Open-Source Telemedicine Platform for Wireless Medical Video Communication

An m-health system for real-time wireless communication of medical video based on open-source software is presented. The objective is to deliver a low-cost telemedicine platform which will allow for reliable remote diagnosis m-health applications such as emergency incidents, mass population screening, and medical education purposes. The performance of the proposed system is demonstrated using five atherosclerotic plaque ultrasound videos. The videos are encoded at the clinically acquired resolution, in addition to lower, QCIF, and CIF resolutions, at different bitrates, and four different encoding structures. Commercially available wireless local area network (WLAN) and 3.5G high-speed packet access (HSPA) wireless channels are used to validate the developed platform. Objective video quality assessment is based on PSNR ratings, following calibration using the variable frame delay (VFD) algorithm that removes temporal mismatch between original and received videos. Clinical evaluation is based on atherosclerotic plaque ultrasound video assessment protocol. Experimental results show that adequate diagnostic quality wireless medical video communications are realized using the designed telemedicine platform. HSPA cellular networks provide for ultrasound video transmission at the acquired resolution, while VFD algorithm utilization bridges objective and subjective ratings

Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751

Evaluation of Wirelessly Transmitted Video Quality Using a Modular Fuzzy Logic System

Video transmission over wireless computer networks is increasingly popular as new applications emerge and wireless networks become more widespread and reliable. An ability to quantify the quality of a video transmitted using a wireless computer network is important for determining network performance and its improvement. The process requires analysing the images making up the video from the point of view of noise and associated distortion as well as traffic parameters represented by packet delay, jitter and loss. In this study a modular fuzzy logic based system was developed to quantify the quality of video transmission over a wireless computer network. Peak signal to noise ratio, structural similarity index and image difference were used to represent the user's quality of experience (QoE) while packet delay, jitter and percentage packet loss ratio were used to represent traffic related quality of service (QoS). An overall measure of the video quality was obtained by combining QoE and QoS values. Systematic sampling was used to reduce the number of images processed and a novel scheme was devised whereby the images were partitioned to more sensitively localize distortions. To further validate the developed system, a subjective test involving 25 participants graded the quality of the received video. The image partitioning significantly improved the video quality evaluation. The subjective test results correlated with the developed fuzzy logic approach. The video quality assessment developed in this study was compared against a method that uses spatial efficient entropic differencing and consistent results were observed. The study indicated that the developed fuzzy logic approaches could accurately determine the quality of a wirelessly transmitted video

Optimized Visual Internet of Things in Video Processing for Video Streaming

The global expansion of the Visual Internet of Things (VIoT) has enabled various new applications during the last decade through the interconnection of a wide range of devices and sensors.Frame freezing and buffering are the major artefacts in broad area of multimedia networking applications occurring due to significant packet loss and network congestion. Numerous studies have been carried out in order to understand the impact of packet loss on QoE for a wide range of applications. This paper improves the video streaming quality by using the proposed framework Lossy Video Transmission (LVT)  for simulating the effect of network congestion on the performance of  encrypted static images sent over wireless sensor networks.The simulations are intended for analysing video quality and determining packet drop resilience during video conversations.The assessment of emerging trends in quality measurement, including picture preference, visual attention, and audio visual quality is checked. To appropriately quantify the video quality loss caused by the encoding system, various encoders compress video sequences at various data rates.Simulation results for different QoE metrics with respect to user developed videos have been demonstrated which outperforms the existing metrics

An automated model for the assessment of QoE of adaptive video streaming over wireless networks

[EN] Nowadays, heterogeneous devices are widely utilizing Hypertext Transfer Protocol (HTTP) to transfer the data. Furthermore, HTTP adaptive video streaming (HAS) technology transmits the video data over wired and wireless networks. In adaptive technology services, a client's application receives a streaming video through the adaptation of its quality to the network condition. However, such a technology has increased the demand for Quality of Experience (QoE) in terms of prediction and assessment. It can also cause a challenging behavior regarding subjective and objective QoE evaluations of HTTP adaptive video over time since each Quality of Service (QoS) parameter affects the QoE of end-users separately. This paper introduces a methodology design for the evaluation of subjective QoE in adaptive video streaming over wireless networks. Besides, some parameters are considered such as video characteristics, segment length, initial delay, switch strategy, stalls, as well as QoS parameters. The experiment's evaluation demonstrated that objective metrics can be mapped to the most significant subjective parameters for user's experience. The automated model could function to demonstrate the importance of correlation for network behaviors' parameters. Consequently, it directly influences the satisfaction of the end-user's perceptual quality. In comparison with other recent related works, the model provided a positive Pearson Correlation value. Simulated results give a better performance between objective Structural Similarity (SSIM) and subjective Mean Opinion Score (MOS) evaluation metrics for all video test samples.This work has been partially supported by the "Ministerio de Economia y Competitividad" in the "Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento" within the Project under Grant TIN2017-84802-C2-1-P. This study has been partially done in the computer science departments at the (University of Sulaimani and Halabja).Taha, M.; Ali, A.; Lloret, J.; Gondim, PRL.; Canovas, A. (2021). An automated model for the assessment of QoE of adaptive video streaming over wireless networks. Multimedia Tools and Applications. 80(17):26833-26854. https://doi.org/10.1007/s11042-021-10934-92683326854801

