Packet Loss in Real-Time Services: Markovian Models Generating QoE Impairments

Abstract

Abstract-Real-time Internet services are gaining in popularity due to rapid provisioning of broadband access technologies. Delivery of high Quality of Experience (QoE) is important for consumer acceptance of multimedia applications.IP packet level errors affect QoE and the resulting quality degradations have to be taken into account in network operation. We derive the second order statistics of the number of packet losses in finite Markov models over several relevant time scales and adapt them to loss processes visible in wired and wireless transmission channels.Higher order Markov chains offer a large set of parameters to be exploited by complex fitting procedures. We experience that the 2-state Gilbert-Elliott model already captures a wide range of observed loss pattern appropriately and discuss how such models can be used to examine the quality degradations caused by packet losses.

IPTV quality assessment system

“…Taking into account that packet losses occur in the Internet in a bursty manner, due to buffer overflows or router updates or disconnections, a common model used to characterize the behavior of a bursty channel is the Gilbert-Elliott 2-state Markov approach [27] [28], based on a discrete two-state model with at first a good (G) and secondly a bad (B) state with different loss rates and transition probabilities from states. It can also be used a 4-state Markov model [29] with two good and bad states to generate a hypergeometrical distribution of the duration of good and bad phases [30]. Both the bad and the good states represent the dependency between consecutively lost or found packets.…”

Technologies and Methodologies Enabling Reliable Real-Time Wireless Automation

“…and the mean packet drop is (Hohlfeld et al, 2008) Based on the measurements performed in the industrial hall, Gilbert-Elliott packet drop models are identified from the data. The models are implemented to the ns-2 network simulator and they are later used in simulations to evaluate the effect of the radio environment to the control system performance.…”

“…The models are implemented to the ns-2 network simulator and they are later used in simulations to evaluate the effect of the radio environment to the control system performance. The model identification is a Hidden Markov Model fitting problem (Hohlfeld et al, 2008), where the observations, in this case the packet drops, are available and the underlying states and emission probabilities are estimated. The data from all the links are individually fitted to separate G-E models using the Baum-Welch algorithm (Baum et al, 1970).…”

To Transmit Now or Not to Transmit Now

“…For example, wireless and power line communication quality are influenced by path loss, fading, interference, switching of the power grid, activation of electrical equipment, etc [9]- [12]. Although message loss is common in wireless and power line networks, it actually exists everywhere [13], [14]. Due to the random occurrences of such inevitable phenomena, messages losses typically come and go over time.…”