QoE Analysis of Media Streaming in Wireless Data Networks

Abstract

Abstract. The purpose of this paper is to model quality of experience (QoE) of media streaming service in a shared fast-fading channel. In this context, the arrival and the service processes of the playout buffer do not have the same job size. We present an analytical framework based on Takács Ballot theorem to compute the probability of buffer starvation and the distribution of playback intervals. We model the arrival processes of Proportional Fair and Round Robin schedulers, and feed them into this framework to study the impact of prefetching on the starvation behavior. Our simulations match the developed model very well if the base station knows the playback rate and the channel gain. Furthermore, we make an important observation that QoE metrics predicted by users are very sensitive to the measurement error of arrival process.

Advances in vehicular ad-hoc networks (VANETs): Challenges and road-map for future development

“…Additionally, video transmission is bit loss tolerant. Hence, the loss of one packet may not affect the experience of users [80]. Therefore, video communication has potential to be of high benefit for traffic management as well as for providing value-added entertainment [81] and advertising services [82].…”

On Dynamic Video Source Decision in VANETs: An On-Demand Clustering Approach

“…International Journal of Distributed Sensor Networks 5 Begin (1) for each vehicle with -ID = (2) // Determine the type of (3) if is a header demanding of -ID = , then (4) if receive a reply on of a non-member, then (5) insert corresponding information in record table (6) elseif record table of changes, then (7) broadcast new table in the cluster (8) end if (9) // Measures of a cluster header (10) elseif is a cluster member, then (11) if receive status message, then (12) rebroadcast in the cluster (13) elseif demand of video of changes, then (14) renew a replay to the header (15) end if (16) // Measures of a cluster member (17) else (18) if demands video -ID = , then (19) if receives no status message on , then (20) as a header, sponsors a new cluster for (21) broadcasts a status message of the cluster (22) elseif receives a status message on , then (23) if has the same direction with header, then (24) if Header < /2, then (25) sends a reply message to header (26) end if (27) end if (28) // Determine the condition of a cluster member (29) end if (30) end if ( Then it can leave the cluster by sending a special reply message with -ID = 0 and -ID = 0. The header will delete the corresponding item in the record table if it receives this kind of reply.…”

Bandwidth allocation for video delivery in wireless networks with QoE constraints for spatially random user population

“…In this paper, we develop an analytical framework to characterize the dependence of the objective QoE metrics on the network and service parameters. Following an approach similar to [9], we model the wireless transmission channel and the playback buffer by two queueing systems. The arrival rate of video segments to the playback buffer can be derived by analyzing the queueing model for the wireless transmission channel.…”

“…Such studies often focus on the playback buffer at the receiver, assuming a given or infinite media file length and certain video packet arrival rate to the receive buffer, which largely depends on the network transmission process. In [9], the authors consider both the wireless transmission buffer at the base station and the playback buffer at the end user. However, it assumes an infinite media file length and a fixed number of users with independent and identically distributed (i.i.d.)…”

“…Following a system model similar to [9], we take into account both the wireless transmission process and the playback process. Furthermore, we relax the i.i.d.…”