Evaluation of the MDC and FEC over the quality of service and quality of experience for video distribution in ad hoc networks

Mobile ad hoc networks (MANETs) offer an excellent scenario for deploying communication applications because of the connectivity and versatility of this kind of networks. In contrast, the topology is usually extremely dynamic causing high rate of packet loss, so that ensuring a specific Quality of Service (QoS) for real-time video services becomes a hard challenge. In this paper, we evaluate the effect of using Multiple Description Coding (MDC) and Forward Error Correction (FEC) techniques for improving video quality in a multimedia content distribution system. A hybrid architecture using fixed and wireless ad hoc networks is proposed, which enables the use of multipoint-to-point transmission. MDC and FEC mechanisms can be combined with multipath transmission to increase the network efficiency and recover lost packets, improving the overall Quality of Experience (QoE) of the receiver. Simulations have been analyzed paying attention to objective parameters (Peak Signal to Noise Ratio, Packet Delivery Ratio, Decodable Frame Rate and interruptions) and subjective parameters. Results show that MDC increases the probability of packet delivery and FEC is able to recover lost frames and reduce video interruptions in moderate mobility scenarios, resulting in the improvement of video quality and the final user experience.This work was supported by project MIQUEL (TEC2007- 68119-C02-01/TCM) of the Spanish Ministry of Education and Science. The authors would like to thank the Editor and the reviewers for helpful suggestions to improve the quality of this paper.Acelas Delgado, P.; Arce Vila, P.; Guerri Cebollada, JC.; Castellanos Hernández, WE. (2014). Evaluation of the MDC and FEC over the quality of service and quality of experience for video distribution in ad hoc networks. Multimedia Tools and Applications. 68(3):969-989. https://doi.org/10.1007/s11042-012-1111-3969989683Apostolopoulos JG, Wong T, Tan W, Wee SJ (2002) On multiple description streaming with content delivery networks. IEEE INFOCOMBoukerche A (2009) Algorithms and protocols for wireless and mobile ad hoc networks. John Wiley & Sons IncChow CO, Ishii H (2007) Enhancing real-time video streaming over mobile ad hoc networks using multipoint-to-point communication. Comput Commun 30:1754–1764Clausen T, Jacquet P (2003) Optimized link state routing protocol (OLSR), RFC 3626Corrie B et al (2003) Towards quality of experience in advanced collaborative environments. Third Annual Workshop on Advanced Collaborative EnvironmentsGabrielyan E, Hersch R (2006) Reliable multi-path routing schemes for real-time streaming. International Conference on Digital Telecommunications, pp 65–65Gandikota VR, Tamma BR, Murthy CSR (2008) Adaptive-FEC based packet loss resilience scheme for supporting voice communication over adhoc wireless networks. IEEE Trans Mobile Comput 7:1184–1199Gharavi H (2008) Multi-channel for multihop communication links. International Conference on Telecommunications, pp 1–6Grega M, Janowski L, Leszczuk M, Romaniak P, Papir Z (2008) Quality of experience evaluation for multimedia services. Przegląd Telekomunikacyjny i Wiadomości Telekomunikacyjne 4:142–153Hsieh MY, Huang YM, Chian TC (2007) Transmission of layered video streaming via multi-path on ad hoc networks. Multimed Tool Appl 34:155–177ITU—International Telecommunication Union (2007) Definition of quality of experience (QoE)”, Reference: TD 109rev2 (PLEN/12)ITU-R Recommendation BT.500-12 (2009) Methodology for the subjective assessment of the quality of television pictures. International Telecommunication Union, GenevaITU-T Recommendation P.910 (2000) Subjective video quality assessment methods for multimedia applications. International Telecommunication Union, GenevaKao KL, Ke ChH, Shieh CH (2006) An advanced simulation tool-set for video transmission performance evaluation. IEEE Region 10 Conference, pp 1–40Ke CH et al (2006) A novel realistic simulation tool for video transmission over wireless network. Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trsutworthy ComputingKeisuke U, Cheeonn C, Hiroshi I (2008) A study on video performance of multipoint-to-point video streaming with multiple description coding over ad hoc networks. EEJ Trans Electron, Inf Syst 128:1431–1437Kilkki K (2008) Quality of experience in communications ecosystem. J Univers Comput Sci 14:615–624Li A (2007) RTP payload format for generic forward error correction. RFC 5109, Dec. 2007Li J, Blake C, Couto DD, Lee H, Morris R (2001) Capacity of ad hoc wireless networks. 7th Annual International Conference on Mobile Computing and Networking, pp 16–21Liao Y, Gibson JD (2011) Routing-aware multiple description video coding over mobile ad-hoc networks. IEEE Trans Multimed 13:132–142Lindeberg M, Kristiansen S, Plagemann T, Goebel V (2011) Challenges and techniques for video streaming over mobile ad hoc networks. Multimed Syst 17:51–82Mao S et al (2003) Video transport over ad hoc networks: multistream coding with multipath transport. IEEE J Sel Area Comm 21:1721–1737Ni P (2009) Towards Optimal Quality of Experience Via Scalable Video Coding. Mälardalen University Press Licentiate Theses, SwedenPinson MH, Wolf S (2004) A new standardized method for objectively measuring video quality. IEEE Trans Broadcast 50:312–322Rong B, Qian Y, Lu K, Hu RQ, Kadoch M (2010) Multipath routing over wireless mesh networks for multiple description video transmission. IEEE J Sel Area Comm 28:321–331Schierl T, Ganger K, Hellge C, Wiegand T, Stockhammer T (2006) SVC-based multisource streaming for robust video trans- mission in mobile ad hoc networks. IEEE Wireless Comm 13:96–103Schierl T, Stockhammer T, Wiegand T (2007) Mobile video transmission using scalable video coding. IEEE Trans Circ Syst Video Tech 17:1204–1217Schwarz H, Marpe D, Wiegand T (2007) Overview of the scalable video coding extension of the H.264/AVC standard. IEEE Trans Circ Syst Video Tech 17:1103–1120VQEG (2008) Video quality experts group. Available online: http://www.vqeg.orgWang Z et al (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13:600–612Wei W, Zakhor A (2004) Robust multipath source routing protocol (RMPSR) for video communication over wireless ad hoc net- works. Proceedings of IEEE International Conference on Multimedia and Expo 2:1379–1382Winkler S, Mohandas P (2008) The evolution of video quality measurement: from PSNR to hybrid metrics. IEEE Trans Broadcast 54:660–668Xunqi Y, Modestino JW, Bajic IV (2005) Performance analysis of the efficacy of packet-level FEC in improving video transport over networks. IEEE International Conference on Image Processing 2:177–180Zink M, Schmitt J, Steinmetz R (2005) Layer-encoded video in scalable adaptive streaming. IEEE Trans Multimed 7:75–8

