Modeling performance evaluation of reinforcement learning based routing algorithm for scalable Non-cooperative Ad-hoc environment

Shrirang Ambaji Kulkarni; G. Raghavendra Rao

doi:10.1007/978-3-642-18440-6_34

Modeling performance evaluation of reinforcement learning based routing algorithm for scalable Non-cooperative Ad-hoc environment

Shrirang Ambaji Kulkarni, G. Raghavendra Rao

School of Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Scalable performance analysis of routing protocols for ad-hoc network reveals the hidden problems of routing protocols in terms of performances. Wireless nodes in ad-hoc networks may exhibit non-cooperation because of limited resources or security concerns. In this paper we model a non-cooperative scenario and evaluate the performance of a reinforcement learning based routing algorithm and compare it with ad-hoc on-demand distance vector a de facto routing standard in ad-hoc networks. Mobility models play an important role in ad-hoc network protocol simulation. In our paper we consider a realistic optimized group mobility model to aid the performance of the reinforcement learning based routing algorithm under scalable non-cooperative conditions.

Original language	English
Title of host publication	Advances in Computing, Communication and Control - International Conference, ICAC3 2011, Proceedings
Pages	269-274
Number of pages	6
DOIs	https://doi.org/10.1007/978-3-642-18440-6_34
Publication status	Published - 2011
Event	2nd International Conference on Advances in Computing, Communication and Control, ICAC3 2011 - Mumbai, India Duration: 28-01-2011 → 29-01-2011

Publication series

Name	Communications in Computer and Information Science
Volume	125 CCIS
ISSN (Print)	1865-0929

Conference

Conference	2nd International Conference on Advances in Computing, Communication and Control, ICAC3 2011
Country/Territory	India
City	Mumbai
Period	28-01-11 → 29-01-11

All Science Journal Classification (ASJC) codes

General Computer Science
General Mathematics

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10.1007/978-3-642-18440-6_34

Cite this

Kulkarni, S. A., & Raghavendra Rao, G. (2011). Modeling performance evaluation of reinforcement learning based routing algorithm for scalable Non-cooperative Ad-hoc environment. In Advances in Computing, Communication and Control - International Conference, ICAC3 2011, Proceedings (pp. 269-274). (Communications in Computer and Information Science; Vol. 125 CCIS). https://doi.org/10.1007/978-3-642-18440-6_34

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title = "Modeling performance evaluation of reinforcement learning based routing algorithm for scalable Non-cooperative Ad-hoc environment",

abstract = "Scalable performance analysis of routing protocols for ad-hoc network reveals the hidden problems of routing protocols in terms of performances. Wireless nodes in ad-hoc networks may exhibit non-cooperation because of limited resources or security concerns. In this paper we model a non-cooperative scenario and evaluate the performance of a reinforcement learning based routing algorithm and compare it with ad-hoc on-demand distance vector a de facto routing standard in ad-hoc networks. Mobility models play an important role in ad-hoc network protocol simulation. In our paper we consider a realistic optimized group mobility model to aid the performance of the reinforcement learning based routing algorithm under scalable non-cooperative conditions.",

author = "Kulkarni, \{Shrirang Ambaji\} and \{Raghavendra Rao\}, G.",

year = "2011",

doi = "10.1007/978-3-642-18440-6\_34",

language = "English",

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series = "Communications in Computer and Information Science",

pages = "269--274",

booktitle = "Advances in Computing, Communication and Control - International Conference, ICAC3 2011, Proceedings",

note = "2nd International Conference on Advances in Computing, Communication and Control, ICAC3 2011 ; Conference date: 28-01-2011 Through 29-01-2011",

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Kulkarni, SA & Raghavendra Rao, G 2011, Modeling performance evaluation of reinforcement learning based routing algorithm for scalable Non-cooperative Ad-hoc environment. in Advances in Computing, Communication and Control - International Conference, ICAC3 2011, Proceedings. Communications in Computer and Information Science, vol. 125 CCIS, pp. 269-274, 2nd International Conference on Advances in Computing, Communication and Control, ICAC3 2011, Mumbai, India, 28-01-11. https://doi.org/10.1007/978-3-642-18440-6_34

Modeling performance evaluation of reinforcement learning based routing algorithm for scalable Non-cooperative Ad-hoc environment. / Kulkarni, Shrirang Ambaji; Raghavendra Rao, G.
Advances in Computing, Communication and Control - International Conference, ICAC3 2011, Proceedings. 2011. p. 269-274 (Communications in Computer and Information Science; Vol. 125 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Scalable performance analysis of routing protocols for ad-hoc network reveals the hidden problems of routing protocols in terms of performances. Wireless nodes in ad-hoc networks may exhibit non-cooperation because of limited resources or security concerns. In this paper we model a non-cooperative scenario and evaluate the performance of a reinforcement learning based routing algorithm and compare it with ad-hoc on-demand distance vector a de facto routing standard in ad-hoc networks. Mobility models play an important role in ad-hoc network protocol simulation. In our paper we consider a realistic optimized group mobility model to aid the performance of the reinforcement learning based routing algorithm under scalable non-cooperative conditions.

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SN - 9783642184390

T3 - Communications in Computer and Information Science

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Kulkarni SA, Raghavendra Rao G. Modeling performance evaluation of reinforcement learning based routing algorithm for scalable Non-cooperative Ad-hoc environment. In Advances in Computing, Communication and Control - International Conference, ICAC3 2011, Proceedings. 2011. p. 269-274. (Communications in Computer and Information Science). doi: 10.1007/978-3-642-18440-6_34

Modeling performance evaluation of reinforcement learning based routing algorithm for scalable Non-cooperative Ad-hoc environment

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