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    25 April 2017, Volume 15 Issue 2
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    The whole issue of ZTE Communications April 2017, Vol. 15 No. 2
    2017, 15(2):  0. 
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    Special Topic
    Guest Editorial
    CAO Jiannong, RONG Chunming
    2017, 15(2):  1-1. 
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    Adaptive Service Provisioning for Mobile Edge Cloud
    HUANG Huawei, GUO Song
    2017, 15(2):  2-10.  doi:10.3969/j.issn.1673-5188.2017.02.001
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    A mobile edge cloud provides a platform to accommodate the offloaded traffic workload generated by mobile devices. It can significantly reduce the access delay for mobile application users. However, the high user mobility brings significant challenges to the service provisioning for mobile users, especially to delay-sensitive mobile applications. With the objective to maximize a profit, which positively associates with the overall admitted traffic served by the local edge cloud, and negatively associates with the access delay as well as virtual machine migration delay, we study a fundamental problem in this paper: how to update the service provisioning solution for a given group of mobile users. Such a profit-maximization problem is formulated as a nonlinear integer linear programming and linearized by absolute value manipulation techniques. Then, we propose a framework of heuristic algorithms to solve this Nondeterministic Polynomial (NP)-hard problem. The numerical simulation results demonstrate the efficiency of the devised algorithms. Some useful summaries are concluded via the analysis of evaluation results.

    Software Defined Networking Based On-Demand Routing Protocol in Vehicle Ad-Hoc Networks
    DONG Baihong, WU Weigang, YANG Zhiwei, LI Junjie
    2017, 15(2):  11-18.  doi:10.3969/j.issn.1673-5188.2017.02.002
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    This paper comes up with a SDN Based Vehicle Ad-Hoc On-Demand Routing Protocol (SVAO), which separates the data forwarding layer and network control layer, as in software defined networking (SDN), to enhance data transmission efficiency within vehicle ad-hoc networks (VANETs). The roadside service unit plays the role of local controller and is in charge of selecting vehicles to forward packets within a road segment. All the vehicles state in the road. Correspondingly, a two-level design is used. The global level is distributed and adopts a ranked query scheme to collect vehicle information and determine the road segments along which a message should be forwarded. On the other hand, the local level is in charge of selecting forwarding vehicles in each road segment determined by the global level. We implement two routing algorithms of SVAO, and compare their performance in our simulation. We compare SVAO with popular ad-hoc network routing protocols, including Optimized Link State Routing (OLSR), Dynamic Source Routing (DSR), Destination Sequence Distance Vector (DSDV), and distance-based routing protocol (DB) via simulations. We consider the impact of vehicle density, speed on data transmission rate and average packet delay. The simulation results show that SVAO performs better than the others in large-scale networks or with high vehicle speeds.

    An MEC and NFV Integrated Network Architecture
    LI Bing, ZHANG Yunyong, XU Lei
    2017, 15(2):  19-25.  doi:10.3969/j.issn.1673-5188.2017.02.003
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    The demand for 5G services and applications is driving the change of network architecture. The mobile edge computing (MEC) technology combines the mobile network technology with cloud computing and virtualization, and is one of the key technologies for 5G networks. Compared to network function virtualization (NFV), another critical enabler of 5G networks, MEC reduces latency and enhances the offered capacity. In this paper, we discuss the combination of the two technologies and propose a new architecture. Moreover, we list the application scenarios using the proposed architecture.

    Key Technologies and Application of Edge Computing
    TU Yaofeng, DONG Zhenjiang, YANG Hongzhang
    2017, 15(2):  26-34.  doi:10.3969/j.issn.1673-5188.2017.02.004
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    Cloud computing faces a series of challenges, such as insufficient bandwidth, unsatisfactory real-time, privacy protection, and energy consumption. To overcome the challenges, edge computing emerges. Edge computing refers to a process where the open platform that converges the core capabilities of networks, computing, storage, and applications provides intelligent services at the network edge near the source of the objects or data to meet the critical requirements for agile connection, real-time services, data optimization, application intelligence, security and privacy protection of industry digitization. Edge computing consists of three elements: edge, computing, and intelligence. Edge computing and the Internet of Things (IoT) mutually create, and edge computing and cloud computing complement each other. In the architecture of edge computing, resources are distributed to the edge nodes, and therefore the storage system is near users while the computation function is near data. In this way, the stress on the backbone network can be lessened. With this architecture, the existing key technologies for computation, networks, and storage will change significantly. ZTE’s edge computing solutions can ensure the service quality of operators and greatly enhance the experience of mobile users.

