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  1. Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing (MCC '13)
  2. CrowdWatch: enabling in-network crowd-sourcing
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A peek into smartphones, cloud services and their security
MPSDataStore: a sensor data repository system for mobile participatory sensing
Energy-efficient content retrieval in mobile cloud
ENDA: embracing network inconsistency for dynamic application offloading in mobile cloud computing
Seeker-assisted information search in mobile clouds
Enabling secure location-based services in mobile cloud computing
Accelerating the mobile web with selective offloading
Mobile fog: a programming model for large-scale applications on the internet of things
vSkyConf: cloud-assisted multi-party mobile video conferencing
Towards resource sharing in mobile device clouds: power balancing across mobile devices
CrowdWatch: enabling in-network crowd-sourcing

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CrowdWatch: enabling in-network crowd-sourcing

Content Provider ACM Digital Library
Author Alkaff, Hilfi Karahalios, Karrie Campbell, Andrew Kravets, Robin Nahrstedt, Klara
Abstract Proliferation of mobile smartphones has opened up possibilities of using crowd-sourcing to gather data from and so monitor large crowds. However, depending on the size of the crowd, current solutions either put unpredictable stress on the infrastructure and energy-constrained smartphones or do not capture the crowd behavior accurately. In response, we present CrowdWatch, a scalable, distributed and energy-efficient crowd-sourcing framework. CrowdWatch achieves its goal through off-loading some of the processing to the devices and establishing a hierarchy of participants by exploiting devices with multiple radios (i.e. WiFi (high-power) and BlueTooth (low-power)). CrowdWatch can outperform traditional crowd-sourcing frameworks by reducing the stress on the infrastructures to 10% of that of a traditional crowd-sourcing solution, while only requiring each phone to use their Wi-Fi radios 15% of the time in a dense environment.
Starting Page 57
Ending Page 62
Page Count 6
File Format PDF
ISBN 9781450321808
DOI 10.1145/2491266.2491277
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2013-08-16
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Crowdsourcing Smartphones Energy-management
Content Type Text
Resource Type Article
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