Providing Dynamic TXOP for QoS Support of Video Transmission in IEEE 802.11e WLANs

The IEEE 802.11e standard introduced by IEEE 802.11 Task Group E (TGe) enhances the Quality of Service (QoS) by means of HCF Controlled Channel Access (HCCA). The scheduler of HCCA allocates Transmission Opportunities (TXOPs) to QoS-enabled Station (QSTA) based on their TS Specifications (TSPECs) negotiated at the traffic setup time so that it is only efficient for Constant Bit Rate (CBR) applications. However, Variable Bit Rate (VBR) traffics are not efficiently supported as they exhibit nondeterministic profile during the time. In this paper, we present a dynamic TXOP assignment Scheduling Algorithm for supporting the video traffics transmission over IEEE 802.11e wireless networks. This algorithm uses a piggybacked information about the size of the subsequent video frames of the uplink traffic to assist the Hybrid Coordinator accurately assign the TXOP according to the fast changes in the VBR profile. The proposed scheduling algorithm has been evaluated using simulation with different variability level video streams. The simulation results show that the proposed algorithm reduces the delay experienced by VBR traffic streams comparable to HCCA scheduler due to the accurate assignment of the TXOP which preserve the channel time for transmission.Comment: arXiv admin note: substantial text overlap with arXiv:1602.0369

The Renegotiable Variable Bit Rate Service: Characterisation and prototyping

he traffic generated by multimedia applications presents a high degree of burstiness that can hardly be described by a static set of traffic parameters. We present a dynamic QoS negotiation scheme applied to a prototype application that provides temporized data transfer. The dynamic and efficient usage of the resources can be reached with the introduction of the renegotiable variable bit rate (RVBR) service, which is based on the renegotiation of the traffic specification. We describe and discuss the RVBR service and how it applies to resource reservation for Internet traffic with RSVP. We propose an architecture design that we evaluate by accomplishing a prototype implementation, whose performance is measured with temporized file transfer using real MPEG2 video traces. The results we obtained indicate that renegotiation is an efficient mechanism for accommodating traffic fluctuations over the burst time-scale and that the RVBR service can be easily implemented in real applications, using available technology

Measurement and application of many-to-one data flows.

Ho, Po Yee.Thesis (M.Phil.)--Chinese University of Hong Kong, 2007.Includes bibliographical references (leaves 77-81).Abstracts in English and Chinese.Acknowledgements --- p.iAbstract --- p.ii摘要 --- p.iiiChapter Chapter 1 --- Introduction --- p.1Chapter Chapter 2 --- Background and Related Work --- p.4Chapter 2.1 --- Link/Path Capacity --- p.4Chapter 2.2 --- Unutilized Bandwidth --- p.5Chapter 2.3 --- Achievable Bandwidth --- p.5Chapter Chapter 3 --- Measurement Methodology --- p.7Chapter 3.1 --- PlanetLab Measurement --- p.8Chapter 3.2 --- FTP Measurement --- p.10Chapter Chapter 4 --- Analysis of Measurement Data --- p.12Chapter 4.1 --- Per-Flow Achievable Bandwidth --- p.13Chapter 4.2 --- Inter-Flow Correlation --- p.14Chapter 4.3 --- Intra-Flow Temporal Correlation --- p.16Chapter 4.4 --- Intra-Flow Bandwidth Variation --- p.18Chapter 4.5 --- Predictability of Bandwidth Properties --- p.22Chapter 4.6 --- Long-term Flow Properties --- p.26Chapter Chapter 5 --- A Mathematical Framework --- p.28Chapter 5.1 --- Bandwidth Variations --- p.28Chapter 5.2 --- Bandwidth Predictability --- p.31Chapter 5.3 --- Sensitivity Analysis --- p.34Chapter Chapter 6 --- Predictive Buffering Algorithm --- p.41Chapter 6.1 --- Related Work --- p.43Chapter 6.2 --- System Model --- p.44Chapter 6.3 --- Prediction Algorithm for Constant Bit-Rate Videos --- p.45Chapter 6.4 --- Prediction Algorithm for Variable Bit-Rate Videos --- p.46Chapter 6.5 --- Parameter Estimation --- p.47Chapter Chapter 7 --- Performance Evaluation --- p.49Chapter 7.1 --- Trace-Driven Simulation Setup --- p.49Chapter 7.2 --- Performance over CBR Videos --- p.50Chapter 7.2.1 --- Video Playback Performance --- p.51Chapter 7.2.2 --- Buffering Time --- p.57Chapter 7.3 --- Performance over VBR Videos --- p.61Chapter 7.3.1 --- Video Playback Performance --- p.62Chapter 7.3.2 --- Buffering Time --- p.66Chapter Chapter 8 --- Future Work --- p.69Chapter 8.1 --- Playback Rate Adaptation --- p.70Chapter 8.2 --- Sender Selection Algorithm --- p.71Chapter 8.3 --- Dynamic Flow Allocation --- p.72Chapter 8.4 --- Predictive Flow Allocation --- p.73Chapter 8.5 --- Challenge in P2P Applications --- p.74Chapter Chapter 9 --- Conclusion --- p.76Bibliograph

