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| 1 | NOMA-Based Energy-Efficient Task Scheduling in Vehicular Edge Computing Networks: A Self-Imitation Learning-Based Approach显示文摘Mobile Edge Computing(MEC)is promising to alleviate the computation and storage burdens for terminals in wireless networks.The huge energy consumption of MEC servers challenges the establishment of smart cities and their service time powered by rechargeable batteries.In addition,Orthogonal Multiple Access(OMA)technique cannot utilize limited spectrum resources fully and efficiently.Therefore,Non-Orthogonal Multiple Access(NOMA)-based energy-efficient task scheduling among MEC servers for delay-constraint mobile applications is important,especially in highly-dynamic vehicular edge computing networks.The various movement patterns of vehicles lead to unbalanced offloading requirements and different load pressure for MEC servers.Self-Imitation Learning(SIL)-based Deep Reinforcement Learning(DRL)has emerged as a promising machine learning technique to break through obstacles in various research fields,especially in time-varying networks.In this paper,we first introduce related MEC technologies in vehicular networks.Then,we propose an energy-efficient approach for task scheduling in vehicular edge computing networks based on DRL,with the purpose of both guaranteeing the task latency requirement for multiple users and minimizing total energy consumption of MEC servers.Numerical results demonstrate that the proposed algorithm outperforms other methods. | Peiran Dong Zhaolong Ning Rong Ma Xiaojie Wang Xiping Hu Bin Hu | 2020 | China Communications2020，17，11： | 4 |
| 2 | Intelligent resource allocation in mobile blockchain for privacy and security transactions:a deep reinforcement learning based approach显示文摘In order to protect the privacy and data security of mobile devices during the transactions in the industrial Internet of Things(IIoT),we propose a mobile edge computing(MEC)-based mobile blockchain framework by considering the limited bandwidth and computing power of small base stations(SBSs).First,we formulate a joint bandwidth and computing resource allocation problem to maximize the long-term utility of all mobile devices,and take into account the mobility of devices as well as the blockchain throughput.We decompose the formulated problem into two subproblems to decrease the dimension of action space.Then,we propose a deep reinforcement learning additional particle swarm optimization(DRPO)algorithm to solve the two subproblems,in which a particle swarm optimization algorithm is leveraged to avoid the unnecessary search of a deep deterministic policy gradient approach.Simulation results demonstrate the effectiveness of our method from various aspects. | Zhaolong NING Shouming SUN Xiaojie WANG Lei GUO Guoyin WANG Xinbo GAO Ricky YKKWOK | 2021 | Science China(Information Sciences)2021，64，6： | 3 |
| 3 | A secure routing scheme based on social network analysis in wireless mesh networks显示文摘As an extension of wireless ad hoc and sensor networks, wireless mesh networks(WMNs) are employed as an emerging key solution for wireless broadband connectivity improvement. Due to the lack of physical security guarantees, WMNs are susceptible to various kinds of attack. In this paper, we focus on node social selfish attack, which decreases network performance significantly. Since this type of attack is not obvious to detect, we propose a security routing scheme based on social network and reputation evaluation to solve this attack issue. First, we present a dynamic reputation model to evaluate a node's routing behavior, from which we can identify selfish attacks and selfish nodes. Furthermore, a social characteristic evaluation model is studied to evaluate the social relationship among nodes. Groups are built based on the similarity of node social status and we can get a secure routing based on these social groups of nodes. In addition, in our scheme, nodes are encouraged to enter into multiple groups and friend nodes are recommended to join into groups to reduce the possibility of isolated nodes. Simulation results demonstrate that our scheme is able to reflect node security status, and routings are chosen and adjusted according to security status timely and accurately so that the safety and reliability of routing are improved. | Yao YU Zhaolong NING Lei GUO | 2016 | Science China Earth Sciences2016，59，12： | 2 |
| 4 | Dynamic Cell Range Expansion-based Interference Coordination Scheme in Next Generation Wireless Networks显示文摘Deploying Picocell Base Station(PBS) throughout a Macrocell is a promising solution for capacity improvement in the next generation wireless networks.However,the strong received power from Macrocell Base Station(MBS) makes the areas of Picocell narrow and limits the gain of cell splitting.In this paper,we firstly propose a Dynamic Cell Range Expansion(DCRE) strategy.By expanding the coverage of the cell,we aim to balance the network load between MBS and PBS.Then,we present a cooperative Resource block and Power Allocation Scheme(coRPAS)based on DCRE.The objective of coRPAS is to decrease interference caused by MBS and Macrocell User Equipments,by which we can expand regions of Picocell User Equipments.Simulation results demonstrate the superiority of our method through comparing with other existing methods. | NING Zhaolong SONG Qingyang GUO Lei DAI Mengfan YUE Minghong | 2014 | China Communications2014，11，5： | 1 |
| 5 | FOG COMPUTING ENABLED INTERNET OF EVERYTHING显示文摘With the rapid development of ubiquitous networks and smart cities,the connection and communication of Internet of Everything(IoE)have drawn great attention from both academia and industry.The main challenge for constructing IoE is to enable real-time communication and high-efficiency computing among mobile devices.Mobile fog computing is promising to lower communication delay and offload network traffic.However,how to realize fog-enabled communication and computing in IoE with high-dynamic and heterogeneous network characters has not been fully investigated.Furthermore,deployment and reliable communications among fog nodes are also challenging. | Zhaolong Ning Lei Guo Joel Rodrigues Mohammad S.Obaidat | 2019 | China Communications2019，16，3： | 0 |
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