Scene change detection-based Discrete Autoregressive modeling for MPEG-4 video traffic

Spanou, I.; Lazaris, Aggelos; Koutsakis, P.

doi:10.1109/icc.2013.6654888

Cited by 8 publications

(6 citation statements)

References 18 publications

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“…Most models are based on autoregressive models and their combinations, which fit the autocorrelation of video traffic well with low complexity [4]. I. Spanou proposed Discrete Autoregrassive modeling which is based on scene change detection [5]. Markov model with high complexity for 3D video is put forward in [6].…”

Section: Introductionmentioning

confidence: 99%

Traffic Model for Teleconsultation Based on the Service Characteristics

Yang¹,

Zhang²,

Kang³

2018

Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018

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The rapid development of numerous emerging network services poses a challenge to the network resources allocation with their bandwidth requirements and statistical characteristics. Network traffic modeling plays an important role in network resources allocation which can be used to guarantee Quality-of-Service (QoS) of these new services. In this study, we analyzed the service composition and traffic characteristics of the spreading teleconsultation service and establish a traffic model. The obtained experimental results show that the proposed methodology which combines discrete autoregressive model (DAR) and wavelet analysis provides good accuracy in teleconsultation service traffic modeling. Keywords-service traffic model; video traffic; discrete autoregressive model; wavelet model I. As Figure 1 shows, teleconsultation service provides video communication, medical images and teleconsultation text transmission between patient and doctor. Teleconsultation holds about ten to fifteen minutes. At the beginning of the teleconsultation process, medical images are transmitted and then there will be teleconsultation text transmission. Video transmission occurs throughout the process, so it is obvious that

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Section: Introductionmentioning

confidence: 99%

Traffic Model for Teleconsultation Based on the Service Characteristics

Yang¹,

Zhang²,

Kang³

2018

Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018

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“…Then, the separate models were used to create new synthetic traces. Again, more details can be found in [9].…”

Section: Related Workmentioning

confidence: 99%

“…In [9] we proposed a scene change detection-based Discrete Autoregressive Model, which was tested on more than sixty different long sequences of MPEG-4 encoded videos, from a publicly available library [28]. Indicative results for some of the 10 traces which we will proceed to use in our satellite CAC/MAC framework study are presented below.…”

Section: Related Workmentioning

confidence: 99%

“…For every scene in both categories, the number of I, P and B frames in it was determined and finally the DAR(1) model was ran, for every case. Details on the steps followed can be found in [9]. The next step, after scene identification, is scene classification.…”

Section: Related Workmentioning

confidence: 99%

“…The section also briefly presents recent work of ours [9] on a new hybrid video traffic model for MPEG-4 video traces, which significantly improves for video sources the accuracy of the DAR(1) model originally used in FPRRA. A vast number of traces has been used and modeled in [9], most of them different and burstier than the ones used in [7], therefore leading to more strenuous traffic scenarios for the system to handle. For the traces studied, the DAR(1) model does not provide satisfactory results, and hence a new modeling approach of low complexity is needed.…”

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confidence: 99%

See 2 more Smart Citations

Video scene identification and classification for user-tailored QoE in GEO satellites

Koutsakis

Spanou²,

Lazaris

2017

Hum. Cent. Comput. Inf. Sci.

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Satellite networks offer an efficient alternative where no terrestrial networks are available, and can offer a cost effective means of transferring data. Numerous proposals have addressed the problem of resource allocation in geostationary (GEO) satellites, and have been evaluated via various performance metrics related to user Quality of Service (QoS). However, ensuring that on average the users’ QoS requirements are satisfied does not guarantee the satisfaction of their individual Quality of Experience (QoE) requirements, especially in the case of bursty video users. This paper proposes the use of video scene identification and classification for traffic modeling at the scene level in order to improve resource allocation and user QoE in GEO satellite networks. The proposed call admission control and medium access control framework makes decisions based on available bandwidth, long-term and short-term user satisfaction and the revenue that the provider may gain.

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Data-driven QoE optimization techniques for multi-user wireless networks

Munaretto

Zucchetto

Zanella

et al. 2015

2015 International Conference on Computing, Networking and Communications (ICNC)

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The proliferation of heterogeneous data services and applications, with different communication requirements, has led to the design of Quality of Service (QoS) mechanisms to provide service differentiation and, possibly, performance guarantee to a range of classes of applications. In this paper, we propose a data-driven media delivery framework for the optimization of multi-user wireless networks that differs from the classic approaches in the following aspects. First, it goes beyond the QoS paradigm to embrace the Quality of Experience (QoE) approach, which discriminates data streams based on their actual content rather than just their class. Second, it applies cutting-edge cognitive science techniques to automatically learn data models and discover optimization strategies. To substantiate our argumentation, we discuss a couple of use cases regarding the transmission of multimedia content over a wireless link shared by users belonging to different QoE classes of service

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Scene change detection-based Discrete Autoregressive modeling for MPEG-4 video traffic

Cited by 8 publications

References 18 publications

Traffic Model for Teleconsultation Based on the Service Characteristics

Traffic Model for Teleconsultation Based on the Service Characteristics

Video scene identification and classification for user-tailored QoE in GEO satellites

Data-driven QoE optimization techniques for multi-user wireless networks

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