An optimal bandwidth allocation strategy for the delivery of compressed prerecorded video

The transportation of prerecorded, compressed video data without loss of picture quality requires the network and video servers to support large fluctuations in bandwidth requirements. Fully utilizing a client-side buffer for smoothing bandwidth requirements can limit the fluctuations in bandwidth required from the underlying network and the video-on-demand servers. This paper shows that, for a fixed-size buffer constraint, the critical bandwidth allocation technique results in plans for continuous playback of stored video that have (1) the minimum number of bandwidth increases, (2) the smallest peak bandwidth requirements, and (3) the largest minimum bandwidth requirements. In addition, this paper introduces an optimal bandwidth allocation algorithm which, in addition to the three critical bandwidth allocation properties, minimizes the total number of bandwidth changes necessary for continuous playback. A comparison between the optimal bandwidth allocation algorithm and other critical bandwidth-based algorithms using 17 full-length movie videos and 3 seminar videos is also presented.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42314/1/530-5-5-297_70050297.pd

Video Smoothing of Aggregates of Streams with Bandwidth Constraints

Compressed variable bit rate (VBR) video transmission is acquiring a growing importance in the telecommunication world. High data rate variability of compressed video over multiple time scales makes an efficient bandwidth resource utilization difficult to obtain. One of the approaches developed to face this problem are smoothing techniques. Various smoothing algorithms that exploit client buffers have been proposed, thus reducing the peak rate and high rate variability by efficiently scheduling the video data to be transmitted over the network. The novel smoothing algorithm proposed in this paper, which represents a significant improvements over the existing methods, performs data scheduling both for a single stream and for stream aggregations, by taking into account available bandwidth constraints. It modifies, whenever possible, the smoothing schedule in such a way as to eliminate frame losses due to available bandwidth limitations. This technique can be applied to any smoothing algorithm already present in literature and can be usefully exploited to minimize losses in multiplexed stream scenarios, like Terrestrial Digital Video Broadcasting (DVB-T), where a specific known available bandwidth must be shared by several multimedia flows. The developed algorithm has been exploited for smoothing stored video, although it can also be quite easily adapted for real time smoothing. The obtained numerical results, compared with the MVBA, another smoothing algorithm that is already presented and discussed in literature, show the effectiveness of the proposed algorithm, in terms of lost video frames, for different multiplexed scenarios

Video traffic modeling and delivery

Video is becoming a major component of the network traffic, and thus there has been a great interest to model video traffic. It is known that video traffic possesses short range dependence (SRD) and long range dependence (LRD) properties, which can drastically affect network performance. By decomposing a video sequence into three parts, according to its motion activity, Markov-modulated self-similar process model is first proposed to capture autocorrelation function (ACF) characteristics of MPEG video traffic. Furthermore, generalized Beta distribution is proposed to model the probability density functions (PDFs) of MPEG video traffic. It is observed that the ACF of MPEG video traffic fluctuates around three envelopes, reflecting the fact that different coding methods reduce the data dependency by different amount. This observation has led to a more accurate model, structurally modulated self-similar process model, which captures the ACF of the traffic, both SRD and LRD, by exploiting the MPEG structure. This model is subsequently simplified by simply modulating three self-similar processes, resulting in a much simpler model having the same accuracy as the structurally modulated self-similar process model. To justify the validity of the proposed models for video transmission, the cell loss ratios (CLRs) of a server with a limited buffer size driven by the empirical trace are compared to those driven by the proposed models. The differences are within one order, which are hardly achievable by other models, even for the case of JPEG video traffic. In the second part of this dissertation, two dynamic bandwidth allocation algorithms are proposed for pre-recorded and real-time video delivery, respectively. One is based on scene change identification, and the other is based on frame differences. The proposed algorithms can increase the bandwidth utilization by a factor of two to five, as compared to the constant bit rate (CBR) service using peak rate assignment

Multimedia in mobile networks: Streaming techniques, optimization and User Experience

1.UMTS overview and User Experience 2.Streaming Service & Streaming Platform 3.Quality of Service 4.Mpeg-4 5.Test Methodology & testing architecture 6.Conclusion

On a Class of Time Varying Shapers with Application to the Renegotiable Variable Bit Rate Service

A shaper is a system that stores incoming bits in a buffer and delivers them as early as possible, while forcing the output to be constrained with a given arrival curve. A shaper is time invariant if the traffic constraint is defined by a fixed arrival curv