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    Guest Editorial
  • Guest Editorial
    SHFuzz: A Hybrid Fuzzing Method Assisted by Static Analysis for Binary Programs
    Wenjie Wang, Donghai Tian, Rui Ma, Hang Wei, Qianjin Ying, Xiaoqi Jia, Lei Zuo
    2021, 18(8): 1-16.
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    Fuzzing is an effective technique to find security bugs in programs by quickly exploring the input space of programs. To further discover vulnerabilities hidden in deep execution paths, the hybrid fuzzing combines fuzzing and concolic execution for going through complex branch conditions. In general, we observe that the execution path which comes across more and complex basic blocks may have a higher chance of containing a security bug. Based on this observation, we propose a hybrid fuzzing method assisted by static analysis for binary programs. The basic idea of our method is to prioritize seed inputs according to the complexity of their associated execution paths. For this purpose, we utilize static analysis to evaluate the complexity of each basic block and employ the hardware trace mechanism to dynamically extract the execution path for calculating the seed inputs' weights. The key advantage of our method is that our system can test binary programs efficiently by using the hardware trace and hybrid fuzzing. To evaluate the effectiveness of our method, we design and implement a prototype system, namely SHFuzz. The evaluation results show SHFuzz discovers more unique crashes on several real-world applications and the LAVA-M dataset when compared to the previous solutions.
  • Guest Editorial
    SecIngress: An API Gateway Framework to Secure Cloud Applications Based on N-Variant System
    Dacheng Zhou, Hongchang Chen, Guozhen Cheng, Weizhen He, Lingshu Li
    2021, 18(8): 17-34.
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    Based on the diversified technology and the cross-validation mechanism, the N-variant system provides a secure service architecture for cloud providers to protect the cloud applications from attacks by executing multiple variants of a single software in parallel and then checking their behaviors' consistency. However, it is complex to upgrade current Software as a Service (SaaS) applications to adapt N-variant system architecture. Challenges arise from the inability of tenants to adjust the application architecture in the cloud environment, and the difficulty for cloud service providers to implement N-variant systems using existing API gateways. This paper proposes SecIngress, an API gateway framework, to overcome the challenge that it is hard in the cloud environment to upgrade the applications based on N-variants system. We design a two-stage timeout processing method to lessen the service latency and an Analytic Hierarchy Process Voting under the Metadata mechanism (AHPVM) to enhance voting accuracy. We implement a prototype in a testbed environment and analyze the security and performance metrics before and after deploying the prototype to show the effectiveness of SecIngress. The results reveal that SecIngress enhances the reliability of cloud applications with acceptable performance degradation.
  • Guest Editorial
    Generative Trapdoors for Public Key Cryptography Based on Automatic Entropy Optimization
    Shuaishuai Zhu, Yiliang Han
    2021, 18(8): 35-46.
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    Trapdoor is a key component of public key cryptography design which is the essential security foundation of modern cryptography. Normally, the traditional way in designing a trapdoor is to identify a computationally hard problem, such as the NPC problems. So the trapdoor in a public key encryption mechanism turns out to be a type of limited resource. In this paper, we generalize the methodology of adversarial learning model in artificial intelligence and introduce a novel way to conveniently obtain sub-optimal and computationally hard trapdoors based on the automatic information theoretic search technique. The basic routine is constructing a generative architecture to search and discover a probabilistic reversible generator which can correctly encoding and decoding any input messages. The architecture includes a trapdoor generator built on a variational autoencoder (VAE) responsible for searching the appropriate trapdoors satisfying a maximum of entropy, a random message generator yielding random noise, and a dynamic classifier taking the results of the two generator. The evaluation of our construction shows the architecture satisfying basic indistinguishability of outputs under chosen-plaintext attack model (CPA) and high efficiency in generating cheap trapdoors.
  • Guest Editorial
    A Safe and Reliable Heterogeneous Controller Deployment Approach in SDN
    Peng Yi, Tao Hu, Yanze Qu, Liang Wang, Hailong Ma, Yuxiang Hu, Julong Lan
    2021, 18(8): 47-61.
