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A Mobile Ad hoc Network Q-Routing Algorithm: Self-Aware Approach

by Amal Alharbi, Abdullah Al-Dhalaan, Mznah Al-Rodhaan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 127 - Number 7
Year of Publication: 2015
Authors: Amal Alharbi, Abdullah Al-Dhalaan, Mznah Al-Rodhaan
10.5120/ijca2015902118

Amal Alharbi, Abdullah Al-Dhalaan, Mznah Al-Rodhaan . A Mobile Ad hoc Network Q-Routing Algorithm: Self-Aware Approach. International Journal of Computer Applications. 127, 7 ( October 2015), 1-6. DOI=10.5120/ijca2015902118

@article{ 10.5120/ijca2015902118,
author = { Amal Alharbi, Abdullah Al-Dhalaan, Mznah Al-Rodhaan },
title = { A Mobile Ad hoc Network Q-Routing Algorithm: Self-Aware Approach },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 127 },
number = { 7 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume127/number7/22738-2015902118/ },
doi = { 10.5120/ijca2015902118 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:19:13.544124+05:30
%A Amal Alharbi
%A Abdullah Al-Dhalaan
%A Mznah Al-Rodhaan
%T A Mobile Ad hoc Network Q-Routing Algorithm: Self-Aware Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 127
%N 7
%P 1-6
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper proposes a new adaptive Mobile Ad hoc Networks (MANET) routing algorithm to find and maintain paths which provide Qulaity of Service (QoS) for network traffic using a low-complexity bio-inspired learning paradigm. MANETS are highly dynamic, and thus providing QoS routing is considered a challenging, complex domain. Classical routing approaches cannot achieve high performance. Thus, it is necessary for nodes to be self-aware i.e. able to discover neighbours, links, and paths when needed. This proposal combines the self-aware capabilities in CPN with a Q-learning inspired path selection mechanism. The research defines a Q-routing reward function as a combination of high stability and low delay path criteria to discover long-lived routes without disrupting the overall delay. The algorithm uses Acknowledgment-based feedback to update link quality values in order to make routing decisions which adapt on line to network changes allowing nodes to learn efficient routing policies. Simulation Results show how the reward function handles the network changing topology to select paths that improve QoS delivered.

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Index Terms

Computer Science
Information Sciences

Keywords

Cognitive Packet Network (CPN) Q-Routing Self-Aware Networks (SAN).

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