List of Titles

A Joint framework for QoS and QoE for video transmission over wireless multimedia sensor networks

- Usman, Muhammad, Ning, Yang, Jan, Mian, Xiangjian, He, Min, Xu, Kin-Man, Lam

Authors: Usman, Muhammad , Ning, Yang , Jan, Mian , Xiangjian, He , Min, Xu , Kin-Man, Lam
Date: 2018
Type: Text , Journal article
Relation: IEEE transactions on mobile computing Vol. 17, no. 4 (2018), p. 746-759
Full Text: false
Reviewed:
Description: With the emergence of Wireless Multimedia Sensor Networks (WMSNs), the distribution of multimedia contents have now become a reality. Without proper management, the transmission of multimedia data over WMSNs affects the performance of networks due to excessive packet-drop. The existing studies on Quality of Service (QoS) mostly deal with simple Wireless Sensor Networks (WSNs) and as such do not account for an increasing number of sensor nodes and an increasing volume of data. In this paper, we propose a novel framework to support QoS in WMSNs along with a light-weight Error Concealment (EC) scheme. The EC schemes play a vital role to enhance Quality of Experience (QoE) by maintaining an acceptable quality at the receiving ends. The main objectives of the proposed framework are to maximize the network throughput and to cover-up the effects produced by dropped video packets. To control the data-rate, Scalable High efficiency Video Coding (SHVC) is applied at multimedia sensor nodes with variable Quantization Parameters (QPs). Multi-path routing is exploited to support real-time video transmission. Experimental results show that the proposed framework can efficiently adjust large volumes of video data under certain network distortions and can effectively conceal lost video frames by producing better objective measurements.

P2DCA: A Privacy-preserving-based data collection and analysis framework for IoMT applications

- Usman, Muhammad, Jan, Mian, He, Xiangjian, Chen, Jinjun

Authors: Usman, Muhammad , Jan, Mian , He, Xiangjian , Chen, Jinjun
Date: 2019
Type: Text , Journal article
Relation: IEEE journal on selected areas in communications Vol. 37, no. 6 (2019), p. 1222-1230
Full Text: false
Reviewed:
Description: The concept of Internet of Multimedia Things (IoMT) is becoming popular nowadays and can be used in various smart city applications, e.g., traffic management, healthcare, and surveillance. In the IoMT, the devices, e.g., Multimedia Sensor Nodes (MSNs), are capable of generating both multimedia and non-multimedia data. The generated data are forwarded to a cloud server via a Base Station (BS). However, it is possible that the Internet connection between the BS and the cloud server may be temporarily down. The limited computational resources restrict the MSNs from holding the captured data for a longer time. In this situation, mobile sinks can be utilized to collect data from MSNs and upload to the cloud server. However, this data collection may create privacy issues, such as revealing identities and location information of MSNs. Therefore, there is a need to preserve the privacy of MSNs during mobile data collection. In this paper, we propose an efficient privacy-preserving-based data collection and analysis (P2DCA) framework for IoMT applications. The proposed framework partitions an underlying wireless multimedia sensor network into multiple clusters. Each cluster is represented by a Cluster Head (CH). The CHs are responsible to protect the privacy of member MSNs through data and location coordinates aggregation. Later, the aggregated multimedia data are analyzed on the cloud server using a counter-propagation artificial neural network to extract meaningful information through segmentation. Experimental results show that the proposed framework outperforms the existing privacy-preserving schemes, and can be used to collect multimedia data in various IoMT applications.

Error concealment for cloud-based and scalable video coding of hd videos

- Usman, Muhammad, He, Xiangjian, Lam, Kin-Man, Xu, Min, Bokhari, Syed, Chen, Jinjun, Jan, Mian

Authors: Usman, Muhammad , He, Xiangjian , Lam, Kin-Man , Xu, Min , Bokhari, Syed , Chen, Jinjun , Jan, Mian
Date: 2019
Type: Text , Journal article
Relation: IEEE transactions on cloud computing Vol. 7, no. 4 (2019), p. 975-987
Full Text: false
Reviewed:
Description: The encoding of HD videos faces two challenges: requirements for a strong processing power and a large storage space. One time-efficient solution addressing these challenges is to use a cloud platform and to use a scalable video coding technique to generate multiple video streams with varying bit-rates. Packet-loss is very common during the transmission of these video streams over the Internet and becomes another challenge. One solution to address this challenge is to retransmit lost video packets, but this will create end-to-end delay. Therefore, it would be good if the problem of packet-loss can be dealt with at the user's side. In this paper, we present a novel system that encodes and stores the videos using the Amazon cloud computing platform, and recover lost video frames on user side using a new Error Concealment (EC) technique. To efficiently utilize the computation power of a user's mobile device, the EC is performed based on a multiple-thread and parallel process. The simulation results clearly show that, on average, our proposed EC technique outperforms the traditional Block Matching Algorithm (BMA) and the Frame Copy (FC) techniques.

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