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    Software-Defined Networking (SDN) provides flexible and global network management by decoupling control plane from data plane, and multiple controllers are deployed in the network in a logically centralized and physically distributed way. However, the existing approaches generally deploy the controllers with the same type in the network, which easily causes homogeneous controller common-mode fault. To this end, this paper proposes heterogeneous controller deployment in the SDN, considering the different types of controllers and relevant criteria (e.g., delay, control link interruption rate, and controller fault rate). Then, we introduce a Safe and Reliable Heterogeneous Controller Deployment (SRHCD) approach, consisting of two stages. Stage 1 determines the type and the number of heterogeneous controllers required for the SDN network based on the dynamic programming. Stage 2 divides the SDN network into multiple subnets by k-means algorithm and improves the genetic algorithm to optimize the heterogeneous controller deployment in these SDN subnets to ensure reliable switch-controller communications. Finally, the simulation results show that the proposed approach can effectively reduce the control plane fault rate and increase the attack difficulties. Besides, the switch- controller delay has been lowered by 16.5% averagely.
  • Guest Editorial
    Distributed Asynchronous Learning for Multipath Data Transmission Based on P-DDQN
    Kang Liu, Wei Quan, Deyun Gao, Chengxiao Yu, Mingyuan Liu, Yuming Zhang
    2021, 18(8): 62-74.
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    Adaptive packet scheduling can efficiently enhance the performance of multipath Data Transmission. However, realizing precise packet scheduling is challenging due to the nature of high dynamics and unpredictability of network link states. To this end, this paper proposes a distributed asynchronous deep reinforcement learning framework to intensify the dynamics and prediction of adaptive packet scheduling. Our framework contains two parts: local asynchronous packet scheduling and distributed cooperative control center. In local asynchronous packet scheduling, an asynchronous prioritized replay double deep Q-learning packets scheduling algorithm is proposed for dynamic adaptive packet scheduling learning, which makes a combination of prioritized replay double deep Q-learning network (P-DDQN) to make the fitting analysis. In distributed cooperative control center, a distributed scheduling learning and neural fitting acceleration algorithm to adaptively update neural network parameters of P-DDQN for more precise packet scheduling. Experimental results show that our solution has a better performance than Random weight algorithm and Round--Robin algorithm in throughput and loss ratio. Further, our solution has 1.32 times and 1.54 times better than Random weight algorithm and Round--Robin algorithm on the stability of multipath data transmission, respectively.
  • Guest Editorial
    A Fast Physical Layer Security-Based Location Privacy Parameter Recommendation Algorithm in 5G IoT
    Hua Zhao, Mingyan Xu, Zhou Zhong, Ding Wang
    2021, 18(8): 75-84.
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    The 5G IoT (Internet of Things, IoT) is easier to implement in location privacy-preserving research. The terminals in distributed network architecture blur their accurate locations into a spatial cloaking region but most existing spatial cloaking algorithms cannot work well because of man-in-the-middle attacks, high communication overhead, time consumption, and the lower success rate. This paper proposes an algorithm that can recommend terminal’s privacy requirements based on getting terminal distribution information in the neighborhood after cross-layer authentication and therefore help 5G IoT terminals find enough collaborative terminals safely and quickly. The approach shows it can avoid man-in-the-middle attacks and needs lower communication costs and less searching time than 520ms at the same time. It has a great anonymization success rate by 93% through extensive simulation experiments for a range of 5G IoT scenarios.
  • Guest Editorial
    SecMVX: Analysis on the Vulnerability of Multi-Variant Execution
    Bingzheng Li, Zheng Zhang, Xiaomei Wang, Sheng Qu, Jiangxing Wu
    2021, 18(8): 85-95.
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    As an active defenses technique, multi-variant execution(MVX) can detect attacks by monitoring the consistency of heterogeneous variants with parallel execution. ompared with patch-style passive defense, MVX can defend against known and even unknown vulnerability-based attacks without relying on attack feature information. However, variants generated with software diversity technologies will introduce new vulnerabilities when they execute in parallel. First, we analyze the security of MVX theory from the perspective of formal description. Then we summarize the general forms and techniques for attacks against MVX, and analyze the new vulnerabilities arising from the combination of variant generation technologies. We propose SecMVX, a secure MVX architecture and variant generation technology. Experimental evaluations based on CVEs and SPEC 2006 benchmark show that SecMVX introduces 11.29% of the average time overhead, and avoids vulnerabilities caused by the improper combination of variant generation technologies while keeping the defensive ability of MVX.
  • Guest Editorial
    Preventing Hardware Trojans in Switch Chip Based on Payload Decoupling
    Ke Song, Binghao Yan, Xiangyu Li, Qinrang Liu, Ling OuYang
    2021, 18(8): 96-108.
