NDLI: Hadoop MapReduce for Tactical Clouds

Content Provider	IEEE Xplore Digital Library
Author	George, J. Chien-An Chen Stoleru, R. Xie, G.G. Sookoor, T. Bruno, D.
Copyright Year	2014
Description	Author affiliation: Comput. Sci. Div., U.S. Army Res. Lab., Aberdeen Proving Ground, MD, USA (Sookoor, T.; Bruno, D.) \|\| Dept. of Comput. Sci. & Eng., Texas A&M Univ., College Station, TX, USA (George, J.; Chien-An Chen; Stoleru, R.) \|\| Dept. of Comput. Sci., Naval Postgrad. Sch., Monterey, CA, USA (Xie, G.G.)
Abstract	We envision a future where real-time computation on the battlefield provides the tactical advantage to an Army over its adversary. The ability to collect and process large amounts of data to provide actionable information to soldiers will greatly enhance their situational awareness. Our vision is based on the observation that the U.S. Military is attempting to equip soldiers with smartphones. While individual phones may not be sufficiently powerful for processing large amount of data, using the mobile devices carried by a squad or platoon of Soldiers as a single distributed computing platform, a Tactical Cloud, would enable large-scale data processing to be conducted in battlefields. In order for this vision to be realized, two issues have to be addressed. The first is the complexity of writing applications for distributed computing environments, and the second is the vulnerability of data on mobile devices. In this paper, we propose combining two existing technologies to address these issues. The first is Hadoop MapReduce, a scalable platform that provides distributed storage and computational capabilities on clusters of commodity hardware, and the second is the Mobile Distributed File System (MDFS) which allows distributed data storage with built-in reliability and security. By making the MDFS file system work with Hadoop on mobile devices, we hope to enable big data applications on tactical clouds.
Starting Page	320
Ending Page	326
File Size	722365
Page Count	7
File Format	PDF
ISBN	9781479927302
DOI	10.1109/CloudNet.2014.6969015
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-08
Publisher Place	Luxembourg
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hadoop Mobile communication Mobile handsets Peer-to-peer computing Mobile cloud Servers Cryptography Reliability Map-reduce
Content Type	Text
Resource Type	Article

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