Objective Measurement of Speech Quality in VoIP over Wireless LAN during Handoff

Quality of Service is a very important factor to determine the quality of a VoIP call. Different subjective and objective models exist for evaluating the speech quality in VoIP. E-model is one of the objective methods of measuring the speech quality; it considers various factors like packet loss, delay and codec impairments. The calculations of Emodel are not very accurate in case of handovers – when a VoIP call moves from one wireless LAN to another. This project conducted experimental evaluation of performance of E-model during handovers and proposes a new approach to accurately calculate the speech quality of VoIP during handovers. A detailed description of the experimental setup and the comparison of the new approach with E-model is presented in this report

A network resource availability model for IEEE802.11a/b-based WLAN carrying different service types

The electronic version of this article is the complete one and can be found online at: http://jwcn.eurasipjournals.com/content/2011/1/103. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Operators of integrated wireless systems need to have knowledge of the resource availability in their different access networks to perform efficient admission control and maintain good quality of experience to users. Network availability depends on the access technology and the service types. Resource availability in a WLAN is complex to gather when UDP and TCP services co-exist. Previous study on IEEE802.11a/b derived the achievable throughput under the assumption of inelastic and uniformly distributed traffic. Further study investigated TCP connections and derived a model to calculate the effective transmission rate of packets under the assumption of saturated traffic flows. The assumptions are too stringent; therefore, we developed a model for evaluating WLAN resource availability that tries to narrow the gap to more realistic scenarios. It provides an indication of WLAN resource availability for admitting UDP/TCP requests. This article presents the assumptions, the mathematical formulations, and the effectiveness of our model

Automatic best wireless network selection based on key performance indicators

Introducing cognitive mechanisms at the application layer may lead to the possibility of an automatic selection of the wireless network that can guarantee best perceived experience by the final user. This chapter investigates this approach based on the concept of Quality of Experience (QoE), by introducing the use of application layer parameters, namely Key Performance Indicators (KPIs). KPIs are defined for different traffic types based on experimental data. A model for an ap- plication layer cognitive engine is presented, whose goal is to identify and select, based on KPIs, the best wireless network among available ones. An experimenta- tion for the VoIP case, that foresees the use of the One-way end-to-end delay (OED) and the Mean Opinion Score (MOS) as KPIs is presented. This first implementation of the cognitive engine selects the network that, in that specific instant, offers the best QoE based on real captured data. To our knowledge, this is the first example of a cognitive engine that achieves best QoE in a context of heterogeneous wireless networks

Performance Evaluation of IPTV over WiMAX Networks Under Different Terrain Environments

Deployment Video on Demand (VoD) over the next generation (WiMAX) has become one of the intense interest subjects in the research these days, and is expected to be the main revenue generators in the near future. In this paper, the performance of Quilty of Service of video streaming (IPTV) over fixed mobile WiMax network is investigated under different terrain environments, namely Free Space, Outdoor to Indoor and Pedestrian. OPNET is used to investigate the performance of VoD over WiMAX. Our findings analyzing different network statistics such as packet lost, path loss, delay, network throughput.Comment: arXiv admin note: substantial text overlap with arXiv:1302.1409, and substantial text overlap with other internet sources by other author