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    Hardware Trojans in integrated circuit chips have the characteristics of being covert, destructive, and difficult to protect, which have seriously endangered the security of the chips themselves and the information systems to which they belong. Existing solutions generally rely on passive detection techniques. In this paper, a hardware Trojans active defense mechanism is designed for network switching chips based on the principle of encryption algorithm. By encoding the data entering the chip, the argot hidden in the data cannot trigger the hardware Trojans that may exist in the chip, so that the chip can work normally even if it is implanted with a hardware Trojans. The proposed method is proved to be effective in preventing hardware Trojans with different trigger characteristics by simulation tests and practical tests on our secure switching chip.
  • Guest Editorial
    On Distributed Object Storage Architecture Based on Mimic Defense
    Haiyang Yu, Hui Li, Xin Yang, Huajun Ma
    2021, 18(8): 109-120.
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    With the advent of the era of big data, cloud computing, Internet of things, and other information industries continue to develop. There is an increasing amount of unstructured data such as pictures, audio, and video on the Internet. And the distributed object storage system has become the mainstream cloud storage solution. With the increasing number of distributed applications, data security in the distributed object storage system has become the focus. For the distributed object storage system, traditional defenses are means that fix discovered system vulnerabilities and backdoors by patching, or means to modify the corresponding structure and upgrade. However, these two kinds of means are hysteretic and hardly deal with unknown security threats. Based on mimic defense theory, this paper constructs the principle framework of the distributed object storage system and introduces the dynamic redundancy and heterogeneous function in the distributed object storage system architecture, which increases the attack cost, and greatly improves the security and availability of data.
    • COVER PAPER
  • COVER PAPER
    Creating Distinctive Connections between Multifunctional Microwave Circuits and Mobile-Terminal Radio-Frequency Integrated Chips Using Integrated Passive Device Technology
    Yongle Wu, Mengdan Kong, Zheng Zhuang, Weimin Wang
    2021, 18(8): 121-132.
    Abstract ( )   Knowledge map   Save
    In this review, the advanced microwave devices based on the integrated passive device (IPD) technology are expounded and discussed in detail, involving the performance breakthroughs and circuit innovations. Then, the development trend of IPD-based multifunctional microwave circuits is predicted further by analyzing the current research hot spots. This paper discusses a distinctive research area for microwave circuits and mobile-terminal radio-frequency integrated chips.
    • REVIEW PAPER
  • REVIEW PAPER
    A Survey on Belief Propagation Decoding of Polar Codes
    Ahmet Çağrı Arlı, Orhan Gazi
    2021, 18(8): 133-168.
    Abstract ( )   Knowledge map   Save
    The increasing data traffic rate of wireless communication systems forces the development of new technologies mandatory. Providing high data rate, extremely low latency and improvement on quality of service are the main subjects of next generation 5G wireless communication systems which will be in the people's life in the years of 2020. As the newest and first mathematically proven forward error correction code, polar code is one of the best candidates among error correction methods that can be employed for 5G wireless networks. The aim of this tutorial is to show that belief propagation decoding of polar codes can be a promising forward error correction technique in upcoming 5G frameworks. First, we survey the novel approaches to the belief propagation based decoding of polar codes and continue with the studies about the simplification of these decoders. Moreover, early detection and termination methods and concept of scheduling are going to be presented throughout the manuscript. Finally, polar construction algorithms, error types in belief propagation based decoders and hardware implementations are going to be mentioned. Overall, this tutorial proves that the BP based decoding of polar codes has a great potential to be a part of communication standards.
    • COMMUNICATIONS THEORIES & SYSTEMS
  • COMMUNICATIONS THEORIES & SYSTEMS
    Personalized Query Recommendation Using Semantic Factor Model
    Jin Xie, Fuxi Zhu, Huanmei Guan, Jiangqing Wang, Hao Feng, Lin Zheng
    2021, 18(8): 169-182.
