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Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 5, Issue 1, Pages 246-276, DOI: https://doi.org/10.21307/ijssis-2017-480
License : (CC BY-NC-ND 4.0)
Received Date : 21-February-2012 / Accepted: 22-February-2012 / Published Online: 01-March-2012
Governmental institutions all over the world are trying to increase the level of security of their countries emphasizing the usage Information Technology solutions. We believe that Cloud Computing may strongly help Homeland Security, since it offers a very flexible support for organizing and managing heterogeneous systems, providing huge amount of processing, storing and sensing resources. In this work we introduce a new Cloud architecture able to virtualize different types of sensing environments in virtual sensing elements, logically belonging to Cooperating Clouds. It represents a very flexible solution, which offers seamless, secure and advanced services to support Homeland Security.
 L. Janczewski and A. Colarik, Managerial guide for handling cyber-terrorism and information warfare. Idea Group Publishing, 2005.
[Online]. Available: http://books.google.com/books?id=vnjfMHWdKHQC
 T. Holt and B. Schell, Corporate Hacking and Technology-Driven Crime: Social Dynamics and Implications. Igi Global, 2010. [Online].
Available: http://books.google.com/books?id=LAIjG OGuIMC
 D. Mortimer, “Homeland security public safety dive teams: how technology can help,” in OCEANS, 2005. Proceedings of MTS/IEEE, 2005,
pp. 178 – 183 Vol. 1.
 A. Koyuncugil and N. Ozgulbas, Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection,
ser. Premier Reference Source. Igi Global, 2010. [Online]. Available: http://books.google.com/books?id=l4Ir1nvyURIC
 C. Reddick, Homeland security preparedness and information systems: strategies for managing public policy. Information Science
Reference, 2010. [Online]. Available: http://books.google.com/books?id=NaT Fob6lBIC
 Warner Bros. Likes Facebook Rentals. http://online.wsj.com/article/
 July 2011, Sensor Web Enablement. Available:
 M. Ortner, A. Nehorai, and A. Jeremic, “Biochemical transport modeling and bayesian source estimation in realistic environments,” Signal
Processing, IEEE Transactions on, vol. 55, no. 6, pp. 2520 –2532, june 2007.
 2004-2006, MITRA: Monitoring and intervention for the transportation of dangerous goods. http://www.mitraproject.info/.
 2009, SMARTFREIGHT project, FP7-216353. http://www.smartfreight.info//.
 F. Valente, G. Zacheo, P. Losito, and P. Camarda, “A telecommunications framework for real-time monitoring of dangerous goods transport,”
in Intelligent Transport Systems Telecommunications,(ITST),2009 9th International Conference on, October 2009, pp. 13 –18.
 Z. Yingjun, X. Shengwei, X. Peng, and W. Xinquan, “Shipping containers of dangerous goods condition monitoring system based on
wireless sensor network,” in Networked Computing (INC), 2010 6th International Conference on, may 2010, pp. 1 –3.
 I. Foster, Y. Zhao, I. Raicu, and S. Lu, “Cloud Computing and Grid Computing 360-Degree Compared,” in Grid Computing Environments
Workshop, 2008. GCE ’08, 2008, pp. 1–10.
 NIST Cloud Computing Reference Architecture
http://www.nist.gov/customcf/get pdf.cfm?pub id=909505 December 2011.
 F. Tusa, M. Paone, M. Villari, and A. Puliafito., “CLEVER: A CLoud-Enabled Virtual EnviRonment,” in 15th IEEE Symposium on
Computers and CommunicationsS Computing and Communications, 2010. ISCC ’10. Riccione, June 2010.
 S. Pandey, W. Voorsluys, S. Niu, A. Khandoker, and R. Buyya, “An autonomic cloud environment for hosting ecg data analysis services,”
Future Generation Computer Systems, vol. 55, no. 6, June 2011.
 S. Alam, M. Chowdhury, and J. Noll, “Senaas: An event-driven sensor virtualization approach for internet of things cloud,” in Networked
Embedded Systems for Enterprise Applications (NESEA), 2010 IEEE International Conference on, nov. 2010, pp. 1 –6.
