Welcome to the InfoSci Platform
Dynamic Scheduling of Multi-Agent in Agent-Based Distributed Network Management

Dynamic Scheduling of Multi-Agent in Agent-Based Distributed Network Management

Luo Junzhou
Copyright: © 2007 |Pages: 18
ISBN13: 9781599041087|ISBN10: 1599041081|ISBN13 Softcover: 9781616927530|EISBN13: 9781599041100
DOI: 10.4018/978-1-59904-108-7.ch007
Cite Chapter Cite Chapter

MLA

Junzhou, Luo. "Dynamic Scheduling of Multi-Agent in Agent-Based Distributed Network Management." Architectural Design of Multi-Agent Systems: Technologies and Techniques, edited by Hong Lin, IGI Global, 2007, pp. 125-142. https://doi.org/10.4018/978-1-59904-108-7.ch007

APA

Junzhou, L. (2007). Dynamic Scheduling of Multi-Agent in Agent-Based Distributed Network Management. In H. Lin (Ed.), Architectural Design of Multi-Agent Systems: Technologies and Techniques (pp. 125-142). IGI Global. https://doi.org/10.4018/978-1-59904-108-7.ch007

Chicago

Junzhou, Luo. "Dynamic Scheduling of Multi-Agent in Agent-Based Distributed Network Management." In Architectural Design of Multi-Agent Systems: Technologies and Techniques, edited by Hong Lin, 125-142. Hershey, PA: IGI Global, 2007. https://doi.org/10.4018/978-1-59904-108-7.ch007

Export Reference

Mendeley
Favorite

Abstract

Agent technology has played an important role in distributed network management, and agent scheduling is an inevitable problem in a multi-agent system. This chapter introduces a network management scenario to support dynamic scheduling decisions. Some algorithms are proposed to decompose the whole network management task into several groups of sub-tasks. During the course of decomposition, different priorities are assigned to sub-tasks. Then, based on the priorities of these sub-tasks, a dynamic multi-agent scheduling algorithm based on dependences of sub-tasks is proposed. An experiment has been done with the decomposition algorithms, the results of which demonstrate the advantage of the algorithms. The performance test demonstrates that the competitive ratio of the dynamic scheduling algorithm is always smaller than that of the existing online scheduling algorithm, which indicates that the performance of the dynamic scheduling algorithm is better than the existing online scheduling algorithm. Finally, as an application example, the process of network stream management is presented. The authors hope that this scheduling method can give a new approach or suggestion for studying dynamic agents scheduling technology.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.