Emmanuel Jammeh

Interval Type-2 Fuzzy Logic Congestion Control for Video Streaming Across IP Networks

Intelligent congestion control is vital for encoded video streaming of a clip or film, as network traffic volatility and the associated uncertainties require constant adjustment of the bit rate. Existing solutions, including the standard transmission control protocol (TCP) friendly rate control equation-based congestion controller, are prone to fluctuations in their sending rate and may respond only when packet loss has already occurred. This is a major problem, because both fluctuations and packet loss affect the end-users perception of the delivered video. A type-1 (T1) fuzzy logic congestion controller (FLC) can operate at video display rates and can reduce packet loss and rate fluctuations, despite uncertainties in measurements of delay arising from congestion and network traffic volatility. However, a T1 FLC employing precise T1 fuzzy sets cannot fully cope with the uncertainties associated with such dynamic network environments. A type-2 FLC using type-2 fuzzy sets can handle such uncertainties to produce improved performance. This paper proposes an interval type-2 FLC that achieves a superior delivered video quality compared with existing traditional controllers and a T1 FLC. To show the response in different network scenarios, tests demonstrate the response both in the presence of typical Internet cross-traffic as well as when other video streams occupy a bottleneck on an All-Internet protocol (IP) network. As All-IP networks are intended for multimedia traffic, it is important to develop a form of congestion control that can transfer to them from the mixed traffic environment of the Internet. It was found that the proposed type-2 FLC, although it is specifically designed for Internet conditions, can also successfully react to the network conditions of an All-IP network. When the control inputs were subject to noise, the type-2 FLC resulted in an order of magnitude performance improvement in comparison with the T1 FLC. The type-2 FLC also showed reduced packet loss when compared with the other controllers, again resulting in superior delivered video quality. When judged by established criteria, such as TCP-friendliness and delayed feedback, fuzzy logic congestion control offers a flexible solution to network bottlenecks. These findings offer the type-2 FLC as a way forward for congestion control of video streaming across packet-switched IP networks.

Quality of experience (QoE) driven adaptation scheme for voice/video over IP

Network quality of service (NQoS) of IP networks is unpredictable and impacts the quality of networked multimedia services. Adaptive voice and video schemes are therefore vital for the provision of voice over IP (VoIP) services for optimised quality of experience (QoE). Traditional adaptation schemes based on NQoS do not take perceived quality into consideration even though the user is the best judge of quality. Additionally, uncertainties inherent in NQoS parameter measurements make the design of adaptation schemes difficult and their performance suboptimal. This paper presents a QoE-driven adaptation scheme for voice and video over IP to solve the optimisation problem to provide optimal QoE for networked voice and video applications. The adaptive VoIP architecture was implemented and tested both in NS2 and in an Open IMS Core network to allow extensive simulation and test-bed evaluation. Results show that the scheme was optimally responsive to available network bandwidth and congestion for both voice and video and optimised delivered QoE for different network conditions, and is friendly to TCP traffic.

Content-Based Video Quality Prediction for HEVC Encoded Videos Streamed Over Packet Networks

A new reference-free, objective, video quality prediction model that takes into account video content type to predict the quality of streamed high efficiency video coding (HEVC) encoded video sequences is proposed. Research has shown that for the same encoder settings and network quality of service (NQoS), the video quality differs for different types of video content . This indicates that, in addition to encoder settings and NQoS, there may be other key parameters that impact video quality. In this work, we hypothesized that video content type is one of the key parameters that may impact the quality of streamed videos. Based on this assertion, temporal information is extracted from the motion vector (MV) information inherent in the encoded video bitstreams and spatial information is extracted from the quantisation parameter (QP) and the number of bits (Bits) of coded intra (I) and predictive (P) frames to develop a metric that quantifies the content type of different video sequences . The content type metric is subsequently used together with encoding QP setting and network packet loss rate (PLR) to develop a reference -free objective video quality prediction model for streamed HEVC encoded video sequences. This model has an accuracy of 92% when the model predicted values of sequences not used in model derivation are compared with mean opinion score (MOS) obtained through subjective method.

Fuzzy-Logic Congestion Control of Transcoded Video Streaming Without Packet Loss Feedback

Congestion control of a variable bit-rate video stream crossing the Internet is crucial to ensuring the quality of the received video. When a fuzzy-logic congestion controller (FLC) changes the sending rate of a video transcoder, it does so without feedback of packet loss, using packet dispersion instead. Compared with the well-known TFRC and RAP controllers, the FLCs sending rate is significantly smoother, allowing it to more closely take up available bandwidth at a bottleneck link. There is an accompanying order of magnitude reduction in packet losses. Due to better utilization of the available bandwidth, video quality is improved over time by several decibels in low-packet-loss conditions. The strength of the FLC solution is demonstrated by the resulting video quality when typical Web traffic forms the background traffic. The FLC avoids any risk of congestion collapse through fairness to coexisting TCP flows and is robust to changes in path delay and router buffer configuration.

Delay-based congestion avoidance for video communication with fuzzy logic control

Early detection of network congestion is important in streaming video, as packet loss has a recurring impact on video quality. Packet delay itself, rather than packet loss, can give early notice of congestion provided it can accurately reflect the congestion level at the network path’s tight link. In this paper, the one-way delay of video packets serves as an incipient network congestion indicator, which acts as one input to fuzzy logic control of congestion avoidance to help optimize the response to network congestion. The fuzzy logic models are shown to be robust under: changes in the complexity and motion content of the video stream under control; a wide range one way end-to-end link delays up to 120 ms; and variations in available bandwidth. Tests reported that the fuzzy logic approach compares favorably to standard TFRC congestion control.

