Enhancing QOS/QOE in MANETs using OLSR Protocol
Hind Ziani1, Nourddine Enneya2
1Hind Ziani*, Informatics, Systems and Optimization Laboratory, Faculty of Sciences, University of Ibn Tofail, BP 133, Kenitra, Morocco.
2Nourddine Enneya,. Informatics, Systems and Optimization Laboratory, Faculty of Sciences, University of Ibn Tofail, BP, Kenitra, Morocco.
Manuscript received on September 12, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 347-354 | Volume-8 Issue-12, October 2019. | Retrieval Number: L32491081219/2019©BEIESP | DOI: 10.35940/ijitee.L3249.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Video streaming over Mobile Ad-hoc Networks (MANETs) has been on the fore as one of the most chiefly solicited web services. Within this context, the enhancement of the Quality of Experience (QoE) on such platforms, whose signature characteristic is the real-time fluctuation of their Mobile Nodes (MNs), remains a high-stakes challenge for highfidelity transmission via the extant MANET routing protocols. Indeed, the free mobility of MNs (i.e. their real-time physical reallocation, viz. intra-network movement), renders network topology often subject to unpredictable fluctuations. It is this margin of relative unpredictability which lends itself to such instances where QoE, as perceived by the Customer/User, may be subject to varying degrees of depreciation.In this perspective, our contribution in this paper aims to optimize the MANETs’ mobility system, through the re-adaptation of some extant MANET routing protocols, so as to afford safer routing courses (lower mobility thresholds equate to lower chances of noise and/or data corruption/loss); all for the capital purpose of improving subjective quality (i.e. the anticipated end-user’s personal assessment of the service).For the implementation of our MANET network, our two-fold choice consisted of the NS2 version 2.9 (a powerful platform with highly reliable protocol support), supplemented by the Evalvid Framework (a fieldproven tool according to many expert ratings, ideal for close monitoring of QoE metrics).We have considered various video transmission scenarios through the OLSR protocol, one of the most well-known and reliable proactive MANET routing protocols .As for QoE prediction, we expect the mean opinion scores (MOS) to provide a metric template for a rough estimation of the end-users’ anticipated appraisal .The results are to demonstrate, as we shall see, that the modified heuristic algorithm of OLSR, leaning on the underlying criterion of mobility, can lead to a significant performance boost in MANETs and, by the same token, to higher returns of QoS and QoE.
Keywords: Ad-hoc Networks, MANET Routing Protocols, QoE, QoS, Video Transmission, Mobility, Mobility Measure.
Scope of the Article: Network Management, Reliability and QoS