How to Manage Multimedia Traffic: Based on QoE or QoT?

doi:10.19729/j.cnki.1673-5188.2018.03.005

ZTE Communications ›› 2018, Vol. 16 ›› Issue (3): 23-29.DOI: 10.19729/j.cnki.1673-5188.2018.03.005

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How to Manage Multimedia Traffic: Based on QoE or QoT?

Amulya Karaadi, Is-Haka Mkwawa, Lingfen Sun

School of Computing, Electronics and Mathematics, University of Plymouth, Plymouth, PL4 8AA, United Kingdom

Online:2018-08-25 Published:2020-03-18
About author:Amulya Karaadi (Amulya.karaadi@plymouth.ac.uk) received her master’s degree in computer systems networking and telecommunications from Staffordshire University, UK in 2016 and bachelor’s degree in information technology from JNTU University, India in 2013. She is now pursuing her Ph.D. at the University of Plymouth, UK in the area of intelligent multimedia transmissions for the Internet of Things (IoT) applications.|Is-Haka Mkwawa (Is-Haka.Mkwawa@plymouth.ac.uk) received his Ph.D. in computing from the University of Bradford, UK in 2004. He has been working in various capacities on EU FP6, FP7 and Horizon 2020 projects since 2002 with the University of Bradford, the University College Dublin and the University of Plymouth. These projects included IASON (2002-2004), Euro-NGI (2003-2005), Euro-FGI (2005-2008), Science Foundation Ireland (2005-2006), FP6 Vital (2006-2008), FP7 ADAMANTIUM (2008-2010) and FP7 GERYON (2011-2014). He has authored several refereed publication and co-authored Guide to Voice and Video over IP: For Fixed and Mobile Networks (Springer, 2013). His research interests include IMS media plane security for next generation of emergency communication and services, QoE control and management, mobility management in mobile and wireless networks, software defined networking, power saving in IoT, overlay networks, performance analysis and evaluation of IMS mobility management, parallel computing, and collective communication.|Lingfen Sun (L.Sun@plymouth.ac.uk) received the B.Eng. degree in telecommunication engineering and the M.Sc. degree in communications and electronic system from the Institute of Communication Engineering, China and the Ph.D. degree in computing and communications from the University of Plymouth, UK. She is currently an associate professor (Reader) in multimedia communications and networks in the School of Computing, Electronics and Mathematics, University of Plymouth. She has been involved in several European projects including H2020 QoE-NET as PI, COST Action QUALINET as an MC member, FP7 GERYON as PI and Scientific Manager and FP7 ADAMANTIUM as Co-PI and WP leader. She has published one book and over 90 peer-refereed technical papers/book chapters since 2000. She was the Chair of QoE Interest Group of IEEE MMTC during 2010-2012, and Symposium Co-Chair for IEEE ICC’14. She has been an AE for IEEE Transactions on Multimedia (2016-2018) and an expert reviewer for grants for EU, EPSRC (UK) and NSERC (Canada). Her main research interests include multimedia networking, multimedia quality assessment, QoS/QoE management, VoIP, DASH and SDN/NFV.

Abstract

Abstract:

Internet of Things (IoT) applications such as environmental monitoring, healthcare, surveillance, event recognition and traffic control are amongst the most commonly deployed applications over the Internet. These applications involve multimedia content that has to be collected, processed and delivered appropriately over the Internet for further processing by human or machines. These applications come with their own set of requirements such as quality, computational power and bandwidth. It is, therefore, vital to minimize power consumption and bandwidth usage in IoT devices without compromising the quality of multimedia delivery. Since the delivery of the multimedia can be destined to a machine or human, it is important to distinguish multimedia quality between the two. Quality of Experience (QoE) for video services involves human visual system, but what will involve a machine or process? To distinguish between the two, this paper defines a new concept of Acceptable Quality of Things (AQoT) which involves IoT devices and their applications. AQoT aims at minimizing bandwidth without compromising quality in IoT devices. Experimental results based on human detection and license number plate detection use cases have demonstrated that the AQoT concept can significantly reduce bandwidth usage.

Key words: QoE, QoT, IoT, bandwidth, video streaming

Amulya Karaadi, Is-Haka Mkwawa, Lingfen Sun. How to Manage Multimedia Traffic: Based on QoE or QoT?[J]. ZTE Communications, 2018, 16(3): 23-29.

Figures/Tables 14

Figure 1. Conceptual diagram for internet multimedia services.

Figure 2. Things, edge and cloud layers.

Figure 3. An IoT scenario for surveillance.

Table 1 Human detection video sequence

Video sequence	Resolution (pixels)	Bitrate (kbit/s)	Frame-rate (fps)
Human detection	768×576	5-800	25

Figure 4. Sample video sequences.

Table 2 License number plate image

Video sequence	Resolution (pixels)	Quality range (%)
Car1	640×480	1-90

Figure 5. Human detection video frames.

Figure 6. Human detection accuracy for frames 1, 44 and 102.

Figure 7. Quality of frames 1, 44 and 102.

Figure 8. Human detection video frames at 50 kbit/s.

Figure 9. Car1 number plate recognition accuracy.

Figure 10. SSIM values of the Car1 image.

Figure 11. Car1 number plate sequence frame size.

Figure 12. Car1 number plate at quality 5%.

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How to Manage Multimedia Traffic: Based on QoE or QoT?

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