    Abstract ( )   Knowledge map   Save
    In the field of query recommendation, the current techniques for semantic analysis technology can’t meet the demands of users. In order to meet diverse needs, we improved the LDA model and designed a new query recommendation model based on collaborative filtering-Semantic Factor Model (SFM), which combines text information, user interest information and web source. First, we improved the LDA model from bag-of-word to bag-of-phrase to understand the topics expressed by users' frequently used sentences. The phrase bag model treats phrases as a whole and can capture more accurate query intent. Second, we use collaborative filtering to build an evaluation matrix between user interests and personalized expressions. Third, we designed a new scoring function that can recommend the top n resources to users. Finally, we conduct experiments on the AOL data set. The experimental results show that compared with other latest query recommendation techniques, SFM has higher recommendation quality.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Γ-Access Policy: Attribute-Based Encryption Scheme for Social Network Based Data Trading
    Shamsher Ullah, Lan Zhang, Muhammad Wasif Sardar, Muhammad Tanveer Hussain
    2021, 18(8): 183-198.
    Abstract ( )   Knowledge map   Save
    The rapid development of social technology has replaced physical interaction in the trading market. The implication of this technology is to provide access to the right information at the right time. The drawback of these technologies is that the eavesdropper can remove the user from the network and can create proxy participants. In this paper, we discuss how a social network overcome and prevent these data trading issues. To maintain the security of data trading, we applied ABE technique based on DBDH to secure data trading network. Our proposed Γ-access policy scheme provides the best solution for the betterment of data trading network in terms of security. In Γ-access policy scheme, the users can encrypt and decrypt Private Transactions Information (PTI) using our proposed Γ-access policy. The security properties of Γ-access policy are data confidentiality, data integrity, authenticity, non-repudiation, and unforgeability. The efficiency of our scheme is 77.73%, which is more suitable for data trading markets and trading strategies.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Single-Site Indoor Fingerprint Localization Based on MIMO-CSI
    Jiancun Fan, Jianxiong Zhang, Xiaoyuan Dou
    2021, 18(8): 199-208.
    Abstract ( )   Knowledge map   Save
    In order to achieve higher accuracy and lower cost of indoor localization, we propose a positioning method using multiple input and multiple output (MIMO) channel state information (CSI) as a fingerprint. The method can be divided into three stages, feature extraction, offline training and online localization. In the feature extraction, the segmented average and principal component analysis (PCA) are used to reduce the data dimension and decrease system complexity. In the offline training, the deep neural network (NN) model is trained to implement the position classification. In the online localization, the data are input into the trained NN model first, and then its output is further processed by weighted k-nearest neighbor (WKNN) technology to estimate the position. Experimental results show that the proposed method can significantly reduce the positioning error compared to other methods and the average error is 1.39m in a complex indoor environment.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Design and Analysis of Spatial Modulation Based Orthogonal Time Frequency Space System
    Yingchao Yang, Zhiquan Bai, Ke Pang, Piming Ma, Haixia Zhang, Xinghai Yang, Dongfeng Yuan
    2021, 18(8): 209-223.
    Abstract ( )   Knowledge map   Save
    In this paper, we design a spatial modulation based orthogonal time frequency space (SM-OTFS) system to achieve improved transmission reliability and meet the high transmission rate and high-speed demands of future mobile communications, which fully utilizes the characteristics of spatial modulation (SM) and orthogonal time frequency space (OTFS) transmission. The detailed system design and signal processing of the SM-OTFS system have been presented. The closed-form expressions of the average symbol error rate (ASER) and average bit error rate (ABER) of the SM-OTFS system have been derived over the delay-Doppler channel with the help of the union bounding technique and moment-generating function (MGF). Meanwhile, the system complexity has been evaluated. Numerical results verify the correctness of the theoretical ASER and ABER analysis of the SM-OTFS system in the high signal-to-noise ratio (SNR) regions and also show that the SM-OTFS system outperforms the traditional SM based orthogonal frequency division multiplexing (SM-OFDM) system with limited complexity increase under mobile conditions, especially in high mobility scenarios.
  • COMMUNICATIONS THEORIES & SYSTEMS
    QMCR: A Q-Learning-Based Multi-Hop Cooperative Routing Protocol for Underwater Acoustic Sensor Networks
    Yougan Chen, Kaitong Zheng, Xing Fang, Lei Wan, Xiaomei Xu
    2021, 18(8): 224-236.