Rate-adaptive video streaming through packet dispersion feedback

The anticipated growth of IPTV makes selection of suitable congestion controllers for video-stream traffic of vital concern. Measurements of packet dispersion at the receiver provide a graded way of estimating congestion, which is particularly suited to video as it does not rely on packet loss. A closed-loop congestion controller, which dynamically adapts the bitstream output of a transcoder or video encoder to a rate less likely to lead to packet loss, is presented. The video congestion controller is based on fuzzy logic with packet dispersion and its rate of change forming the inputs. Compared with TCP emulators such as TCP-friendly rate control (TFRC) and rate adaptation protocol (RAP), which rely on packet loss for real-time congestion control, the fuzzy-logic trained systems sending rate is significantly smoother when multiple video-bearing sources share a tight link. Using a packet dispersion method similarly results in a fairer allocation of bandwidth than TFRC and RAP. These gains for video traffic are primarily because of better estimation of network congestion through packet dispersion but also result from accurate interpretation by the fuzzy-logic controller.

Open IMS Core with VoIP Quality Adaptation

As IMS becomes more available to academia and industry, the requirements for IMS clients are growing faster than ever. From all IMS components, IMS clients are vital components for the success of overall services provided by the IMS. Most of ongoing research is focusing on adding more services on clients side, none has been done for voice over Internet protocol (VoIP) quality adaptation so far. Since the end user is the only one to perceive the quality of services provided by the IMS network, this paper reports a testbed that demonstrates the concept of adaptation of VoIP system based on an open IMS core and open source mobile terminal.

Feedback-Free Early VoIP Quality Adaptation Scheme in Next Generation Networks

The Next Generation Networks (NGNs) were proposed to provide ubiquitous access to multimedia services over the Internet. With the best effort nature of the Internet, the quality of real time multimedia services such as voice and video can rapidly degrade due to network impairments. We propose a novel feedback-free Early VoIP Quality Adaptation Scheme (EVQAS) which can adapt voice send bit rate (e.g. Adaptive Multi-Rate (AMR) codec mode) automatically according to the buildup of queuing delay in the network. This differs from existing adaptation methods which adapt send bit rate according to either packet loss information or Perceived Quality of Service (PQoS) metrics (e.g. Mean Opinion Score (MOS)) derived from packet loss and delay. The proposed scheme can avoid congested packet loss which has an obvious impact on perceived voice quality. We implemented this adaptation mechanism in open Android mobile and tested in Open IMS Core testbed. Preliminary results show that the early adaptation mechanism can effectively release congestion before packet loss occurs. This has increased overall perceived voice quality when compared with existing adaptation method. This lightweight feedback-free early adaptation mechanism can be easily applied to other mobile devices to improve VoIP quality in current NGN VoIP applications.

Packet by Packet Analysis in Contemporary Network Simulators

This article presents a comparative study of three hybrid network simulators: OPNET’s Modeler and ns-2, as well as NCTUns. In order to fulfill this, the simulated results were compared with the results obtained from a real network testbed using a packet by packet analysis methodology. Using a generic network based in an experimental network and modeled in the three simulators, the experimental comparison consisted in introducing data traffic in six different scenarios, combining traffic patterns of Constant Bit Rate (CBR) and a File Transfer Protocol session (FTP). The first objective is to corraborate the precision of the used models in the simulation to create this traffic patterns. Second, to test the network response to these types of traffic, all these by using the same packet by packet analysis methodology. The results obtained from the simulators were compared against the results obtained from the testbed network. The results obtained in this study showed that ns-2 presents good results in the simulation of CBR traffic, while the Modeler from OPNET presents an outstanding traffic simulation in terms of the FTP traffic. Nevertheless, some problems were detected in the three simulators, but NCTUns was the one that presented the most number of errors and problems in the overall results. These types of studies at the packet by packet level are important to validate the models used in the simulations that are based in components and applications used in grand scale simulations.

Resource-Aware Fuzzy Logic Control of Video Streaming over IP and Wireless Networks

Congestion control of real-time streaming a video clip or film across the Internet is vital, as network traffic volatility requires constant adjustment of the bit rate in order to reduce packet loss. Traditional solutions to congestion control are prone to delivery rate fluctuations and may respond only when packet loss has already occurred, while both fluctuations and packet loss seriously affect the end user’s appreciation of the delivered video. In this chapter, fuzzy logic control (FLC) is newly applied to control of video streaming in fixed and wireless networks. In a fixed network, by way of congestion control the encoded video bitstream’s rate is adjusted according to the available bandwidth. Compared to existing controllers, FLC’s sending rate is significantly smoother, allowing it to closely track available bandwidth at a bottleneck on the video stream’s path across a network. The chapter also shows that when multiple video streams are congestion controlled through FLC, the result is a fairer and more efficient sharing of the bandwidth capacity. Also considered is a pioneering application of FLC to wireless networks, where other resources, apart from available bandwidth, come into play. An FLC system has been designed that provides a modular solution to control of latency and energy consumption, which is important for battery-powered devices, but must be balanced against the quality of delivered video. The chapter concludes by presenting the potential of emerging type-2 fuzzy logic as a way of significantly improving the robustness of classical type-1 fuzzy logic.