Haptic data transferring through converged networks

Abstract

As the Internet spreads, new web applications come to light. One promising sector that is still in its infancy is supermedia applications. Supermedia applications manipulate video, audio, haptic and other sensory data. With the word haptic we refer to the sense of touch that the user feels when he uses a “Haptic” service. The haptic feeling has the ability to increase the sense of reality, to excite the user and improve the quality of experience. To carry out this sense through the Internet was, until recently, impracticable due to processing inefficiencies and/or protocol performance in capabilities, such as throughput and jitter constraints. This thesis presents a survey of transport protocols for supermedia applications. It outlines the Haptic data transmission characteristics and the necessary QoS requirements for the maximization of the Quality of Experience for Haptic users. It also depicts the qualitative features that transport and application layer protocols should contain in order to carry haptic data. It also describes a Haptic system architecture. A new network adaptive flow control algorithm is proposed. The new algorithm combines most of the known flow control algorithms while taking into account the network conditions οf the Internet and the significant haptic events. It analyses the metrics that have to be taken into consideration for the evaluation of Haptic transferring. These metrics are the delay, the jitter, the throughput, the efficiency, the packet loss and the proposed by the authors, packet arrival deviation. Based on these metrics, evaluation of the most commonly used real time transport protocols is performed. It also presents experiments for real time Haptic data transferring that have been carried out by the authors through different networks and locations. Extensive simulations and experiments for the performance evaluation of transport protocols for real time transferring HEVC streams with supermedia data are carried out. Complements, differences and relevancies between simulation and real world experiments are discussed. The simulation tests reveal which protocols could be used for the transfer of real-time supermedia data with a HEVC video stream. As far as video transmission is concerned, this thesis presents the related work on High Efficiency Video Coding. It points out the challenges and the synchronization techniques that have being proposed for synchronizing video and haptic data. Comparative tests between H.264 and HEVC are undertaken. Measurements for the network conditions of the Internet are carried out. The equations for the transferring delay of all the inter prediction configurations of the HEVC are defined. Furthermore, it proposes a new efficient algorithm for transferring a real-time High Efficient Video Coding stream with haptic data through the Internet. Furthermore, it presents the design of a novel real time wireless multisensory smart surveillance system with 3D HEVC features. The proposed high level system architecture of this surveillance system is analyzed. The advantages of the new HEVC encoding are presented. The synchronization issues between the multiple streams are described and solved. All the available wireless standard are presented and compared. A network adaptive transmission protocol for a reliable real-time multisensory surveillance system is proposed. Adaptive Packet Frame Grouping and quantization is enforced in order maximum Quality of Experience to be fulfilled. Measurements from the proposed protocol have given satisfactory results comparing to existing transport protocols. It also deals with the wireless transfer of real-time high update rate supermedia data over the Internet of Things. It presents the related work on supermedia data transferring and QoE requirements. It proposes a high level architectural design for the transport of wireless multiple supermedia streams over IoT. The most known compression techniques and flow controls for wireless sensory data transferring are analyzed. Based on these compression techniques a new network adaptive flow control algorithm is proposed. Measurements for multihop wireless transferring of high update rate supermedia packets over IoT are presented