Towards video streaming in IoT environments: vehicular communication perspective

Multimedia oriented Internet of Things (IoT) enables pervasive and real-time communication of video, audio and image data among devices in an immediate surroundings. Today's vehicles have the capability of supporting real time multimedia acquisition. Vehicles with high illuminating infrared cameras and customized sensors can communicate with other on-road devices using dedicated short-range communication (DSRC) and 5G enabled communication technologies. Real time incidence of both urban and highway vehicular traffic environment can be captured and transmitted using vehicle-to-vehicle and vehicle-to-infrastructure communication modes. Video streaming in vehicular IoT (VSV-IoT) environments is in growing stage with several challenges that need to be addressed ranging from limited resources in IoT devices, intermittent connection in vehicular networks, heterogeneous devices, dynamism and scalability in video encoding, bandwidth underutilization in video delivery, and attaining application-precise quality of service in video streaming. In this context, this paper presents a comprehensive review on video streaming in IoT environments focusing on vehicular communication perspective. Specifically, significance of video streaming in vehicular IoT environments is highlighted focusing on integration of vehicular communication with 5G enabled IoT technologies, and smart city oriented application areas for VSV-IoT. A taxonomy is presented for the classification of related literature on video streaming in vehicular network environments. Following the taxonomy, critical review of literature is performed focusing on major functional model, strengths and weaknesses. Metrics for video streaming in vehicular IoT environments are derived and comparatively analyzed in terms of their usage and evaluation capabilities. Open research challenges in VSV-IoT are identified as future directions of research in the area. The survey would benefit both IoT and vehicle industry practitioners and researchers, in terms of augmenting understanding of vehicular video streaming and its IoT related trends and issues

Survey on QoE/QoS Correlation Models for Video Streaming over Vehicular Ad-hoc Networks

Vehicular Ad-hoc Networks (VANETs) are a new emerging technology which has attracted enormous interest over the last few years. It enables vehicles to communicate with each other and with roadside infrastructures for many applications. One of the promising applications is multimedia services for traffic safety or infotainment. The video service requires a good quality to satisfy the end-user known as the Quality of Experience (QoE). Several models have been suggested in the literature to measure or predict this metric. In this paper, we present an overview of interesting researches, which propose QoE models for video streaming over VANETs. The limits and deficiencies of these models are identified, which shed light on the challenges and real problems to overcome in the future

A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks

One of the major challenges for the transmission of time-sensitive data like video over mobile ad-hoc networks (MANETs) is the deployment of an end-to-end QoS support mechanism. Therefore, several approaches and enhancements have been proposed concerning the routing protocols. In this paper we propose a new QoS routing protocol based on AODV (named AQA-AODV), which creates routes according to application QoS requirements. We have introduced link and path available bandwidth estimation mechanisms and an adaptive scheme that can provide feedback to the source node about the current network state, to allow the application to appropriately adjust the transmission rate. In the same way, we propose a route recovery approach into the AQA-AODV protocol, which provides a mechanism to detect the link failures in a route and re-establish the connections taking into account the conditions of QoS that have been established during the previous route discovery phase. The simulation results reveal performance improvements in terms of packet delay, number of link failures and connection setup latency while we make more efficient use of the available bandwidth than other protocols like AODV and QAODV. In terms of video transmission, the obtained results prove that the combined use of AQA-AODV and the scalable video coding provides an efficient platform for supporting rate-adaptive video streaming.Castellanos Hernández, WE.; Guerri Cebollada, JC.; Arce Vila, P. (2016). A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks. Computer Communications. 77:10-25. doi:10.1016/j.comcom.2015.08.012S10257

QSMVM: QoS-aware and social-aware multimetric routing protocol for video-streaming services over MANETs

A mobile ad hoc network (MANET) is a set of autonomous mobile devices connected by wireless links in a distributed manner and without a fixed infrastructure. Real-time multimedia services, such as video-streaming over MANETs, offers very promising applications, e.g. two members of a group of tourists who want to share a video transmitted through the MANET they form; a video-streaming service deployed over a MANET where users watch a film; among other examples. On the other hand, social web technologies, where people actively interact online with others through social networks, are leading to a socialization of networks. Information of interaction among users is being used to provide socially-enhanced software. To achieve this, we need to know the strength of the relationship between a given user and each user they interact with. This strength of the relationship can be measured through a concept called tie strength (TS), first introduced by Mark Granovetter in 1973. In this article, we modify our previous proposal named multipath multimedia dynamic source routing (MMDSR) protocol to include a social metric TS in the decisions taken by the forwarding algorithm. We find a trade-off between the quality of service (QoS) and the trust level between users who form the forwarding path in the MANET. Our goal is to increase the trust metric while the QoS is not affected significantly

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