DocumentCode :
118758
Title :
A container-based elastic cloud architecture for real-time full-motion video (FMV) target tracking
Author :
Wu, Ryan ; Yu Chen ; Blasch, Erik ; Bingwei Liu ; Genshe Chen ; Dan Shen
Author_Institution :
Dept. of Electr. & Comput. Eng., Binghamton Univ., Binghamton, NY, USA
fYear :
2014
fDate :
14-16 Oct. 2014
Firstpage :
1
Lastpage :
8
Abstract :
Full-motion video (FMV) target tracking requires the objects of interest be detected in a continuous video stream. Maintaining a stable track can be challenging as target attributes change over time, frame-rates can vary, and image alignment errors may drift. As such, optimizing FMV target tracking performance to address dynamic scenarios is critical. Many target tracking algorithms do not take advantage of parallelism due to dependencies on previous estimates which results in idle computation resources when waiting for such dependencies to resolve. To address this problem, a container-based virtualization technology is adopted to make more efficient use of computing resources for achieving an elastic information fusion cloud. In this paper, we leverage the benefits provided by container-based virtualization to optimize an FMV target tracking application. Using OpenVZ as the virtualization platform, we parallelize video processing by distributing incoming frames across multiple containers. A concurrent container partitions video stream into frames and then resembles processed frames into video output. We implement a system that dynamically allocates VE computing resources to match frame production and consumption between VEs. The experimental results verify the viability of container-based virtualization for improving FMV target tracking performance and demostrates a solution for mission-critical information fusion tasks.
Keywords :
cloud computing; containers; image fusion; object detection; parallel algorithms; resource allocation; target tracking; video signal processing; video streaming; virtualisation; FMV target tracking optimisation; OpenVZ; concurrent container partitions video stream; container-based elastic cloud architecture; container-based virtualization; container-based virtualization technology; continuous video stream; dynamic VE computing resource allocation; elastic information fusion cloud; frame consumption; frame distribution; frame production; full motion video; image alignment errors; mission-critical information fusion; object detection; parallelize video processing; Containers; Dynamic scheduling; Operating systems; Resource management; Streaming media; Target tracking; Virtualization; Container-based Virtualization; Dynamic Resource Allocation; Full-Motion Video (FMV); Information Fusion Cloud; OpenVZ; Target Tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Imagery Pattern Recognition Workshop (AIPR), 2014 IEEE
Conference_Location :
Washington, DC
Type :
conf
DOI :
10.1109/AIPR.2014.7041896
Filename :
7041896
Link To Document :
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