Toward Maximizing the Quality of Results of Dependent Tasks Computed Unreliably

Authors:
Li Gao;Grzegorz Malewicz
Affiliations:
Department of Computer Science, University of Alabama, Tuscaloosa, AL 35487, USA;Department of Engineering, Google, Inc., Mountain View, CA 94043, USA
Venue:
Theory of Computing Systems
Year:
2007

Citing 0
Cited 5

Integrity and its applications

ACM-SE 45 Proceedings of the 45th annual southeast regional conference
Advances in IC-Scheduling Theory: Scheduling Expansive and Reductive Dags and Scheduling Dags via Duality

IEEE Transactions on Parallel and Distributed Systems
Extending IC-scheduling via the Sweep Algorithm

Journal of Parallel and Distributed Computing
Robust network supercomputing with malicious processes

DISC'06 Proceedings of the 20th international conference on Distributed Computing
Robust network supercomputing without centralized control

OPODIS'11 Proceedings of the 15th international conference on Principles of Distributed Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper studies the problem of maximizing the number of correct results of dependent tasks computed unreliably. We consider a distributed system composed of a reliable server that coordinates the computation of a massive number of unreliable workers. Any worker computes correctly with probability p