Jan Janssen

Assessing voice quality in packet-based telephony

Our goal is to extend recommendations ITU-T G.114 and G.131 to cover distorted phone calls transported (partly) over a packet-based network. We assume the user terminals to be optimally tuned and focus on how network parameters-delay, packet loss, jitter, and so on-influence voice quality. We then discuss how those parameters can be quantified and incorporated into a model that lets us predict the quality of any packet-based phone call.

Delay bounds for voice over IP calls transported over satellite access networks

Whether or not voice calls of traditional quality can be supported between two users connected to an IP backbone via satellite access systems depends largely on the mouth-to-ear delay, an important part of which is consumed by the satellite networks themselves. In this paper, a methodology is developed to calculate upper bounds for the latter delay component as a function of the used codec, the experienced packet loss ratio, the echo levels at both sides of the connection and the chosen voice packet size. Illustrations are provided.

Delay bounds for low-bit-rate voice transport over IP networks

The mouth-to-ear delay bounds that can be tolerated for undistorted voice are well known and standardized in the ITU-T Recommendations. In this paper, similar delay bounds are determined for voice that is transported in compressed form over an IP network. More precisely, the dependency of these bounds on the low bit rate codecs used, the amount of echo control performed and the way the IP network is accessed, is investigated in detail.

Policing aggregates of voice traffic with the token bucket algorithm

Estimating correct traffic descriptors is an important issue when deploying IP telephony with quality of service guarantees. Usually, a token bucket is used to police a traffic flow. Such a policer checks (and ensures) that the traffic flow fits inside a traffic envelope. For variable bit rate (VBR) sources normally two traffic envelopes are specified: one dealing with the peak rate and one dealing with the sustainable rate with an associated burst size. These parameters have to be specified when making a reservation with either the resource reservation protocol (RSVP) in case of IntServ or may be specified in a service level specification (SLS) when using DiffServ. This paper shows how to choose the traffic descriptors for aggregate voice traffic for both constant bit rate sources and sources that use voice activity detection. Also the influence of variable packet size on the packet discard ratio (PDR) is shown. A traditional policer discards large packets more frequent than smaller ones. To alleviate this, a modification to the token bucket algorithm is proposed.

Resource allocation and management in DiffServ networks for IP telephony

This paper discusses resource allocation and management in Differentia ted Services (DiffServ) networks, particularly in the context of IP telephony. We assume that each node uses Weighted Fair Queuing (WFQ) schedulers in order to provide Quality of Service (QoS) to aggregates of traffic. All voice traffic destined for a certain output interface is aggregated into a single queue. When a voice flow traverses a node, its packets are placed in this queue; which is drained at a certain rate, determined by a weight associated with that queue. This paper shows how to set this weight such that the edge-router-to-edge-router queuing delay in the DiffServ network is statistically bounded. The nodes are modeled as M/G/1 queuing systems and a heuristic formula is used to compute a quantile of the queuing delay. This formula is compared with results derived from simulations. It is also shown how to use this result to allocate the appropriate resources in a DiffServ network and how to update and process RSVP messages at the edge of a DiffServ network in an IntServ over DiffServ scenario.

Determining the tolerable load generated by a set of packet-based phones on a multiplexing node

Abstract To determine the voice load that can be supported by a packet-based node, we study the MMBP/D/1 model. Using this load the number of phones that can be supported by that node is calculated. We investigate the case of homogeneous and heterogeneous traffic and phones with and without silence suppression, and study the impact of the link rate, the activity grade and the codec bit rate. We also compare the number of phones that can be supported by the node according to the MMBP/D/1 model with the number of phones that can be supported according to the M/D/1 model.