Kandaraj Piamrat

Quality of Experience Measurements for Video Streaming over Wireless Networks

As wireless networks have been increasingly deployed, the need of quality measurement became essential since network operators want to control their network resources while maintaining user satisfaction. More importantly, measurement of technical parameters fails to give an account of the user experience, what could be named QoE (Quality of Experience). Therefore, many techniques have been developed in order to assess as accurately as possible this perceptual quality. To investigate QoE measurement, this paper presents three approaches namely subjective approach, objective approach, and hybrid approach. It also presents performance evaluation of these approaches for assessing QoE in video streaming application over wireless networks in different network conditions (using variation of loss rate and its distribution). We focus more specifically on a hybrid approach called Pseudo Subjective Quality Assessment (PSQA) that keeps advantages of both subjective and objective schemes while minimizing their drawbacks. We demonstrate that this approach provides good estimations comparing to the well-known objective metric called Peak Signal to Noise Ratio (PSNR). We also observe that PSQA gives similar result comparing to subjective test that has been evaluated by human observers in most of the cases. Moreover, one objective of this evaluation is to validate PSQA for QoE measurement, which will facilitate the use of QoE as metric for resource management in the future. For that, we also give some possible directions allowing us to manage network resources using this metric.

QoE-Aware Admission Control for Multimedia Applications in IEEE 802.11 Wireless Networks

Widespread use of wireless networks nowadays raises many problems for service providers in managing their resources. These problems are caused mainly by restricted bandwidth and variable radio condition in this type of network. Moreover, with the emergence of multimedia traffic and its requirements in terms of quality, admission control is hence an inevitable choice to optimize network resources while maintaining high service quality at users. In this paper, we propose an admission control mechanism based on quality of experience (QoE) perceived by users. The human QoE is obtained by a tool called pseudo subjective quality assessment (PSQA), which is based on statistic learning using random neural network (RNN). Instead of relying on technical parameters such as bandwidth, loss, or latency, which do not correlate well with human perception, our scheme is based on mean opinion score (MOS) but without interaction from real humans. The simulation results demonstrate the better performance of our proposition compared to the loss-based approach regarding user satisfaction evaluated by achieved QoE at user and bandwidth utilization of the network evaluated by good put.

Q-DRAM: QoE-Based Dynamic Rate Adaptation Mechanism for Multicast in Wireless Networks

The deployment of real-time and multimedia applications over Wireless LAN has gained a growing interest in this last decade. These applications, e.g. video streaming, require tight guarantee on Quality of Service (QoS). Also, they use multicast communication in order to reduce the bandwidth consumption. However, in WLAN, multicast packets are sent with the basic rate (lowest rate); which results in capacity wasting because of longer channel occupancy. Moreover the lack of feedback mechanism makes it difficult to deal with reliability or service quality. In this paper, we propose to rely on the WLAN multi-rate capability, in order to transmit multicast packets with higher and dynamic rate than the basic rate. Unlike other existing protocols that use a static-threshold to decide when to change transmission rate, we propose a novel dynamic rate-adaptation mechanism based on Quality of Experience (QoE), namely Q-DRAM. According to the clients feedback on QoE, we adapt the multicast rate: (i) when users had bad QoE we reduce the multicast transmission rate; (ii) when users had good QoE, we increase the multicast transmission rate. Simulation results show that Q-DRAM increases the wireless channel utilization and maximizes users QoE, compared to existing solutions as well as to the IEEE 802.11 standard.

QoE-based network selection for multimedia users in IEEE 802.11 wireless networks

Widespread use of wireless networks nowadays raises many challenging issues to be explored. With increasing of multimedia traffic, quality of experience (QoE) needs to be satisfied at users while overall performance needs to be maintained at networks. In order to achieve these goals, the use of network selection mechanism is inevitable. When several access points are present, user should select the best available network while trying to keep load balanced between access networks. In this paper, we present a user-based and network-assisted scheme for network selection in wireless IEEE 802.11 technology. By providing users in decision making process with relevant information about the networks, the proposed solution keeps compromising advantage for both user and network. Our mechanism is based on a technique called pseudo-subjective quality assessment (PSQA), which is used basically to measure quality of experience perceived by users. We propose a new scheme where PSQA tool is used to assist in terminal-centric network selection. We explain the scheme and illustrate its efficient performance compared to a signal-based mechanism.

QoE-Aware Scheduling for Video-Streaming in High Speed Downlink Packet Access

With widespread use of multimedia communication, quality of experience (QoE) progressively becomes an important factor in networking today. Besides, multimedia applications can be supported under various technologies, including wired and wireless networks. Among them, Universal Mobile Telecommunications System (UMTS) is one of the most popular technology thanks to its support on mobility. Improved with a new access method (High Speed Downlink Packet Access or HSDPA), it can provide higher bandwidth and enable wider range of services including multimedia applications. In UMTS, different categories of traffic are specified along with their characteristics. Best effort traffic has been specified with less priority because it has fewer constraints. On the other hand, real-time multimedia traffic such as streaming video or VoIP are more sensitive to network condition changes, hence special treatment (e.g. QoS scheduler) is needed in order to achieve user satisfaction. According to the literature, most of scheduling mechanisms mainly take into account signal quality and fairness and do not consider user perception. In this paper, we propose a novel approach, QoE-aware scheduler that takes quality of experience into account when making scheduling decisions. Compared to other existing schedulers, QoE-aware approach has reached a profitable performance in terms of user satisfaction, throughput, and fairness.

Optimising QoE for Scalable Video multicast over WLAN

Quality of Experience (QoE) is the key to success for multimedia applications and perceptual video quality is one of the important component of QoE. A recent video encoding scheme called Scalable Video Coding (SVC) provides the flexibility and the capability to adapt the video quality to varying network conditions and heterogeneous users. In this paper, we focus on SVC multicast over IEEE 802.11 networks. Traditionally, multicast uses the lowest modulation resulting in a video with only base quality even for users with good channel conditions. To optimize QoE, we propose to use multiple multicast sessions with different transmission rates for different SVC layers. The goal is to provide at least the multicast session with acceptable quality to users with bad channel conditions and to provide additional multicast sessions having SVC enhancement layers to users with better channel conditions. The selection of modulation rate for each SVC layer and for each multicast session is achieved with binary integer linear programming depending on network conditions with a goal to maximize global QoE. Results show that our algorithm maximizes global QoE by providing highest quality videos to users with good channel conditions and by guaranteeing at least acceptable QoE for all users.

Rate adaptation mechanism for multimedia multicasting in wireless networks

Nowadays, wireless networks have been deploying everywhere, with IEEE 802.11 as the most popular standard. However, wireless resources are scarce and wireless condition varies often. These limitations are crucial for applications with tight QoS requirements such as video or voice over IP. To cope with the problems, the standard has provided many features including multi-rate capability, which is the focus of this paper. Multi-rate capability is beneficial especially for multicast transmission, in which the traffic sent by default at basic rate may result in capacity wasting because of longer channel occupancy. Moreover the lack of feedback mechanism makes it difficult to deal with reliability or service quality. Some protocols have proposed to use rate adaptation to handle the problems but none of them takes into account quality of experience (QoE), which is an essential quality indicator in multimedia traffic, for making decision. Therefore, we propose in this paper a novel rate-adaptation mechanism based on quality of experience. We make use of PSQA (Pseudo-Subjective Quality Assessment) tool for obtaining mean opinion score in real-time. Our objective is to improve bandwidth utilization while satisfying user experience. We illustrate significant performance improvement obtained by our scheme according to this goal.