in the number of Wi-Fi home devices (1 to 25) –Median home has 4 resident devices (i.e., observed for several days)

Wireless, Mobile Networks6-15 Characteristics of selected wireless links Indoor 10-30m Outdoor m Mid-range outdoor 200m – 4 Km Long-range outdoor 5Km – 20 Km G: IS-95, CDMA, GSM 2.5G: UMTS/WCDMA, CDMA b a,g 3G: UMTS/WCDMA-HSPDA, CDMA2000-1xEVDO 4G: LTWE WIMAX a,g point-to-point n Data rate (Mbps)

Wi-Fi Traffic Dynamics Traffic is generated by a few devices 3 Wi-Fi devices generated the most traffic in 70% of the homes … during evening times

Outline Measurement infrastructure and deployment Metrics Wi-Fi environment and traffic dynamics Wireless performance Root cause of performance bottlenecks

18 What is Home Wireless Performance? Wireless link performance (i.e., PHY rate) is overall good! Effective (f(PHY Rate, overheads)) higher than actual throughput … but there are still performance bottlenecks (for 7.6% of the samples PHY rate <=6.5Mbps) throughput gap > 20Mbps for most of the homes

Performance Variation Across Homes The fraction of poor performance episodes varies across homes for most of the homes poor episodes are ≤ 6% Poor performance episodes can be up to 66%

20 Root Cause of Poor Performance Metric: Convert RSSI signals to an expected link speed (PHY Rate) Wireless coverage is not likely a cause of poor performance 78% of the transmissions at the peak expected PHY rate

Root Cause of Poor Performance Poor performance can be caused by interference and PHY rate adaptation dynamics High RateGap can lead to poor performance for 18% of the instances RateGap>4 RateGap varies across homes The peak RateGap corresponds to the 2 homes with the highest poor performance instances

Interference Causes Contention from in-home Wi-Fi devices is low –For the majority of homes (78%) local contention is less than 10% –Interference can be attributed to external sources (non-Wi-Fi devices, neighboring Wi-Fi networks) There is no strong correlation between Wi-Fi performance and the density of the neighboring Wi-Fi environment.

Conclusion We study Wi-Fi home networks of the subscribers of a large ISP Wireless link performance (i.e., PHY rate) is overall good We still identify instances of poor performance, where we eliminate poor coverage to be their root cause ISPs’ helpdesk calls for wireless problems may not be attributed to the wireless link –… but to gateway misconfigurations, authentication problems, end-device issues

Thank you!