Paper Info
Title
Workload Prediction and Weighted Rule-Based Task Scheduling for Face Certification System on Distributed Parallel Computing.
Abstract
This paper presents a workload prediction and weighted rule-based task scheduling for face certification on distributed parallel computing. To compose a large-scale certification system. such as a criminal surveillance system for a public security, the system requires an enormous processing power. Thus a grid and distributed parallel computing is an essential approach for a large scale certification system. However his kind of approach is generally comprised of heterogeneous resources. And differential characteristics of each resource have influence on a performance of system. Therefore, an efficient task distribution and scheduling is necessary to improve a performance of system. There are various kinds of scheduling for task distribution. However existing methods cannot provide a suitable task distribution for a face certification system. Therefore, this paper proposes a task scheduling which includes a queue management policy with workload-prediction and weighted rule-based resource selection. The proposed method predicts the volume of certification task for a task queue management policy and selects the suitable certification server using performance weighted rules. Simulation result shows that the proposed method has better performance than other scheduling methods.
Year
DOI
Venue
2011
10.1007/978-3-642-27180-9_42
Communications in Computer and Information Science
Keywords
DocType
Volume
Task Scheduling,Workload Prediction,Rule-based System,Distributed Parallel Computing
Conference
261
ISSN
Citations 
PageRank 
1865-0929
1
0.36
References 
Authors
6
2
Name
Order
Citations
PageRank
Tae Young Kim110.69
Jong Sik Lee27418.95