Decentralized On-line Task Reallocation on Parallel Computing Architectures with Safety-Critical Applications

TL;DR

This paper introduces a decentralized algorithm for allocating computational resources in parallel architectures to ensure the reliable execution of safety-critical applications, even in the presence of faults, by formulating the problem as an Integer Linear Program.

Contribution

It proposes a novel decentralized allocation method using redundancy and graph representations, improving system reliability for safety-critical tasks.

Findings

Decentralized approach maintains system operation despite component failures.

Experimental results on a multi-core architecture demonstrate effectiveness.

The method guarantees safety-critical application execution under fault conditions.

Abstract

This work presents a decentralized allocation algorithm of safety-critical application on parallel computing architectures, where individual Computational Units can be affected by faults. The described method consists in 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 the 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. Experimental reproduction of a multi-core architecture 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 component fails.