Research on intelligent service scheduling model based on service level optimization

DOI

10.2991/itms-15.2015.418How to use a DOI?

Keywords

service scheduling; mesh refinement; node searching; transmission path

Abstract

Parallel services efficiently mining frequent itemsets is the core issue of dynamic service scheduling. For the feature that service nodes split the task into reorganization service under the data transmission environment, how to arrange the services sequence of matched nodes in accordance with specific calculation sequence to ensure the best computing and communications performance and to avoid explosion in the service delivery process is a puzzle. Through in-depth study of Apriori algorithm, a mining algorithm based on Partial Depth Priority (PDP) was proposed. The algorithm has a variety of features like various service nodes distributed in the AOV network to meet the characteristics of the DAG chart, short services communication time, dynamic allocation of service priorities. Experiments prove that: the model by studying the Apriori algorithm proposed "preferential attachment-merge pruning algorithm for mining" partial depth based on MapReduce, using the "density grid attunements connected region algorithm" deep into the MapReduce technology, so as to better complete the service node partition and data merge.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - X Cheng
AU  - W.H. Li
PY  - 2015/11
DA  - 2015/11
TI  - Research on intelligent service scheduling model based on service level optimization
BT  - Proceedings of the 2015 International Conference on Industrial Technology and Management Science
PB  - Atlantis Press
SP  - 1717
EP  - 1720
SN  - 2352-538X
UR  - https://doi.org/10.2991/itms-15.2015.418
DO  - 10.2991/itms-15.2015.418
ID  - Cheng2015/11
ER  -