Open AccessANALYTICALLY MODELING UNRELIABLE PARALLEL PROCESSING SYSTEMS WITH GENERAL TASK TIME DISTRIBUTIONS
Author(s) -
Pierre M. Fiorini,
Robert W. Rowan
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.4.3.368
Subject(s) - dependability , computer science , task (project management) , distributed computing , class (philosophy) , event (particle physics) , artificial intelligence , physics , software engineering , management , quantum mechanics , economics
For many computing systems, failure is rare enough that it can be ignored. In other systems, failure is so common that the recovery procedure can have a significant impact on the performance of the system. In this paper, assuming a computing system is unreliable, we discuss how heavy-tail or power-tail job completion time distributions can appear in an otherwise well-behaved task stream. This is an important consideration since it is known that powertails can lead to unstable systems. We then demonstrate how to obtain performance and dependability measures for a class of computing systems comprised of P unreliable processors and a finite number of tasks, N, given different recovery policies. Finally, we discuss the effects of checkpointing on the job completion time distribution.