    Abstract ( )   Knowledge map   Save
    Routing plays a critical role in data transmission for underwater acoustic sensor networks (UWSNs) in the internet of underwater things (IoUT). Traditional routing methods suffer from high end-to-end delay, limited bandwidth, and high energy consumption. With the development of artificial intelligence and machine learning algorithms, many researchers apply these new methods to improve the quality of routing. In this paper, we propose a Q-learning-based multi-hop cooperative routing protocol (QMCR) for UWSNs. Our protocol can automatically choose nodes with the maximum Q-value as forwarders based on distance information. Moreover, we combine cooperative communications with Q-learning algorithm to reduce network energy consumption and improve communication efficiency. Experimental results show that the running time of the QMCR is less than one-tenth of that of the artificial fish-swarm algorithm (AFSA), while the routing energy consumption is kept at the same level. Due to the extremely fast speed of the algorithm, the QMCR is a promising method of routing design for UWSNs, especially for the case that it suffers from the extreme dynamic underwater acoustic channels in the real ocean environment.
  • COMMUNICATIONS THEORIES & SYSTEMS
    A Novel Robust Zero-Watermarking Algorithm for Audio Based on Sparse Representation
    Longting Xu, Daiyu Huang, Xing Guo, Wei Rao, Yunyun Ji, Ruoyi Li, Xiaochen Lu
    2021, 18(8): 237-248.
    Abstract ( )   Knowledge map   Save
    Behind the prevalence of multimedia technology, digital copyright disputes are becoming increasingly serious. The digital watermarking prevention technique against the copyright infringement needs to be improved urgently. Among the proposed technologies, zero-watermarking has been favored recently. In order to improve the robustness of the zero-watermarking, a novel robust audio zero-watermarking method based on sparse representation is proposed. The proposed scheme is mainly based on the K-singular value decomposition (K-SVD) algorithm to construct an optimal over complete dictionary from the background audio signal. After that, the orthogonal matching pursuit (OMP) algorithm is used to calculate the sparse coefficient of the segmented test audio and generate the corresponding sparse coefficient matrix. Then, the mean value of absolute sparse coefficients in the sparse matrix of segmented speech is calculated and selected, and then comparing the mean absolute coefficient of segmented speech with the average value of the selected coefficients to realize the embedding of zero-watermarking. Experimental results show that the proposed audio zero-watermarking algorithm based on sparse representation performs effectively in resisting various common attacks. Compared with the baseline works, the proposed method has better robustness.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Achieving Energy Efficiency in Wireless Sensor Networks Using Dynamic Channel Polling and Packet Concatenation
    Shama Siddiqui, Anwar Ahmed Khan, Sayeed Ghani
    2021, 18(8): 249-270.
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    There has been a significant interest of researchers to combine different schemes focused on optimizing energy performance while developing a MAC protocol for Wireless Sensor Networks (WSNs). In this paper, we propose to integrate two cross-layer schemes: dynamic channel polling and packet concatenation using a recent asynchronous MAC protocol “Adaptive & Dynamic Polling MAC” (ADP-MAC). ADP-MAC dynamically selects the polling interval distribution based on characterization of incoming traffic patterns using Coefficient of variation (CV). Packet Concatenation (PC) refers to combining the individually generated data packets into a single super packet and sending it at the polling instant. Also, the Block Acknowledgement (BA) scheme has been developed for ADP-MAC to work in conjunction with the packet concatenation. The proposed schemes have been implemented in Tiny-OS for Mica2 platform and Avrora emulator has been used for conducting experiments. Simulation results have revealed that the performance both in terms of energy & packet loss improves when ADP-MAC is used in conjunction with the additional features of PC & BA. Furthermore, the proposed scheme has been compared with a state-of-art packet concatenation primitive PiP (Packet-in-Packet). It has been observed that ADP-MAC supersedes the performance of PiP in terms of PDR (Packet Delivery Ratio) due to better management of synchronization between source and sink.
  • COMMUNICATIONS THEORIES & SYSTEMS
    A Log-Penalty-Based Method for Multi-Parameters Estimation with Partly Calibrated COLD Array
    Yudi Qin, Xiaoying Sun
    2021, 18(8): 271-278.
    Abstract ( )   Knowledge map   Save
    In this paper, we focus on the problem of joint estimation of DOA, power and polarization angle from sparse reconstruction perspective with array gain-phase errors, where a partly calibrated cocentered orthogonal loop and dipole (COLD) array is utilized. In detailed implementations, we first combine the output of loop and dipole in second-order statistics domain to receive the source signals completely, and then we use continuous multiplication operator to achieve gain-phase errors calibration. After compensating the gain-phase errors, we construct a log-penalty-based optimization problem to approximate e0 norm and further exploit difference of convex (DC) functions decomposition to achieve DOA. With the aid of the estimated DOAs, the power and polarization angle estimation are obtained by the least squares (LS) method. By conducting numerical simulations, we show the effectiveness and superiorities of the proposed method.
