Signal and image processing algorithm performance in a virtual and elastic computing environment

Kelly W. Bennett; James Robertson

doi:10.1117/12.2016941

23 May 2013 Signal and image processing algorithm performance in a virtual and elastic computing environment

Kelly W. Bennett, James Robertson

Proceedings Volume 8734, Active and Passive Signatures IV; 87340B (2013) https://doi.org/10.1117/12.2016941
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

The U.S. Army Research Laboratory (ARL) supports the development of classification, detection, tracking, and localization algorithms using multiple sensing modalities including acoustic, seismic, E-field, magnetic field, PIR, and visual and IR imaging. Multimodal sensors collect large amounts of data in support of algorithm development. The resulting large amount of data, and their associated high-performance computing needs, increases and challenges existing computing infrastructures. Purchasing computer power as a commodity using a Cloud service offers low-cost, pay-as-you-go pricing models, scalability, and elasticity that may provide solutions to develop and optimize algorithms without having to procure additional hardware and resources. This paper provides a detailed look at using a commercial cloud service provider, such as Amazon Web Services (AWS), to develop and deploy simple signal and image processing algorithms in a cloud and run the algorithms on a large set of data archived in the ARL Multimodal Signatures Database (MMSDB). Analytical results will provide performance comparisons with existing infrastructure. A discussion on using cloud computing with government data will discuss best security practices that exist within cloud services, such as AWS.

Citation Download Citation

Kelly W. Bennett and James Robertson "Signal and image processing algorithm performance in a virtual and elastic computing environment", Proc. SPIE 8734, Active and Passive Signatures IV, 87340B (23 May 2013); https://doi.org/10.1117/12.2016941

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