 V. Rajesh, J. Gnanasekar, R. Ponmagal, and P. Anbalagan, “Integration of wireless sensor network with cloud,” in Recent Trends in
Information, Telecommunication and Computing (ITC), 2010 International Conference on, march 2010, pp. 321 –323.
 S. Rusitschka, K. Eger, and C. Gerdes, “Smart grid data cloud: A model for utilizing cloud computing in the smart grid domain,” in Smart
Grid Communications (SmartGridComm), 2010 First IEEE International Conference on, oct. 2010, pp. 483 –488.
 K. Egami, S. Matsumoto, and M. Nakamura, “Ubiquitous cloud: Managing service resources for adaptive ubiquitous computing,” in
Pervasive Computing and Communications Workshops (PERCOM Workshops), 2011 IEEE International Conference on, march 2011, pp.
 M. Yuriyama and T. Kushida, “Sensor-cloud infrastructure - physical sensor management with virtualized sensors on cloud computing,” in
Network-Based Information Systems (NBiS), 2010 13th International Conference on, sept. 2010, pp. 1 –8.
 The Extensible Messaging and Presence Protocol (XMPP) protocol:
 Ejabberd, the Erlang Jabber/XMPP daemon, http://www.ejabberd.im/ December 2011.
 Sedna, Native XML Database System:
http://modis.ispras.ru/sedna/ December 2011.
 The Apache Cassandra Project develops a highly scalable second-generation distributed database
 A. Kerrouche, J. Leighton, W. Boyle, Y. Gebremichael, T. Sun, K. Grattan, and B. Taljsten, “Strain measurement on a rail bridge loaded
to failure using a fiber bragg grating-based distributed sensor system,” Sensors Journal, IEEE, vol. 8, no. 12, pp. 2059 –2065, dec. 2008.
 Q. Li, T. Zhang, and Y. Yu, “Using cloud computing to process intensive floating car data for urban traffic surveillance,” Int. J. Geogr.
Inf. Sci., vol. 25, pp. 1303–1322, August 2011. [Online]. Available: http://dx.doi.org/10.1080/13658816.2011.577746
 N. Sahli, N. Jabeur, and M. Badra, “Agent-based approach to plan sensors relocation in a virtual geographic environment,” in New
Technologies, Mobility and Security (NTMS), 2011 4th IFIP International Conference on, feb. 2011, pp. 1 –5.
 C.-T. Yang, L.-T. Chen, W.-L. Chou, and K.-C. Wang, “Implementation of a medical image file accessing system on cloud computing,” in
Computational Science and Engineering (CSE), 2010 IEEE 13th International Conference on, dec. 2010, pp. 321 –326.
 J. Wang, B. Huang, A. Huang, and M. D. Goldberg, “Parallel computation of the weather research and forecast (wrf) wdm5 cloud
microphysics on a many-core gpu,” in Parallel and Distributed Systems (ICPADS), 2011 IEEE 17th International Conference on, dec.
2011, pp. 1032 –1037.
 M. Saini, W. Xiangyu, P. Atrey, and M. Kankanhalli, “Dynamic workload assignment in video surveillance systems,” in Multimedia and
Expo (ICME), 2011 IEEE International Conference on, july 2011, pp. 1 –6.
 C. Reed, M. Botts, J. Davidson, and G. Percivall, “OGC Sensor Web Enablement: Overview and High Level Architecture,” IEEE Autotestcon,
pp. 372–380, 2007.
 A. Celesti, F. Tusa, M. Villari, and A. Puliafito, “How to Enhance Cloud Architectures to Enable Cross-Federation,” in IEEE 3rd International
Conference on Cloud Computing (CLOUD’10), Miami, FL, 5-10 July 2010, pp. 337 –345.
 A. Dunkels, B. Grnvall, and T. Voigt, “Contiki - a lightweight and flexible operating system for tiny networked sensors,” in Proceedings
of the 29th Annual IEEE International Conference on Local Computer Networks (LCN ’04), 2004.