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Characterizing Smartwatch Usage In The Wild

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1 Characterizing Smartwatch Usage In The Wild
Xing Liu, Tianyu Chen, Feng Qian, Zhixiu Guo, Felix Xiaozhu Lin, Xiaofeng Wang,and Kai Chen

2

3 Towards Understanding the Smartwatch Ecosystem
How users interact with smartwatch? How energy efficient is smartwatch? Can we optimize the battery usage? What is the network behavior?

4 Outline The user study infrastructure Usage patterns
Energy consumption Network traffic

5 The Smartwatch User Trial
Crowd-sourced measurement study involving 27 users Limited experiences using smartwatch

6 The Data Collection Data collector 106-day dataset, 37 GB of data
Automated – transparent to user Reliable – negligible down time Lightweight – CPU overhead < 3% Energy efficient – energy overhead < 3% 106-day dataset, 37 GB of data

7 Outline The user study infrastructure Usage patterns
Energy consumption Network traffic

8 Android Wear State Machine

9 Duration Spent across the States

10 Push Notifications 200+ phone apps push notifications to watch
An average user receives 40 notifications per day

11 Push Notifications How predictable are push notifications?
Difficult in the long term Strong bursty pattern in the short term The median inter-arrival time is only 49 seconds Problematic push logic

12 Smartwatch App Usage Smartwatch run 3rd-party apps
Avetage # apps installed on a watch: 18 Activity vs. Service Activity: a visible user interface Service: runs in the background without UI Service execution duration = 56x activity duration 70% of service execution < 1s

13 Outline The user study infrastructure Usage patterns
Energy consumption Derive fine-grained power model Apply the power model to our dataset Study methods for improving energy efficiency Network traffic

14 Energy Consumption in the Wild
Power Model Post Processing User Study Trace Energy Utilization Stats.

15 Energy Consumption in the Wild
Network incurs little E consumption CPU accounts 29.3%, Display contributes to 30.2% despite the small screen Dozing consume more than half of overall E. Awake state consume 26.6% of overall E A fully charged watch can last for about 41.7 hours

16 Improve Smartwatch Energy Efficiency
4 methods for improving the smartwatch energy efficiency Tuning the state machine timers Optimize OLED display Bundling delay-tolerant push notification Building workload aware CPU configuration

17 Outline The user study infrastructure Usage patterns
Energy consumption Network traffic

18 Smartwatch Networking
Our LG Urbane watch has both WiFi and Bluetooth. For most of the time(80%), the watch and phone are paired. Most traffic(91%) is delivered over BT. Most BT traffic(89%) is downlink (phone → watch).

19 Characteristics of BT Traffic Flows
Compared to smartphone traffic, smartwatch traffic flows are… Small: 77% of flows are smaller than 10KB Short: 53% of flows are shorter than 1sec Low rate, Average UL rate:~ 6kbps; Average DL flow rate: ~15kbps Highly bursty WiFi/BT handover is poorly supported

20 Limitation Lacks device diversity Participants have limited diversity
Android Wear 2.0 is up

21 Summary A first comprehensive measurement study of smartwatch usage “in the wild” Focus on three aspects: User Usage patterns Energy consumption Network traffic Smartwatch usage is highly different from smartphone! Provide key knowledge and hints for future system design


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