Abstract
We present a centralized and a distributed algorithm for scheduling multi-task agents in a distributed system with the objective of minimizing the overall application completion time. Each agent consists of multiple tasks that can be executed on multiple machines which correspond to resources. The machine speeds and link transfer rates are heterogeneous. Our centralized algorithm has an upper bound on the overall completion time and is used as a module in the distributed algorithm. Extensive simulations show promising results of the algorithms, especially for scheduling communication-intensive multi-task agents.
This work bas been supported in part by Department of Defense contract MURI F49620-97-1-0382 and DARPA contract F30602-98-2-0107, ONR grant N00014-01- 1-0675, NSF CAREER award IRI-9624286, NSF award IIS 9912193, Honda corporation, and the Sloan foundation; we are grateful for this support. We are also grateful to Bob Gray and Susan McGrath for their efforts in developing the scheduling experiments using the D’Agents system. We thank Miguel Fernandez and Santiago Aja for their implementation of the scheduling system on top of the D’Agents.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
H. El-Rewini and T.G. Lewis. Scheduling parallel program tasks onto arbitrary target machines. Journal of Parallel and Distributed Computing, 9:138–153, 1990.
C. Hanen and A. Munier. An approximation algorithm for scheduling dependent tasks on m processors with small communication delays. 1995.
M. Iverson and F. Ozguner. Parallelizing existing applications in a distributed heterogeneous environments. In Proc. of HCW, pages 93–100, 1995.
J.J. Hwang and Y.C. Chow. Scheduling precedence graphs in system with interprocessor communication times. SIAM Journal on Computing, 18(2):244–257, 1989.
Y. Kwok and I. Ahmad. Benchmarking the task graph scheduling algorithms. In Proceedigns of the first merged international parallel processing symposium and symposium on parallel and distributed processing, pages 531–537, 1998.
R.H. Mohring, M.W. Schaffter, and A.S. Schulz. Scheduling jobs with communication delays: using infeasible solutions for approximation. In Algorithms-ESA’96, pages 76–90, Barcelona, Spain, 1996.
A. Munier. Approximation algorithms for scheduling trees with general communication delays. Parallel Computing, 25(1):41–48, 1999.
C.H. Papadimitriou and M. Yannakakis. Towards an architecture-independent analysis of parallel algorithms. SIAM Journal on Computing, 19(2):322–328, 1990.
R. Gray, G. Cybenko, D. Kotz, R. Peterson, and D. Rus. D’Agents: Applications and Performance of a Mobile-Agent System.submitted to Software Practice and Experience,2000.
G.C. Sih and E.A. Lee. A compile-time scheduling heuristic for interconnectionconstrained heterogeneous processor architectures. IEEE Trans. Parallel and Distributed Sys., 4:175–186, 1993.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Xie, R., Rus, D., Stein, C. (2001). Scheduling Multi-task Agents. In: Picco, G.P. (eds) Mobile Agents. MA 2001. Lecture Notes in Computer Science, vol 2240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45647-3_18
Download citation
DOI: https://doi.org/10.1007/3-540-45647-3_18
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42952-4
Online ISBN: 978-3-540-45647-6
eBook Packages: Springer Book Archive