DocumentCode :
3696564
Title :
Mobile storm: Distributed real-time stream processing for mobile clouds
Author :
Qian Ning;Chien-An Chen;Radu Stoleru;Congcong Chen
Author_Institution :
Department of Computer Science and Engineering, Texas A&
fYear :
2015
Firstpage :
139
Lastpage :
145
Abstract :
Recent advances in mobile technologies have enabled a plethora of new applications. The hardware capabilities of mobile devices, however, are still insufficient for real-time stream data processing (e.g., real-time video stream). In order to process real-time streaming data, most existing applications offload the data and computation to a remote cloud service, such as Apache Storm or Apache Spark Streaming. Offloading streaming data, however, has high costs for users, e.g., significant service fees and battery consumption. To address these challenges, we design, implement and evaluate Mobile Storm, the first stream processing platform for mobile clouds, leveraging clusters of local mobile devices to process real-time stream data. In Mobile Storm, we model the workflow of a real-time stream processing job and decompose it into several tasks so that the job can be executed concurrently and in a distributed manner on multiple mobile devices. Mobile Storm was implemented on Android phones and evaluated extensively through a real-time HD video processing application. The result shows that Mobile Storm effectively processes HD Video Stream in a mobile cloud, which would be impossible on a single mobile device.
Keywords :
"Mobile communication","Storms","Mobile handsets","Real-time systems","Servers","Sparks","Fasteners"
Publisher :
ieee
Conference_Titel :
Cloud Networking (CloudNet), 2015 IEEE 4th International Conference on
Type :
conf
DOI :
10.1109/CloudNet.2015.7335296
Filename :
7335296
Link To Document :
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