Paper Details

Communicating Process Architectures (CPA)
 Title: Formal Analysis of Video Encoding Application within Map/Reduce
 Conference: Communicating Process Architectures 2017
 Authors: M. Carmen Ruiza, Diego Pérez Leándreza, Damas Gruskab
(a) Universidad de Castilla-La Mancha
(b) Institute of Informatics, Comenius University
 Abstract: Cloud computing is the infrastructure of choice for compute and data intensive systems providing flexible number of resources for software applications: that is, the processing capacity assigned to an application can be adapted to its needs. Nevertheless, in a cloud pay–per–use model, the number of demanded resources must be taken into account in order to minimise the costs. Our main goal is to reason about a cloud-aware application’s resource usage by means of the Timed Process Algebra BTC and study the trade–offs between an application’s response time and resource usage. On the other hand, video encoders are software applications that need a lot of resources and work on files of considerable size, therefore it seems reasonable to try to take advantage of the capacity offered by cloud computing to accelerate the coding process. The H.264 standard is the most widely–scrambled encoding solution, although other standards are being developed and tested to be the latter’s successors, such as H.265 or HEVC. In this paper, the video encoder H.265 will be adapted following the MAP/REDUCE paradigm in order to be able to be executed in Hadoop. Then, its algebraic formalization will be developed by BTC and validated on a real private cloud environment. Finally, we will carry out a performance evaluation using the BAL tool. 
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