391 research outputs found
Random Linear Network Coding for 5G Mobile Video Delivery
An exponential increase in mobile video delivery will continue with the
demand for higher resolution, multi-view and large-scale multicast video
services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a
number of new opportunities for optimizing video delivery across both 5G core
and radio access networks. One of the promising approaches for video quality
adaptation, throughput enhancement and erasure protection is the use of
packet-level random linear network coding (RLNC). In this review paper, we
discuss the integration of RLNC into the 5G NR standard, building upon the
ideas and opportunities identified in 4G LTE. We explicitly identify and
discuss in detail novel 5G NR features that provide support for RLNC-based
video delivery in 5G, thus pointing out to the promising avenues for future
research.Comment: Invited paper for Special Issue "Network and Rateless Coding for
Video Streaming" - MDPI Informatio
Adaptive Multicast of Multi-Layered Video: Rate-Based and Credit-Based Approaches
Network architectures that can efficiently transport high quality, multicast
video are rapidly becoming a basic requirement of emerging multimedia
applications. The main problem complicating multicast video transport is
variation in network bandwidth constraints. An attractive solution to this
problem is to use an adaptive, multi-layered video encoding mechanism. In this
paper, we consider two such mechanisms for the support of video multicast; one
is a rate-based mechanism that relies on explicit rate congestion feedback from
the network, and the other is a credit-based mechanism that relies on
hop-by-hop congestion feedback. The responsiveness, bandwidth utilization,
scalability and fairness of the two mechanisms are evaluated through
simulations. Results suggest that while the two mechanisms exhibit performance
trade-offs, both are capable of providing a high quality video service in the
presence of varying bandwidth constraints.Comment: 11 page
Quality of Service over Specific Link Layers: state of the art report
The Integrated Services concept is proposed as an enhancement to the current Internet architecture, to provide a better Quality of Service (QoS) than that provided by the traditional Best-Effort service. The features of the Integrated Services are explained in this report. To support Integrated Services, certain requirements are posed on the underlying link layer. These requirements are studied by the Integrated Services over Specific Link Layers (ISSLL) IETF working group. The status of this ongoing research is reported in this document. To be more specific, the solutions to provide Integrated Services over ATM, IEEE 802 LAN technologies and low-bitrate links are evaluated in detail. The ISSLL working group has not yet studied the requirements, that are posed on the underlying link layer, when this link layer is wireless. Therefore, this state of the art report is extended with an identification of the requirements that are posed on the underlying wireless link, to provide differentiated Quality of Service
Dynamic Feedback Flow Control Algorithms for Unicast and Multicast Available Bit Rate Service in Asynchronous Transfer Mode Networks
Asynchronous transfer mode (ATM) network technology has been
adopted to integrate different kinds of traffic, like video, audio and data. It provides several service categories including constant bit rate (CBR), variable bit rate (VBR), available bit rate (ABR), and unspecified bit rate (UBR) service. In particular, the ABR service has been approved to use the bandwidth left by CBR and VBR services, which is ideal for data applications and can perform well for real-time applications with the appropriate implementation. Basically ABR servIce attempts to guarantee minimum cell rate, achieve fairness, and minimise cell loss
by periodically indicating to sources the rate at which to send. Therefore, there is a critical need for an effective flow control mechanism to allocate network resources (buffers, bandwidth), and provide the negotiated quality of service. This thesis develops dynamic feedback flow control schemes in ATM networks, with primary focus on point-to-point (unicast) and point-tomUltipoint (multicast) ABR algorithms. Firstly, it surveys a number of point-to-point schemes proposed for supporting unicast ABR service. Some of these algorithms do not measure the actual ABR traffic load which leads to either overestimates or underestimates of the bandwidth allocation. Others do not monitor the activity of the sources and overlook the temporarily idle sources. The rest may be implemented with additional complexity. Secondly, the research shifts to the problems of point-to-multipoint algorithms by introducing the basic
concept of multicasting ABR servIce and reviewing a group of
consolidation schemes, where the compromise between low
consolidation nOlse and fast transient response is the main issue. Thirdly, the design and implementation issues have been addressed together with the major drawbacks of the previous schemes and hence two algorithms have been proposed. A dynamic rate-based flow control (DRFC) scheme has been developed to support ABR service in unicast environment, while an adaptive feedback consolidation (AFC) algorithm has been designed for ABR multicasting. Finally, these schemes are extensively tested and compared with others from the literature using a wide range of network configurations and different types of traffic sources. The simulation results show that the DRFC algorithm allocates
the available bandwidth fairly among the contending ABR sources, while achieving high link utilisation with reasonable growth of queues. The AFC scheme eliminates the consolidation noise with fast transient response as well as minimising the effect of non-responsive branches
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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)
An efficient flow control algorithm for multi-rate multicast networks
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