By Topic

Distributed Scheduling of Parallel I/O in the Presence of Data Replication

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jan-Jan Wu ; Inst. of Inf. Sci., Acad. Sinica, Taipei, Taiwan ; Pangfeng Liu

This paper studies distributed scheduling of parallel I/O data transfers on systems that provide data replication. In our previous work, we proposed a centralized algorithm for solving this problem in systems where data transfer information is centrally available. This algorithm finds the optimal scheduling by constructing augmenting paths in the data transfer bipartite graph, requiring O(nmlog n + {text{n}}^{text{2}} {text{log}}^{frac{3}{2}} n) time, with n nodes and m edges in the bipartite graph. In this paper, we investigate this scheduling problem in distributed systems where data transfer information may not be centrally available. We propose a distributed scheduling algorithm, Highest Degree Lowest Workload First (HDLWF), which approximates the augmenting path algorithm in distributed environments. HDLWF is based on a distributed, two-step scheme that determines appropriate execution order of data requests through a small number of rounds of bidding between clients and I/O servers. Our experimental results indicate that HDLWF yields schedules close to the centralized optimal solution, and in some cases within 3% of the optimal solution.

Published in:

Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International

Date of Conference:

04-08 April 2005