NDLI: Flow Based Routing for Irregular Traffic using Reinforcement Learning Approach in Dynamic Networks

Content Provider	IEEE Xplore Digital Library
Author	Mellouk, A. Hoceini, S. Larynouna, S.
Copyright Year	2006
Description	Author affiliation: University of Paris XII, France (Mellouk, A.)
Abstract	Routing is a relevant issue for maintaining good performance and successfully operating in a network. We focused in this paper on neuro-dynamic programming to construct dynamic state-dependent routing policies which offer several advantages, including a stochastic modelization of the environment, learning and evaluation are assumed to happen continually, multi-paths routing and minimizing state overhead. This paper describe an adaptive algorithm for high speed irregular packet routing using reinforcement learning called N Q-routing Optimal Shortest Paths (NQOSP). In contrast with other algorithms that are also based on Reinforcement Learning methods, NQOSP is based on a multi-paths routing technique combined with the Q-Routing algorithm. In this case, the exploration space is limited to N-Optimal non loop paths in term of hops number (number of routers in a path) leading to a substantial reduction of convergence time. We propose here a framework to describe our algorithm and focus to improve scalability, robustness of our approach. We also integrate a module to compute dynamically a probability in order to better distribute traffic on best paths. The performance of NQOSP is evaluated experimentally with OPNET simulator for different levels of traffic’s load and compared to standard shortest path and Q-routing algorithms on large interconnected network. Our approach prove superior to a classical algorithms and is able to route efficiently in large networks even when critical aspects, such as the link broken network, are allowed to vary dynamically.
Starting Page	519
Ending Page	525
File Size	507859
Page Count	7
File Format	PDF
ISBN	0769525881
ISSN	15301346
DOI	10.1109/ISCC.2006.78
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-26
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Routing Telecommunication traffic Learning Traffic control Dynamic programming Space exploration Stochastic processes Adaptive algorithm Convergence Scalability
Content Type	Text
Resource Type	Article
Subject	Signal Processing Mathematics Computer Networks and Communications Computer Science Applications Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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