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Outsourcing Coordination and Management of Home Wireless Access Points through an Open API Ashish Patro* Prof. Suman Banerjee University of Wisconsin Madison.

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Presentation on theme: "Outsourcing Coordination and Management of Home Wireless Access Points through an Open API Ashish Patro* Prof. Suman Banerjee University of Wisconsin Madison."— Presentation transcript:

1 Outsourcing Coordination and Management of Home Wireless Access Points through an Open API Ashish Patro* Prof. Suman Banerjee University of Wisconsin Madison *patro@cs.wisc.edu Ashish Patro / INFOCOM 20151

2 Dense residential WiFi deployments… Apartment Building Apt 202 Apt 201 WiFi Access Points WiFi Clients (e.g., laptops, smartphones) Ashish Patro / UW Madison2

3 What problems degrade residential WiFi experience today? Ashish Patro / UW Madison3 WiFi Access Points Apartment Building

4 1. Channel congestion Ashish Patro / UW Madison4 Dark Knight #@!*@

5 Real Scenario in an apartment building Ashish Patro / INFOCOM 20155 AP 1 AP 2 Long periods with channel congestion

6 2. Hidden terminal WiFi interference Ashish Patro / UW Madison6 Dark Knight Happy Feet #@!*@

7 3. Non-WiFi interferers Ashish Patro / UW Madison7 > 50% throughput degradation due to non-WiFi interference (MobiCom’13) Microwave Oven ZigBee Bluetooth Devices Cordless Phones

8 4. Static and inefficient channel configuration Ashish Patro / UW Madison8 Spectrum Wastage: More than 50% of home APs used static WiFi channels (MobiCom’13) Home WiFi Access Points

9 How can we mitigate these residential WiFi problems ? Ashish Patro / UW Madison9 WiFi Access Points Apartment Building

10 Goal: Managing home Access Points (APs) Ashish Patro / UW Madison Apartment Building AP Mitigate WiFi and non-WiFi interference Improve spectrum utilization Enable AP cooperation to improve performance Software-only solution for commodity WiFi APs Vendor neutral APIs for wider adoption 10

11 A central management control plane? Ashish Patro / INFOCOM 201511 AP Apartment 201Apartment 202Apartment 203

12 Enter COAP… COAP: Coordination framework for Open APs – A cloud based management service using OpenFlow SDN Ashish Patro / INFOCOM 201512 COAP Enabled APs........ Apartment Building Internet COAP Cloud Controller (Hosted by ISP or Building manager)

13 Outline Introduction COAP Framework Overview COAP Applications Summary Ashish Patro / INFOCOM 201513

14 COAP framework Ashish Patro / INFOCOM 201514 Uses open-source OpenFlow SDN + Floodlight controller Implemented OpenFlow wireless extensions to collect statistics from APs Cloud-based COAP controller collects and coalesces statistics to configure APs COAP enabled home Access Points COAP Cloud Controller (Hosted by ISP or Building manager)

15 COAP API examples (at Access Point) Ashish Patro / INFOCOM 201515 APConfigManager BasicStatsReporter DiagnosticStatsReporter GetAirtimeUtilization() GetLinkStatistics() GetNeighborInfo() GetAirtimeUtilization() GetLinkStatistics() GetNeighborInfo() SetParameters(channel, power) SetAirtimeAccess(slotDur, xmitBitmap) SetParameters(channel, power) SetAirtimeAccess(slotDur, xmitBitmap) GetNonWiFiDevices() (Airshark, IMC’11) GetPacketSummaries() (WiSe, MobiCom’13) GetNonWiFiDevices() (Airshark, IMC’11) GetPacketSummaries() (WiSe, MobiCom’13)

16 Outline Introduction COAP Framework Overview COAP Applications Summary Ashish Patro / INFOCOM 201516

17 Ashish Patro / UW Madison Channel 1, 6 or 11 ? Co-operative spectrum allocation Interference mitigation Context-aware configuration 17 Microwave oven activity

18 WiFi channel configuration Ashish Patro / INFOCOM 201518 APs........ Apartment Building Channel? COAP Cloud Controller Airtime Util Statistics Channel Configuration

19 Using airtime-aware channel configuration Ashish Patro / INFOCOM 201519 12 COAP APs in an apartment building COAP Enabled APs........ Apartment Building Random vs “airtime-aware” channel config over 6 days (one day per scheme)

20 Using airtime-aware channel configuration Ashish Patro / INFOCOM 201520 12 COAP APs: Random vs “airtime-aware” channel config over 6 days (one day per scheme) Upto 42% reduction in median airtime utilization

21 Ashish Patro / UW Madison Channel 1, 6 or 11 ? Co-operative spectrum allocation Interference mitigation Context-aware configuration 21 Microwave oven activity

22 Hidden terminal WiFi interference Ashish Patro / UW Madison22 Dark Knight Happy Feet #@!*@

23 Slotting mechanism AP 1 (Hidden terminal) AP 2 (Hidden terminal) t1t1 t2t2 t3t3 t4t4 …………. 10 ms Transitive time synchronization (error < 50 microseconds) Time synchronization using common WiFi frames (error < 50 μs) Ashish Patro / UW Madison23

24 Example: Mitigate hidden terminal interference Ashish Patro / UW Madison Setup: 6 WiFi (802.11n) Links - 6 APs and clients 3 HTTP video streaming WiFi links (average 10 Mbps) 3 bulk download links (max 10 Mbps) Setup as hidden terminals Used “Slotting” mechanism to mitigate interference 24

25 Mitigating hidden terminal interference Ashish Patro / UW Madison HTTP video streaming links Hidden terminals (Bulk downloads) Slotting improved video throughput Minor throughput drop for hidden terminals 25

26 Impact on packet losses and video quality Ashish Patro / UW Madison 50% reduction in packet losses Better spectrum utilization Almost zero frame drops with “Slotting” Smooth video experience 26 At Access Point At Client

27 Ashish Patro / UW Madison Channel 1, 6 or 11 ? Co-operative spectrum allocation Interference mitigation Context-aware configuration 27 Microwave oven activity

28 Context-aware configuration Predict future WiFi/non-WiFi activity Proactively configure APs based on predicted future activity Example inputs for modeling context: – Client device type (e.g., iPad, Google TV) – Traffic source (e.g., Netflix, YouTube) – Time of day – Activity statistics (session durations, bytes downloaded) Ashish Patro / INFOCOM 201528

29 Example: “Time of day” microwave oven activity Ashish Patro / UW Madison29 How predictable is this activity for future time periods?

30 Building “Activity Vectors” Activity Vector: Represents time-series device activity Correlate activity vectors across “time-spans”(e.g., 1 day, 1 week etc.) to determine predictability Ashish Patro / INFOCOM 201530

31 Correlation between microwave oven activity across time spans Ashish Patro / UW Madison31 High predictability of microwave oven activity with 5 days of data

32 COAP demo screenshot Ashish Patro / UW Madison32 COAP APs Video Client Video Server COAP controller dashboard Cordless Phone (Interferer)

33 Summary Presented an SDN framework for managing home Access Points – Provides a light-weight centralized control plane Enabler for improving residential WiFi experience – Upto 42% reduction in channel contention – Motivated “Airtime access APIs” to mitigate WiFi interference Context-aware applications can help with pro- active configuration of APs Ashish Patro / INFOCOM 201533

34 Ashish Patro / INFOCOM 201534 Thanks! http://research.cs.wisc.edu/wings/projects/coap/


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