3 research outputs found
WLAN Interface Management on Mobile Devices
The number of smartphones in use is overwhelmingly increasing every year.
These devices rely on connectivity to the Internet for the majority of
their applications. The ever-increasing number of deployed 802.11 wireless
access points and the relatively high cost of other data services make the
case for opportunistic communication using free WiFi hot-spots. However,
this requires effective management of the WLAN interface, because by
design the energy cost of WLAN scanning and interface idle operation is
high and energy is a primary resource on mobile devices.
This thesis studies the WLAN interface management problem on mobile
devices. First, I consider the hypothetical scenario where future
knowledge of wireless connectivity opportunities is available, and present
a dynamic programming algorithm that finds the optimal schedule for the
interface. In the absence of future knowledge, I propose several heuristic
strategies for interface management, and use real-world user traces to
evaluate and compare their performance against the optimal algorithm.
Trace-based simulations show that simple static scanning with a suitable
interval value is very effective for delay-tolerant, background
applications. I attribute the good performance of static scanning to the
power-law distribution of the length of the WiFi opportunities of
mobile users, and provide guidelines for choosing the scanning interval
based on the statistical properties of the traces. I improve the
performance of static scanning, by 46% on average, using a local cache of
previous scan results that takes advantage of the location hints provided
by the set of visible GSM cell towers
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AndWellness: An Open Mobile System for Activity and Experience Sampling
Advances in technology and infrastructure have positioned mobile phones as a convenient platform for real-time assessment of an individuals health and behavior, while offering unprecedented accessibility and affordability to both the producers and the consumers of the data. In this paper we address several of the key challenges that arise in leveraging smartphones for health: designing the complex set of building blocks required for an end-to-end system, motivating participants to sustain engagement in long-lived data collection, and interpreting both the data and the quality of the data collected.We present AndWellness, a mobile to web platform that records, analyzes, and visualizes data from both prompted experience samples entered by the user, as well as continuous streams of data passively collected from sensors onboard the mobile device. In order to address the system design and participation motivation challenges, we have incorporated feedback from hundreds of behavioral and technology researchers, focus group participants, and end-users of the system in an iterative design process. AndWellness additionally includes rich system and user analytics to instrument the act of participation itself and ultimately to contextualize and better understand the factors affecting the quality of collected data over time. We evaluate the usability and feasibility of AndWellness using data from 3 studies with a variety of populations including young moms and recent breast cancer survivors. More than 85% of the diverse set of participants who responded to exit surveys claim they would use AndWellness for further personal behavior discovery