Enabling third-party apps in home gateways for and (through virtualization, edge computing, SDN, and RF management) Suman Banerjee (suman@cs.wisc.edu) 1
IoT and smart home apps
IoT and smart home apps Should the cloud manage your home thermostats?
IoT and smart home apps Should the cloud manage your home thermostats?
IoT and smart home apps Should your home security feed be uploaded to the cloud?
IoT and smart home apps Should your home security feed be uploaded to the cloud?
IoT and smart home apps Can we watch 4K streaming movies?
IoT and smart home apps Can we watch 4K streaming movies? Network variability
What is ParaDrop?
What is ParaDrop? Edge computing in the extreme Move the cloud right into your home
What is ParaDrop? Edge computing in the extreme Providing a cloud-like abstraction in your home WiFi router
WiFi router has low latency to home devices, and is always-on 3 rd party apps/services drop into your home WiFi router on-demand
SeeCam cloud service How it works? ParaDrop cloud manager SeeCam
SeeCam cloud service How it works? ParaDrop cloud manager EnvSense cloud service SeeCam EnvSense
ParaDrop examples Transcode video to adapt to wireless channel conditions Cache movies in router from head of instant queue Vehicular: Passenger tracking and engagement Home vent control
More examples Kids router Framily router TOR in your router Monitor your ISP (a la BisMark) <Your idea here >
Let us know if you need one! (We can ship you one or more) Check out www.paradrop.io
ParaDrop smart router A programmable substrate Virtualization framework Chutes Isolated and proprietary Multiple wireless interfaces WiFi, Bluetooth, ZigBee Cloud-based RF management
Overall architecture Cloud-based Wireless Management Virtualization and edge computing SDN Commodity AP Hardware 19
Overall architecture Cloud-based Wireless Management Virtualization and edge computing SDN Commodity AP Hardware 20
Problem statement Wireless users Expectation: wire-like performance Experience: seems to work well mostly flaky, connection keeps dropping [thread from user mailing list]: Is anybody else finding the network to be slow/flaky? I want to sanity check before I tell lab admin It was flaky for me yesterday. Restarting the laptop seemed to solve the problem
Problem statement What is the cause of interference?
Problem statement Network administrators [email from wireless network admin]: We continued to hear reports of problems, but could not reproduce the problems "on demand" nor do we have enough details to identify the real issues. Problem: issues are transient, lack of details and tools Is my wireless network operating well enough?
A blood test for the network (Comment made by Pravin Bhagwat: CTO, Airtight Networks)
Basic question Access points WLAN score BAD GOOD Can we provide a real-time, overall health score for the entire network? L1 L2 L3 Clients L4 L6 L5
Links Basic question BAD WLAN score GOOD Identify why certain links are under-performing L1 L2 L3 L4 L5 L6 BAD Goodness of the link Impact: 0.7 Impact: 0.3 Impact: 0.1 L6 Impact: 0.2 weak signal GOOD
RF Management goals Cloud controllers Key questions: Detect: Who are the real interferers? Quantify: How much interference do they cause? Locate: How do we locate these non-wifi devices? Mitigate: What configuration needed to mitigate them?
Our solution Real-time Interference estimators WiFi to WiFi Interference Non-WiFi to WiFi Interference (use WiFi-only hardware!) - COLLIE (Collision Inferencing Engine) - PIE (Passive Interference Estimator) - Airshark 1. detect non-wifi devices - WiFiNet 1. quantify interference impact 2. pin point device location
Spectrum at a university cafe High powered non-wifi devices share the spectrum with WiFi devices 29
Is non-wifi interference a real problem? How severe is the impact? More than 50% throughput drop and, in some cases, throughput drops to zero! How prevalent are the devices? Across locations, many devices frequently appeared with a high signal strength 30
Non-WiFi interferers Analog Cordless Phone (Uniden EXP4540) Video Camera (Pyrus Electronics) High duty devices Frequency hoppers ZigBee (Jennic JN 5121) Microwave Ovens (Whirlpool, Daewoo, Sunbeam) Broadband interferers FHSS Cordless Phone (Panasonic KT-TG2343) Bluetooth ACL/SCO (iphone, ipod touch, Jabra headsets) Game controllers (Wii, PS3) Audio Transmitter (GoGroove PurePlay)
Time Use a coarse-grained WiFi lens Coarse-grained freq. resolution 312 khz Sub-carriers Coarse-grained time resolution O(10 3 ) to O(10 4 ) samples/sec Frequency 22 MHz Limited spectrum view RSSI/power per sub-carrier 32
Airshark: how it works Device Detection Pipeline Spectral Sampling Pulse Detection Feature Extraction DT-classifiers Extract Features (OFF) (ON) Training / Classification Decision Tree Classifier 33
Detection Accuracy > 98% accuracy at signal strengths >= -80 dbm 34
Many trials Including integrating with a commercial off-the-shelf AP platform 35
Works with We built Linux drivers for spectral sampling for the AR92xx and AR93xx NICs Open sourced and publicly available Have also released an Android version For Samsung Nexus devices Check wisense.io Available from Google Play 36
Cloud-based RF Management COAP: Coordination framework for Open Access Points 37
Cloud-based RF Management COAP: Coordination framework for Open Access Points 38
Cloud-based RF Management COAP: Coordination framework for Open Access Points Analytics Interference estimation and mitigation techniques 39
Cloud-based RF Management COAP: Coordination framework for Open Access Points Analytics Spectrum Management Commands Interference estimation and mitigation techniques 40
Cloud-based RF Management COAP: Coordination framework for Open Access Points Analytics Spectrum Management Commands Interference estimation and mitigation techniques 41
Field Trials OpenWRT based APs ALIX 2d2 platform: (500 MHz AMD Geocode CPU, 256 DDR RAM, flash storage) 30+ APs deployed in homes & apartment complexes for 3+ years Madison, WI MDU Deployment 1 Cloud controller hosted in off-the-shelf Linux server MDU Deployment 14 APs 2 42
Microware cuts throughput 43
30.1 25.5 13 16 100% improvement most of the time Data is sorted
Enabling third-party apps in home gateways for and Suman Banerjee (suman@cs.wisc.edu) 45