    Scheduling Heuristics for Live Video Transcoding on Cloud Edges
    Panagiotis Oikonomou, Maria G. Koziri, Nikos Tziritas, Thanasis Loukopoulos, XU Cheng-Zhong
    2017, 15(2):  35-41.  doi:10.3969/j.issn.1673-5188.2017.02.005
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    Efficient video delivery involves the transcoding of the original sequence into various resolutions, bitrates and standards, in order to match viewers’ capabilities. Since video coding and transcoding are computationally demanding, performing a portion of these tasks at the network edges promises to decrease both the workload and network traffic towards the data centers of media providers. Motivated by the increasing popularity of live casting on social media platforms, in this paper we focus on the case of live video transcoding. Specifically, we investigate scheduling heuristics that decide on which jobs should be assigned to an edge mini-datacenter and which to a backend datacenter. Through simulation experiments with different QoS requirements we conclude on the best alternative.

    Review
    A Survey on Cloud Security
    WU Chunming, LIU Qianjun, LI Yuwei, CHENG Qiumei, ZHOU Haifeng
    2017, 15(2):  42-47.  doi:10.3969/j.issn.1673-5188.2017.02.006
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    Cloud computing system packages infrastructures, applications and other resources as services, and delivers the services to market in an elastic and fast way. The significant advantages of cloud computing, e.g., scalability, elasticity, and pay-per-use, bring it considerable commercial values. Nevertheless, owing to the new application scenario, e.g., multi-tenant, cloud computing is encountering potential security risks. This paper reviews the state-of-art research in cloud security. According to the attack levels, it analyzes four kinds of attacks in the cloud, i.e., network-based attacks, VM-based attacks, storage-based attacks, and application-based attacks. The countermeasures and corresponding techniques are then introduced. Furthermore, this paper also discusses an innovative and promising solution for cloud security by dynamically changing system configuration.

    Research Paper
    Network Coding-Based Interference Management Scheme in D2D Communications
    WANG Shuang, HOU Ronghui
    2017, 15(2):  48-54.  doi:10.3969/j.issn.1673-5188.2017.02.007
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    In this paper, we propose an interference management scheme for device-to-device (D2D) communications in cellular networks. Considering the underlay D2D communications, the signal quality of cellular users would be affected by D2D users. To solve this problem, we explore the application of network coding and relay-assistance to mitigate interference. In the proposed scheme, helper nodes overhear the signal from cellular users, encode the received packets, and send the encoded packets to the base station. We design the helper node selection scheme and the transmission policy of helper nodes. The performance of the proposed scheme for different positions of the cellular user and D2D users is then evaluated. The results suggest that the cellular transmission scheme should be adjusted dynamically when underlay D2D communications are active. Compared with the existing solutions, the proposed scheme can effectively increase system throughput.

    Variable Bit Rate Fuzzy Control for Low Delay Video Coding
    ZHONG Min, ZHOU Yimin, LUO Minke, ZUO Wen
    2017, 15(2):  55-65.  doi:10.3969/j.issn.1673-5188.2017.02.008
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    Rate control plays a critical role in achieving perceivable video quality under a variable bit rate, limited buffer sizes and low delay applications. Since a rate control system exhibits non-linear and unpredictable characteristics, it is difficult to establish a very accurate rate-distortion (R-D) model and acquire effective rate control performance. Considering the excellent control ability and low computing complexity of the fuzzy logic in non-linear systems, this paper proposes a bit-rate control algorithm based on a fuzzy controller, named the Fuzzy Rate Control Algorithm (FRCA), for All-Intra (AI) and low-delay (LD) video source coding. Contributions of the proposed FRCA mainly consist of four aspects. First, fuzzy logic is adopted to minimize the deviation between the actual and the target buffer size in the hypothetical reference decoder (HRD). Second, a fast lookup table is employed in fuzzy rate control, which reduces computing cost of the control process. Third, an input domain determination scheme is proposed to improve the precision of the fuzzy controller. Fourth, a novel scene change detection is introduced and integrated in the FRCA to adaptively adjust the Group-of-Pictures (GOP) length when the source content fluctuates. The FRCA can be transplanted and implemented in various industry coders. Extensive experiments show that the FRCA has accurate variable bit-rate control ability and maintains a steady buffer size during the encoding processes. Compared with the default configuration encoding under AI and LD, the proposed FRCA can achieve the target bit rates more accurately in various classical encoders.