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Real-time task reconfiguration support applied to an UAV-based surveillance system

Alecio Pedro Delazari Binotto, Edison Pignaton de Freitas, Carlos Eduardo Pereira, Andre Stork, Tony Larsson
Fraunhofer IGD, Tech. Univ. Darmstadt, Darmstadt
International Multiconference on Computer Science and Information Technology, 2008. IMCSIT 2008

@inproceedings{binotto2008real,

   title={Real-time task reconfiguration support applied to an UAV-based surveillance system},

   author={Binotto, A.P.D. and de Freitas, E.P. and Pereira, C.E. and Stork, A. and Larsson, T.},

   booktitle={Computer Science and Information Technology, 2008. IMCSIT 2008. International Multiconference on},

   pages={581–588},

   year={2008},

   organization={IEEE}

}

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Modern surveillance systems, such as those based on the use of unmanned aerial vehicles, required powerful high-performance platforms to deal with many different algorithms that make use of massive calculations. At the same time, low-cost and high-performance specific hardware (e.g., GPU, PPU) are rising and the CPUs turned to multiple cores, characterizing together an interesting and powerful heterogeneous execution platform. Therefore, reconfigurable computing is a potential paradigm for those scenarios as it can provide flexibility to explore the computational resources on heterogeneous cluster attached to a high-performance computer system platform. As the first step towards a run-time reconfigurable workload balancing framework targeting that kind of platform, application time requirements and its crosscutting behavior play an important role for task allocation decisions. This paper presents a strategy to reallocate specific tasks in a surveillance system composed by a fleet of unmanned aerial vehicles using aspect-oriented paradigms in order to address non-functional application timing constraints in the design phase. An aspect support from a framework called DERAF is used to support reconfiguration requirements and provide the resource information needed by the reconfigurable load-balancing strategy. Finally, for the case study, a special attention on radar image processing will be given.
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