A Social-Aware P2P Video Transmission Strategy for Multimedia IoT Devices

Hsu, Tz-Heng; Tung, Yao-Min

doi:10.1109/access.2020.2995274

Cited by 9 publications

(4 citation statements)

References 18 publications

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“…With the rapid development of the internet of things (IoT), more and more machines and autonomous devices are interconnected to produce various communication devices, such as smartphones, tablets, and set-top boxes. In the communication device, many visual sensors or cameras are used to capture the large-scale video data, and the video data are gathered in the cloud by a wireless network [1]. At the IoT nodes, due to the limited capacities of the storage and processing, it is difficult to provide the high-quality recovered video in real time [2], so it is necessary to reduce the frame rate of video at the IoT nodes to restrict the transmission rate.…”

Section: Introductionmentioning

confidence: 99%

Machine-Type Video Communication Using Pretrained Network for Internet of Things

Hao

Sun

et al. 2021

Security and Communication Networks

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With the increasing demand for internet of things (IoT) applications, machine-type video communications have become an indispensable means of communication. It is changing the way we live and work. In machine-type video communications, the quality and delay of the video transmission should be guaranteed to satisfy the requirements of communication devices at the condition of limited resources. It is necessary to reduce the burden of transmitting video by losing frames at the video sender and then to increase the frame rate of transmitting video at the receiver. In this paper, based on the pretrained network, we proposed a frame rate up-conversion (FRUC) algorithm to guarantee low-latency video transmitting in machine-type video communications. At the IoT node, by periodically discarding the video frames, the video sequences are significantly compressed. At the IoT cloud, a pretrained network is used to extract the feature layers of the transmitted video frames, which is fused into the bidirectional matching to produce the motion vectors (MVs) of the losing frames, and according to the output MVs, the motion-compensated interpolation is implemented to recover the original frame rate of the video sequence. Experimental results show that the proposed FRUC algorithm effectively improve both objective and subjective qualities of the transmitted video sequences.

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Section: Introductionmentioning

confidence: 99%

Machine-Type Video Communication Using Pretrained Network for Internet of Things

Hao

Sun

et al. 2021

Security and Communication Networks

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“…A collaborative video streaming strategy is designed based integration of flexibility of D2D communications and scalable-high-efficiency-video-coding streams, which reduces the negative influence of network instability. Hsu et al propose a social-aware P2P video transmission strategy for multimedia IoT devices [32]. Multimedia IoT devices are grouped as a peer-to-peer (P2P) network and implement communications and interactions with each other in the P2P network.…”

Section: Related Workmentioning

confidence: 99%

A Novel Epidemic-Based Video Diffusion Strategy Using Awareness of Sociality and Mobility in Wireless Networks

Jia

Zhang

et al. 2023

Electronics

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Social networks open up a new channel of video sharing and promote the scale and efficiency of video diffusion. Adjustable and scalable video diffusion is significant for the quality and performance of the service of video systems. In this paper, we propose a novel epidemic-based video diffusion strategy using awareness of sociality and mobility in wireless networks (EVDSM). EVDSM constructs a video diffusion model with the consideration of interest preference, social influence, and user mobility according to the roles and the propagation process of the Epidemic model. EVDSM designs an estimation method of interest preference according to content similarity and preference discrimination between videos; EVDSM designs an estimation method of user roles by investigation of interest preference and social influence to identify the video sharing behaviors of users and define the roles of users; EVDSM designs an estimation method of user mobility in terms of data transmission time and path structure stability. EVDSM proposes a control strategy of video diffusion, which formulates priority-based pairing between infectors and candidate infectors to achieve joint optimization of pairing success rate and delivery performance. The simulation results show how EVDSM achieves much better performance results in comparison with other state-of-the-art solutions.

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“…In social-network-based incentive mechanisms such as [7], [33], [34], peers maintain social relationship links and provide services to their social friends based on the weight of their friendship and their mutual sharing contributions. Social network-based incentives are unfair to newcomers and are not scalable.…”

Section: B Reciprocity-based Categorymentioning

confidence: 99%

Share-Ratio-Based Incentive Mechanism for File Sharing With BitTorrent Protocol

Adamu

2021

IEEE Access

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Several P2P file-sharing networks were successfully deployed and are used by millions of Internet users globally to share files (such as movies, video clips, software systems, e-books, etc.) cooperatively over the Internet. These networks were designed with cooperation in mind, therefore, several incentive mechanisms were devised to encourage cooperation among downloaders and yet the free-riding phenomenon remains a threat to these networks since free-riders could indulge in acts such as whitewashing, Sybil, and collusion attacks to escape penalties imposed by the incentive mechanisms. This paper proposes a share-ratio-based incentive mechanism for P2P file-sharing networks where files are shared via BitTorrent protocol. The proposed incentive mechanism is not prone to Sybil and collusion attacks, and it was designed to simultaneously: (1) encourage cooperation, (2) provide fairness to new downloaders, and (3) deter freeriding while resisting whitewashing attack. The proposed incentive mechanism does not require any central entity to be realized and it was designed in existing terminologies used in P2P file-sharing networks, hence, it is easy to implement. In addition to the accomplishment of the set objectives, the proposed incentive mechanism has successfully deterred free-riding as shown by the experiments conducted.

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A Social-Aware P2P Video Transmission Strategy for Multimedia IoT Devices

Cited by 9 publications

References 18 publications

Machine-Type Video Communication Using Pretrained Network for Internet of Things

Machine-Type Video Communication Using Pretrained Network for Internet of Things

A Novel Epidemic-Based Video Diffusion Strategy Using Awareness of Sociality and Mobility in Wireless Networks

Share-Ratio-Based Incentive Mechanism for File Sharing With BitTorrent Protocol

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