VoIPiggy: Implementation and evaluation of a mechanism to boost voice capacity in 802.11 WLANs

This work is at: The 31st Annual IEEE International Conference on Computer Communications (IEEE INFOCOM 2012), took place March 25-30, 2012 in Orlando, Florida, USA.Supporting voice traffic in existing WLANs results extremely inefficient, given the large overheads of the protocol operation and the need to prioritize this traffic over, e.g., bulky transfers. In this paper we propose a simple scheme to improve the efficiency of WLANs when voice traffic is present. The mechanism is based on piggybacking voice frames over the acknowledgments, which reduces both frame overheads and time spent in contentions. We evaluate its performance in a large-scale testbed consisting on 33 commercial off-the-shelf devices. The experimental results show dramatic performance improvements in both voice-only and mixed voice-and-data scenarios.The research leading to these results was funded by the EU’s Seventh Framework Programme (FP7-ICT-2009-5) under grant agreement n.257263 (FLAVIA) and by the the Spanish Ministry of Science and Innovation under grant TEC2010- 10440-E. It was supported in part by the MEDIANET Project (grant S2009/TIC-1468) from the General Directorate of Universities and Research of the Regional Government of Madrid.Publicad

Effect of Free Bandwidth on VoIP Performance in 802.11b WLAN Networks

In this paper we experimentally study the relationship between bandwidth utilization in the wireless LAN and the quality of VoIP calls transmitted over the wireless medium. Specifically we evaluate how the amount of free bandwidth decreases as the number of calls increases and how this influences transmission impairments (i.e. delay, loss and jitter) and thus degrades call quality. We show that the amount of free bandwidth is a good indicator for predicting VoIP call quality

Capacity of an IEEE 802.11b wireless LAN supporting VoIP

In this paper we evaluate the capacity of an IEEE 802.11b network carrying voice calls in a wide range of scenarios, including varying delay constraints, channel conditions and voice call quality requirements. We consider both G.711 and G.729 voice encoding schemes and a range of voice packet sizes. We first present an analytical..

Achievable bandwidth estimation for stations in multi-rate IEEE 802.11 WLAN cells

This paper analyzes the effect of multi-rate transmissions in a CSMA wireless LAN environment. Observations in a real testbed showed that bandwidth resources (in Bytes/s) are shared fairly among all stations even though transmissions carried out at lower rates capture the medium for longer periods, which drastically reduces the overall throughput. The intrinsic concept of fairness in a CSMA scheme with multiple rates is quantified by means of a new formulation which is validated through simulations and practical measurements. The algorithm presented provides the maximum achievable bandwidth that can be offered to a given IEEE 802.11 station. Having this information has evident applications in realtime multimedia transmissions over WLANs. The algorithm was also run in commercial APs as a proof of concept, after analyzing its implementation issues

Call capacity for voice over Internet Protocol on wireless mesh networks

This paper describes work in progress on call capacity optimization for voice over Internet Protocol on wireless mesh networks. In a developing country such as South Africa, evidence has shown that rural inhabitants find it difficult to afford the voice services offered by cellular networks. Voice over Internet Protocol is known for its affordability relative to cellular voice services, therefore deploying such services for rural communities will not only benefit rural inhabitants but also offer economic advantages to service providers. We are interested in the provision of voice services with rural wireless mesh networks. Unfortunately voice on mesh networks can experience packet loss and delays that cause reduction in voice quality. Transmission of small voice packets over wireless mesh networks imposes high overhead that leads to a tremendous decrease in call capacity. Therefore, we aim to study the performance of voice over 802.11 wireless mesh networks and evaluate packet aggregation mechanisms that merge small voice packets into a single large packet, in order to preserve voice quality with more calls. We will implement and evaluate packet aggregations mechanisms on a 'mesh potato' network with iterative cycles of laboratory experiments using a network simulator to collect data for performance evaluation.Telkom, Cisco, THRIPDepartment of HE and Training approved lis

Packet aggregation for voice over internet protocol on wireless mesh networks

>Magister Scientiae - MScThis thesis validates that packet aggregation is a viable technique to increase call ca-pacity for Voice over Internet Protocol over wireless mesh networks. Wireless mesh networks are attractive ways to provide voice services to rural communities. Due to the ad-hoc routing nature of mesh networks, packet loss and delay can reduce voice quality.Even on non-mesh networks, voice quality is reduced by high overhead, associated with the transmission of multiple small packets. Packet aggregation techniques are proven to increase VoIP performance and thus can be deployed in wireless mesh networks. Kernel level packet aggregation was initially implemented and tested on a small mesh network of PCs running Linux, and standard baseline vs. aggregation tests were conducted with a realistic voice tra c pro le in hop-to-hop mode. Modi cations of the kernel were then transferred to either end of a nine node 'mesh potato' network and those tests were conducted with only the end nodes modi ed to perform aggregation duties. Packet ag- gregation increased call capacity expectedly, while quality of service was maintained in both instances, and hop-to-hop aggregation outperformed the end-to-end con guration. However, implementing hop-to-hop in a scalable fashion is prohibitive, due to the extensive kernel level debugging that must be done to achieve the call capacity increase.Therefore, end-to-end call capacity increase is an acceptable compromise for eventual scalable deployment of voice over wireless mesh networks

The Voice Capacity of WiFi for Best Effort and Prioritized Traffic

Crucial to supporting voice over 802.11b is the knowledge of voice capacity (Nc) of a single Access Point. This paper provides an analytical formulation of Nc in the case where all traffic in the network is voice. Our formulation, which can apply to a range of voice codec specifications, are verified by detailed simulations. We also investigate how to deliver, within the 802.11b standard, priority service to voice in the presence of best effort background traffic. It is known that the voice capacity degrades very quickly in the presence of other traffic sources if all packets are treated as best effort. Using an experimental deployment in which all voice packets are prioritized by having their channel back-off times set to zero, we determine the rate of the best effort background traffic below which our analytical formulation of voice-only capacity remains useful

Optimum WLAN Protocol and Network Architecture Identification for VOIP Application

This research developed a novel algorithm to evaluate Voice over Internet Protocol (VoIP) metrics of different IEEE 802.11 technologies in order to identify the optimum network architecture among Basic Service Set (BSS), Extended Service Set (ESS), and the Independent Basic Service Set (IBSS). The proposed algorithm will yield the rank order of different IEEE 802.11 technologies. By selecting the optimum network architecture and technology, the best overall network performance that provides a good voice quality is guaranteed. Furthermore, it meets the acceptance threshold values for the VoIP quality metrics. This algorithm was applied to various room sizes ranging from 2x3m to 10x14m and the number of nodes ranged from one to forty. The spatial distributions considered were circular, uniform, and random. The Quality of Service (QoS) metrics used were delay, jitter, throughput and packet loss