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25 August 2018, Volume 16 Issue 3

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The whole issue of ZTE Communications September 2018, Vol. 16 No.3

2018, 16(3):  0. 

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Special Topic

Next Generation Mobile Video Networking

HWANG Jenq-Neng, WEN Yonggang

2018, 16(3):  1-2.  doi:10.19729/j.cnki.1673-5188.2018.03.001

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Introduction to Point Cloud Compression

XU Yiling, ZHANG Ke, HE Lanyi, JIANG Zhiqian, ZHU Wenjie

2018, 16(3):  3-8.  doi:10.19729/j.cnki.1673-5188.2018.03.002

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Characterized by geometry and photometry attributes, point cloud has been widely applied in the immersive services of various 3D objects and scenes. The development of even more precise capture devices and the increasing requirements for vivid rendering inevitably induce huge point capacity, thus making the point cloud compression a demanding issue. In this paper, we introduce several well-known compression algorithms in the research area as well as the boosting industry standardization works. Specifically, based on various applications of this 3D data, we summarize the static and dynamic point cloud compression, both including irregular geometry and photometry information that represent the spatial structure information and corresponding attributes, respectively. In the end, we conclude the point cloud compression as a promising topic and discuss trends for future works.

Adaptive Mobile Video Delivery Based on Fountain Codes and DASH: A Survey

WU Kesong, CAO Xianbin, CHEN Zhifeng, WU Dapeng

2018, 16(3):  9-14.  doi:10.19729/j.cnki.1673-5188.2018.03.003

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Recent years have witnessed an explosive growth in mobile video-based services and efficient and reliable video delivery draws more and more attention. As a type of rateless codes, fountain codes can automatically adapt to wireless channel conditions without any knowledge of channels. This paper provides an overview of several typical Forward Error Correction (FEC) codes, such as Reed-Solomon (RS) code, Tornado code, Luby-Transform (LT) code, and Raptor code. We focus on a novel delay-aware fountain coding (DAF) technique that maximizes the code word length under the constraint of a given delay. Based on DAF, this paper also presents Unequal Error Protection DAF (UEP-DAF) which improves the Peak Signal to Noise Ratio (PSNR) without additional coordination between the encoder and the decoder, as well as Model Predictive Control DAF (MPC-DAF) which reduces the computational complexity to an affordable level for real-time video communications. Moreover, we review video streaming technologies, then introduce Dynamic Adaptive Streaming over HTTP (DASH) and DASH over Multiple Content Distribution Servers (MCDS-DASH) in detail. Based on MCDS-DASH that adapts video bitrate at the block level to alleviate video fluctuation, we propose a novel approach to integrating fountain codes with MCDS-DASH, which is capable of achieving unprecedented high throughput.

DASH and DASH-VR Video Multicast Systems

PARK Jounsup, HWANG Jenq-Neng

2018, 16(3):  15-22.  doi:10.19729/j.cnki.1673-5188.2018.03.004

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Multimedia data traffic occupies more than 70% of the Internet traffic and is still growing. On-demand video is already a major video content platform and private broadcast is getting more popular. In addition to this, virtual reality (VR) and augmented reality (AR) data traffic is increasing very fast. To provide the good quality of the multimedia service, huge amount of resource is needed because users’ service experience is usually proportional to the video rates they can receive. Moreover, the variation of the bandwidth also affects to the users’ experience, while more users want to use their mobile devices to see multimedia data by accessing the network through wireless links, such as Long Term Evolution (LTE) and Wi-Fi. Therefore, better spectral efficiency during wireless transmission and video rate adaptation to provide better quality to users are in great demand. Multicast system is one of the technologies that can improve the spectral efficiency drastically, and Dynamic Adaptive Streaming over HTTP (DASH) is one of the most popular video rate adaptation platforms. In this paper, we investigate the state-of-the-art video multicast technologies. LTE supports the multicast service through evolved Multimedia Broadcast Multicast Service (eMBMS) systems, and there are different algorithms to perform the video multicast along with adaptive video quality control. The algorithms include the procedure to decide the video rates, resource allocations, and user groupings. Moreover, we propose a novel approach to improve the quality of experience for DASH-VR video multicast systems.

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

Amulya Karaadi, Is-Haka Mkwawa, Lingfen Sun

2018, 16(3):  23-29.  doi:10.19729/j.cnki.1673-5188.2018.03.005

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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.

