• Publications
  • Influence
Theory and Practice of Bloom Filters for Distributed Systems
TLDR
This survey article presents a number of frequently used and useful probabilistic techniques, reviewing over 20 variants and discussing their application in distributed systems. Expand
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Carat: collaborative energy diagnosis for mobile devices
TLDR
We aim to detect and diagnose energy anomalies, abnormally heavy battery use. Expand
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Smartphone Energy Consumption: Modeling and Optimization
Part I. Understanding Energy Consumption: 1. Introduction 2. Energy and power primer 3. Smartphone batteries 4. Energy measurement 5. On human behavior and energy efficiency Part II. EnergyExpand
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BeTelGeuse: A Platform for Gathering and Processing Situational Data
TLDR
BeTelGeuse is an extensible data collection platform for mobile devices, which also automatically infers higher level context from sensor data. Expand
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Collaborative Energy Debugging for Mobile Devices
TLDR
This paper presents a method for diagnosing energy bugs in the wild, given incomplete and noisy instrumentation measurements from a community of clients. Expand
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The company you keep: mobile malware infection rates and inexpensive risk indicators
TLDR
We present the first independent study of malware infection rates and associated risk factors using data collected directly from over 55,000 Android devices. Expand
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Mobile search and the cloud: The benefits of offloading
TLDR
This paper presents the benefits and drawbacks of mobile desktop search coupled with cloud- assisted operations, such as operation offloading, cloud storage, and cloud-assisted search. Expand
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How carat affects user behavior: implications for mobile battery awareness applications
TLDR
This paper examines a large-scale mobile battery awareness application, called Carat, to see how it changes user behavior with long-term use. Expand
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Energy modeling of system settings: A crowdsourced approach
TLDR
The question “Where has my battery life gone?” remains a common source of frustration for many smartphone users. Expand
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Differentially private Bayesian learning on distributed data
TLDR
We propose a secure multi-party sum function for aggregating summaries from data holders and the Gaussian mechanism for DP. Expand
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