    • EMERGING TECHNOLOGIES & APPLICATIONS
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Blockchain and MEC-Assisted Reliable Billing Data Transmission over Electric Vehicular Network: An Actor-Critic RL Approach
    Xinyu Ye, Meng Li, Pengbo Si, Ruizhe Yang, Enchang Sun, Yanhua Zhang
    2021, 18(8): 279-296.
    Abstract ( )   Knowledge map   Save
    Recently, electric vehicles (EVs) have been widely used under the call of green travel and environmental protection, and diverse requirements for charging are also increasing gradually. In order to ensure the authenticity and privacy of charging information interaction, blockchain technology is proposed and applied in charging station billing systems. However, there are some issues in blockchain itself, including lower computing efficiency of the nodes and higher energy consumption in the consensus process. To handle the above issues, in this paper, combining blockchain and mobile edge computing (MEC), we develop a reliable billing data transmission scheme to improve the computing capacity of nodes and reduce the energy consumption of the consensus process. By jointly optimizing the primary and replica nodes offloading decisions, block size and block interval, the transaction throughput of the blockchain system is maximized, as well as the latency and energy consumption of the system are minimized. Moreover, we formulate the joint optimization problem as a Markov decision process (MDP). To tackle the dynamic and continuity of the system state, the reinforcement learning (RL) is introduced to solve the MDP problem. Finally, simulation results demonstrate that the performance improvement of the proposed scheme through comparison with other existing schemes.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    C-V2X Equipment Identification Management and Authentication Mechanism
    Shanzhi Chen, Qiang Li, Yong Wang, Hui Xu, Xiaoyong Jia
    2021, 18(8): 297-306.
    Abstract ( )   Knowledge map   Save
    Cellular vehicle-to-everything (C-V2X) is the most promising V2X communication technology which can greatly improve traffic efficiency and road safety. However, when vehicles are interconnected with the surrounding radio environment, the C-V2X system will face various network security risks and threats, significantly impacting on traffic and life safety. This paper proposes a novel unified identification management framework and security authentication mechanism for the C-V2X equipment based on the security problems analyses of the C-V2X system and the existing security protection schemes. This paper also presents the security analysis and evaluation for the unified identification management and authentication mechanism. A experiment system is implemented to verify feasibility and effectiveness for the proposed mechanism.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Research on Intelligent Logic Design and Application of Campus MMTC Scene Based on 5G Slicing Technology
    Lili Tong, Chen Zhang, Ronghuai Huang
    2021, 18(8): 307-315.
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    A consensus has been reached that 5G network slicing technology is becoming increasingly important in EMBB, MMTC and URLLC. However, this technology still has a long way to go in education industry. By selecting four types of demands in campus MMTC scenarios as specific application references, this research explores the architectural relationship between network slicing layer, intelligent terminal layer and application capability layer. Besides, emphasis has been put on the influences that virtual logic network design technology, isolation technology and standard technology has on application experiences. Under such goal, a two-dimensional route has been proposed to deploy network slicing technology based on the concept of full life cycle and the synergistic effect that AI algorithms has on slicing technology. This research is expected to nurture slicing technology, not only its technology chain, but more importantly, facilitate its value chain and large-scale vertical industry applications.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Two-Timescale Online Learning of Joint User Association and Resource Scheduling in Dynamic Mobile Edge Computing
    Jian Zhang, Qimei Cui, Xuefei Zhang, Xueqing Huang, Xiaofeng Tao
    2021, 18(8): 316-331.
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    For the mobile edge computing network consisting of multiple base stations and resource-constrained user devices, network cost in terms of energy and delay will incur during task offloading from the user to the edge server. With the limitations imposed on transmission capacity, computing resource, and connection capacity, the per-slot online learning algorithm is first proposed to minimize the time-averaged network cost. In particular, by leveraging the theories of stochastic gradient descent and minimum cost maximum flow, the user association is jointly optimized with resource scheduling in each time slot. The theoretical analysis proves that the proposed approach can achieve asymptotic optimality without any prior knowledge of the network environment. Moreover, to alleviate the high network overhead incurred during user handover and task migration, a two-timescale optimization approach is proposed to avoid frequent changes in user association. With user association executed on a large timescale and the resource scheduling decided on the single time slot, the asymptotic optimality is preserved. Simulation results verify the effectiveness of the proposed online learning algorithms.