An approach to optimization of fault tolerant architectures using HiP-HOPS

Adachi, Masakazu; Papadopoulos, Yiannis; Sharvia, Septavera; Parker, David; Tohdo, Tetsuya

Abstract

New processes for the design of dependable systems must address both cost and dependability concerns. They should also maximize the potential for automation to address the problem of increasing technological complexity and the potentially immense design spaces that need to be explored. In this paper we show a design process that integrates system modelling, automated dependability analysis and evolutionary optimization techniques to achieve the optimization of designs with respect to dependability and cost from the early stages. Computerized support is provided for difficult aspects of fault tolerant design, such as decision making on the type and location of fault detection and fault tolerant strategies. The process is supported by HiP-HOPS, a scalable automated dependability analysis and optimization tool. The process was applied to a Pre-collision system for vehicles at an early stage of its design. The study shows that HiP-HOPS can overcome the limitations of earlier work based on Reliability Block Diagrams by enabling dependability analysis and optimization of architectures that may have a network topology and exhibit multiple failure modes.

Citation

Adachi, M., Papadopoulos, Y., Sharvia, S., Parker, D., & Tohdo, T. (2011). An approach to optimization of fault tolerant architectures using HiP-HOPS. Software: Practice and Experience, 41(11), 1303-1327. https://doi.org/10.1002/spe.1044

• Journal Article Type: Article
• Acceptance Date: Nov 4, 2010
• Online Publication Date: Jan 24, 2011
• Publication Date: 2011-10
• Deposit Date: Nov 13, 2014
• Journal: Software-Practice & Experience
• Print ISSN: 0038-0644
• Electronic ISSN: 1097-024X
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 41
• Issue: 11
• Pages: 1303-1327
• DOI: https://doi.org/10.1002/spe.1044
• Keywords: Fault tolerance; Active safety; Multi-objective optimization; Genetic algorithms
• Public URL: https://hull-repository.worktribe.com/output/463688