Objective assessment of region of interest-aware adaptive multimedia streaming quality

Adaptive multimedia streaming relies on controlled adjustment of content bitrate and consequent video quality variation in order to meet the bandwidth constraints of the communication link used for content delivery to the end-user. The values of the easy to measure network-related Quality of Service metrics have no direct relationship with the way moving images are perceived by the human viewer. Consequently variations in the video stream bitrate are not clearly linked to similar variation in the user perceived quality. This is especially true if some human visual system-based adaptation techniques are employed. As research has shown, there are certain image regions in each frame of a video sequence on which the users are more interested than in the others. This paper presents the Region of Interest-based Adaptive Scheme (ROIAS) which adjusts differently the regions within each frame of the streamed multimedia content based on the user interest in them. ROIAS is presented and discussed in terms of the adjustment algorithms employed and their impact on the human perceived video quality. Comparisons with existing approaches, including a constant quality adaptation scheme across the whole frame area, are performed employing two objective metrics which estimate user perceived video quality

Impact of the LTE scheduler on achieving good QoE for DASH video streaming

Dynamic adaptive video over HTTP (DASH) is fast becoming the protocol of choice for content providers for their online video streaming delivery. Concurrently, dependence on cellular Long Term Evolution (LTE) networks is growing to serve user demands for bandwidth-hungry applications, especially video. Each LTE base station's (eNodeB) scheduler assigns wireless resources to individual clients. Several alternative schedulers have been proposed, especially to meet the user's desired quality of experience (QoE) with video. In this paper, we investigate the impact of the scheduler on DASH performance, motivated by the fact that video performance and the underlying traffic models are different from other HTTP/TCP applications. We use our laboratory testbed employing real video content and streaming clients, over a simulated ns-3 LTE network. We quantify the impact of the scheduler and show that it has a significant impact on key video streaming performance metrics such as stalls and QoE, for different client adaptation algorithms. Additionally, we show the impact of user mobility within a cell, which has the side-effect of improving performance by mitigating long-term fading effects. Our detailed assessment of four LTE schedulers in ns-3 shows that the proportional fair scheduler achieves the best overall user experience, although somewhat disadvantaging static cell-edge users