When Machine Learning Meets Media Cloud: Architecture, Application and Outlook

JIN Yichao, WEN Yonggang

2018, 16(3):  30-39.  doi:10.19729/j.cnki.1673-5188.2018.03.006

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Nowadays, media cloud and machine learning have become two hot research domains. On the one hand, the increasing user demand on multimedia services has triggered the emergence of media cloud, which uses cloud computing to better host media services. On the other hand, machine learning techniques have been successfully applied in a variety of multimedia applications as well as a list of infrastructure and platform services. In this article, we present a tutorial survey on the way of using machine learning techniques to address the emerging challenges in the infrastructure and platform layer of media cloud. Specifically, we begin with a review on the basic concepts of various machine learning techniques. Then, we examine the system architecture of media cloud, focusing on the functionalities in the infrastructure and platform layer. For each of these function and its corresponding challenge, we further illustrate the adoptable machine learning based approaches. Finally, we present an outlook on the open issues in this intersectional domain. The objective of this article is to provide a quick reference to inspire the researchers from either machine learning or media cloud area.

Research Paper

Mechanism of Fast Data Retransmission in CU-DU Split Architecture of 5G NR

HUANG He, LIU Yang, LIU Zhuang, HAN Jiren, GAO Yin

2018, 16(3):  40-44.  doi:10.19729/j.cnki.1673-5188.2018.03.007

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The 5G radio access network (RAN) architecture is supposed to be split into the central unit (CU) and the distributed unit (DU) in order to support more flexible transport networks and provide enhanced user experience. However, such functional split may also introduce some new technical issues. In this paper, we study the data fast retransmission issue introduced by this functional split in different scenarios and solutions are provided to handle this issue. With the fast data retransmission mechanism proposed in this paper, the retransmitted data packets could be identified and handled with high priority. In this way, the data delivery between the CU and DU in 5G RAN is assured.

DexDefender: A DEX Protection Scheme to Withstand Memory Dump Attack Based on Android Platform

RONG Yu, LIU Yiyi, LI Hui, WANG Wei

2018, 16(3):  45-51.  doi:10.19729/j.cnki.1673-5188.2018.03.008

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Since Dalvik Executable (DEX) files are prone to be reversed to the Java source code using some decompiling tools, how to protect the DEX files from attackers becomes an important research issue. The traditional way to protect the DEX files from reverse engineering is to encrypt the entire DEX file, but after the complete plain code has been loaded into the memory while the application is running, the attackers can retrieve the code by using memory dump attack. This paper presents a novel DEX protection scheme to withstand memory dump attack on the Android platform with the name of DexDefender, which adopts the dynamic class-restoration method to ensure that the complete plain DEX data not appear in the memory while the application is being loaded into the memory. Experimental results show that the proposed scheme can protect the DEX files from both reverse engineering and memory dump attacks with an acceptable performance.

A Quantum Key Re-Transmission Mechanism for QKD-Based Optical Networks

WANG Hua, ZHAO Yongli, WANG Dajiang, WANG Jiayu, WANG Zhenyu

2018, 16(3):  52-58.  doi:10.19729/j.cnki.1673-5188.2018.03.009

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Due to the vulnerability of fibers in optical networks, physical-layer attacks targeting photon splitting, such as eavesdropping, can potentially lead to large information and revenue loss. To enhance the existing security approaches of optical networks, a new promising technology, quantum key distribution (QKD), can securely encrypt services in optical networks, which has been a hotspot of research in recent years for its characteristic that can let clients know whether information transmission has been eavesdropped or not. In this paper, we apply QKD to provide secret keys for optical networks and then introduce the architecture of QKD based optical network. As for the secret keys generated by QKD in optical networks, we propose a re-transmission mechanism by analyzing the security risks in QKD-based optical networks. Numerical results indicate that the proposed re-transmission mechanism can provide strong protection degree with enhanced attack protection. Finally, we illustrated some future challenges in QKD-based optical networks.

Review

Persistent Data Layout in File Systems

LUO Shengmei, LU Youyou, YANG Hongzhang, SHU Jiwu, ZHANG Jiacheng

2018, 16(3):  59-66.  doi:10.19729/j.cnki.1673-5188.2018.03.010

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Data layout in a file system is the organization of data stored in external storages. The data layout has a huge impact on performance of storage systems. We survey three main kinds of data layout in traditional file systems: in-place update file system, log-structured file system, and copy-on-write file system. Each file system has its own strengths and weaknesses under different circumstances. We also include a recent usage of persistent layout in a file system that combines both flash memory and byte-addressable non-volatile memory. With this survey, we conclude that persistent data layout in file systems may evolve dramatically in the era of emerging non-volatile memory.