Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

The increasing popularity of live video streaming from mobile devices, such as Facebook Live, Instagram Stories, Snapchat, etc. pressurizes the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of quality of experience (QoE) as the basis for network control, customer loyalty, and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users' quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-the-art approaches following three key directions: 1) adaptation; 2) energy efficiency; and 3) multipath content delivery. Discussions, challenges, and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided

Seamless multimedia delivery within a heterogeneous wireless networks environment: are we there yet?

The increasing popularity of live video streaming from mobile devices such as Facebook Live, Instagram Stories, Snapchat, etc. pressurises the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of Quality of Experience (QoE) as the basis for network control, customer loyalty and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users’ quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-the-art approaches following three key directions: adaptation, energy efficiency and multipath content delivery. Discussions, challenges and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided

An approach for improving performance of aggregate voice-over-IP traffic

The emerging popularity and interest in Voice-over-IP (VoIP) has been accompanied by customer concerns about voice quality over these networks. The lack of an appropriate real-time capable infrastructure in packet networks along with the threats of denial-of service (DoS) attacks can deteriorate the service that these voice calls receive. And these conditions contribute to the decline in call quality in VoIP applications; therefore, error-correcting/concealing techniques remain the only alternative to provide a reasonable protection for VoIP calls against packet losses. Traditionally, each voice call employs its own end-to-end forward-error-correction (FEC) mechanisms. In this paper, we show that when VoIP calls are aggregated over a provider's link, with a suitable linear-time encoding for the aggregated voice traffic, considerable quality improvement can be achieved with little redundancy. We show that it is possible to achieve rates closer to channel capacity as more calls are combined with very small output loss rates even in the presence of significant packet loss rates in the network. The advantages of the proposed scheme far exceed similar or other coding techniques applied to individual voice calls

Adaptive delivery of real-time streaming video

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 87-92).While there is an increasing demand for streaming video applications on the Internet, various network characteristics make the deployment of these applications more challenging than traditional Internet applications like email and the Web. The applications that transmit data over the Internet must cope with the time-varying bandwidth and delay characteristics of the Internet and must be resilient to packet loss. This thesis examines these challenges and presents a system design and implementation that ameliorates some of the important problems with video streaming over the Internet. Video sequences are typically compressed in a format such as MPEG-4 to achieve bandwidth efficiency. Video compression exploits redundancy between frames to achieve higher compression. However, packet loss can be detrimental to compressed video with interdependent frames because errors potentially propagate across many frames. While the need for low latency prevents the retransmission of all lost data, we leverage the characteristics of MPEG-4 to selectively retransmit only the most important data in order to limit the propagation of errors. We quantify the effects of packet loss on the quality of MPEG-4 video, develop an analytical model to explain these effects, and present an RTP-compatible protocol-which we call SR-RTP--to adaptively deliver higher quality video in the face of packet loss. The Internet's variable bandwidth and delay make it difficult to achieve high utilization, Tcp friendliness, and a high-quality constant playout rate; a video streaming system should adapt to these changing conditions and tailor the quality of the transmitted bitstream to available bandwidth. Traditional congestion avoidance schemes such as TCP's additive-increase/multiplicative/decrease (AIMD) cause large oscillations in transmission rates that degrade the perceptual quality of the video stream. To combat bandwidth variation, we design a scheme for performing quality adaptation of layered video for a general family of congestion control algorithms called binomial congestion control and show that a combination of smooth congestion control and clever receiver-buffered quality adaptation can reduce oscillations, increase interactivity, and deliver higher quality video for a given amount of buffering. We have integrated this selective reliability and quality adaptation into a publicly available software library. Using this system as a testbed, we show that the use of selective reliability can greatly increase the quality of received video, and that the use of binomial congestion control and receiver quality adaptation allow for increased user interactivity and better video quality.by Nicholas G. Feamster.M.Eng

Adaptive network abstraction layer packetization for low bit rate H.264/AVC video transmission over wireless mobile networks under cross layer optimization

Master'sMASTER OF ENGINEERIN

Measurement-Driven Algorithm and System Design for Wireless and Datacenter Networks

The growing number of mobile devices and data-intensive applications pose unique challenges for wireless access networks as well as datacenter networks that enable modern cloud-based services. With the enormous increase in volume and complexity of traffic from applications such as video streaming and cloud computing, the interconnection networks have become a major performance bottleneck. In this thesis, we study algorithms and architectures spanning several layers of the networking protocol stack that enable and accelerate novel applications and that are easily deployable and scalable. The design of these algorithms and architectures is motivated by measurements and observations in real world or experimental testbeds. In the first part of this thesis, we address the challenge of wireless content delivery in crowded areas. We present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast. AMuSe is based on accurate receiver feedback and incurs a small control overhead. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. Specifically, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes which periodically send information about the channel quality to the multicast sender. Further, we describe the Multicast Dynamic Rate Adaptation (MuDRA) algorithm that utilizes AMuSe's feedback to optimally tune the physical layer multicast rate. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. We implemented the AMuSe system on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi nodes. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions. Further, our experimental evaluation of MuDRA on the ORBIT testbed shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of nodes while meeting quality requirements. As an example application, MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality. Next, we specifically focus on ensuring high Quality of Experience (QoE) for video streaming over WiFi multicast. We formulate the problem of joint adaptation of multicast transmission rate and video rate for ensuring high video QoE as a utility maximization problem and propose an online control algorithm called DYVR which is based on Lyapunov optimization techniques. We evaluated the performance of DYVR through analysis, simulations, and experiments using a testbed composed of Android devices and o the shelf APs. Our evaluation shows that DYVR can ensure high video rates while guaranteeing a low but acceptable number of segment losses, buffer underflows, and video rate switches. We leverage the lessons learnt from AMuSe for WiFi to address the performance issues with LTE evolved Multimedia Broadcast/Multicast Service (eMBMS). We present the Dynamic Monitoring (DyMo) system which provides low-overhead and real-time feedback about eMBMS performance. DyMo employs eMBMS for broadcasting instructions which indicate the reporting rates as a function of the observed Quality of Service (QoS) for each UE. This simple feedback mechanism collects very limited QoS reports which can be used for network optimization. We evaluated the performance of DyMo analytically and via simulations. DyMo infers the optimal eMBMS settings with extremely low overhead, while meeting strict QoS requirements under different UE mobility patterns and presence of network component failures. In the second part of the thesis, we study datacenter networks which are key enablers of the end-user applications such as video streaming and storage. Datacenter applications such as distributed file systems, one-to-many virtual machine migrations, and large-scale data processing involve bulk multicast flows. We propose a hardware and software system for enabling physical layer optical multicast in datacenter networks using passive optical splitters. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Our evaluation shows that the optical multicast architecture can achieve higher throughput and lower latency than IP multicast and peer-to-peer multicast schemes with lower switching energy consumption. Finally, we study the problem of congestion control in datacenter networks. Quantized Congestion Control (QCN), a switch-supported standard, utilizes direct multi-bit feedback from the network for hardware rate limiting. Although QCN has been shown to be fast-reacting and effective, being a Layer-2 technology limits its adoption in IP-routed Layer 3 datacenters. We address several design challenges to overcome QCN feedback's Layer- 2 limitation and use it to design window-based congestion control (QCN-CC) and load balancing (QCN-LB) schemes. Our extensive simulations, based on real world workloads, demonstrate the advantages of explicit, multi-bit congestion feedback, especially in a typical environment where intra-datacenter traffic with short Round Trip Times (RTT: tens of s) run in conjunction with web-facing traffic with long RTTs (tens of milliseconds)