KEYWORDS: Video, Video surveillance, Video processing, Data processing, Signal processing, Distributed computing, Computing systems, Systems modeling, Multidimensional signal processing
Current trends in increasing the intelligence level of software systems for analyzing data flows under the constraints of processing time require the study of new technologies that take advantage of a distributed computing environment. In this paper, we implement a technology for distributed streaming processing of multidimensional optical signals based on the Apache Flink framework. The technology is studied on the task of transport video surveillance tracking unique objects captured by a system of geographically dispersed video cameras. We study the ability of proposed solution scale the processing depending on the amount of resources in the cloud, the quantity and quality of optical signals. The characteristics of processing processes of a set of frames of varying complexity on a computing cluster are investigated. NVIDIA AI City Challenge is used as test data sets.
This research article contains an experiment with implementation of image filtering task in Apache Storm and IBM InfoSphere Streams stream data processing systems. The aim of presented research is to show that new technologies could be effectively used for sliding window filtering of image sequences. The analysis of execution was focused on two parameters: throughput and memory consumption. Profiling was performed on CentOS operating systems running on two virtual machines for each system. The experiment results showed that IBM InfoSphere Streams has about 1.5 to 13.5 times lower memory footprint than Apache Storm, but could be about 2.0 to 2.5 slower on a real hardware.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.