A two-step optimization technique for functions placement, partitioning, and priority assignment in distributed systems

  • Authors:
  • Asma Mehiaoui;Ernest Wozniak;Sara Tucci-Piergiovanni;Chokri Mraidha;Marco Di Natale;Haibo Zeng;Jean-Philippe Babau;Laurent Lemarchand;Sébastien Gerard

  • Affiliations:
  • cea-List DILS, Gif-sur-yvette, France;cea-List DILS, Gif-sur-yvette, France;cea-List DILS, Gif-sur-yvette, France;cea-List DILS, Gif-sur-yvette, France;Scuola Superiore Sant' Anna, Pisa, Italy;McGill university, Montreal, Canada;University of Brest, Brest, France;University of Brest, Brest, France;cea-List DILS, Gif-sur-yvette, France

  • Venue:
  • Proceedings of the 14th ACM SIGPLAN/SIGBED conference on Languages, compilers and tools for embedded systems
  • Year:
  • 2013

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Abstract

Modern development methodologies from the industry and the academia for complex real-time systems define a stage in which application functions are deployed onto an execution platform. The deployment consists of the placement of functions on a distributed network of nodes, the partitioning of functions in tasks and the scheduling of tasks and messages. None of the existing optimization techniques deal with the three stages of the deployment problem at the same time. In this paper, we present a staged approach towards the efficient deployment of real-time functions based on genetic algorithms and mixed integer linear programming techniques. Application to case studies shows the applicability of the method to industry-size systems and the quality of the obtained solutions when compared to the true optimum for small size examples.