Decentralized Task Reallocation on Parallel Computing Architectures Targeting an Avionics Application

Thanakorn Khamvilai (), Louis Sutter (), Philippe Baufreton (), François Neumann () and Eric Feron ()
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Thanakorn Khamvilai: Georgia Institute of Technology
Louis Sutter: Dassault Aviation
Philippe Baufreton: Safran Electronics and Defense
François Neumann: Safran Electronics and Defense
Eric Feron: King Abdullah University of Science and Technology

Journal of Optimization Theory and Applications, 2021, vol. 191, issue 2, No 22, 874-898

Abstract: Abstract This work presents an online decentralized allocation algorithm of a safety-critical application on parallel computing architectures, where individual Computational Units can be affected by faults. The described method includes representing the architecture by an abstract graph where each node represents a Computational Unit. Applications are also represented by the graph of Computational Units they require for execution. The problem is then to decide how to allocate Computational Units to applications to guarantee execution of a safety-critical application. The problem is formulated as an optimization problem with the form of an Integer Linear Program. A state-of-the-art solver is then used to solve the problem. Decentralizing the allocation process is achieved through redundancy of the allocator executed on the architecture. No centralized element decides on the allocation of the entire architecture, thus improving the reliability of the system. Inspired by multi-core architectures in avionics systems, an experimental illustration of the work is also presented. It is used to demonstrate the capabilities of the proposed allocation process to maintain the operation of a physical system in a decentralized way while individual components fail.

Keywords: Parallel computing; Distributed computing; Reconfigurable; Safety-critical; Fault tolerance; Avionics; Integer linear programming; 90B10; 90C09; 90C90; 93A14; 93B52; 94C15 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10957-021-01862-7

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