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The emerging connected and automated vehicle (CAV) has the potential to improve traffic efficiency and safety. With the cooperation between vehicles and intersection, CAVs can adjust speed and form platoons to pass the intersection faster. However, perceptual errors may occur due to external conditions of vehicle sensors. Meanwhile, CAVs and conventional vehicles will coexist in the near future and imprecise perception needs to be tolerated in exchange for mobility. In this paper, we present a simulation model to capture the effect of vehicle perceptual error and time headway to the traffic performance at cooperative intersection, where the intelligent driver model (IDM) is extended by the Ornstein–Uhlenbeck process to describe the perceptual error dynamically. Then, we introduce the longitudinal control model to determine vehicle dynamics and role switching to form platoons and reduce frequent deceleration. Furthermore, to realize accurate perception and improve safety, we propose a data fusion scheme in which the Differential Global Positioning system (DGPS) data interpolates sensor data by the Kalman filter. Finally, a comprehensive study is presented on how the perceptual error and time headway affect crash, energy consumption as well as congestion at cooperative intersections in partially connected and automated traffic. The simulation results show the trade-off between the traffic efficiency and safety for which the number of accidents is reduced with larger vehicle intervals, but excessive time headway may result in low traffic efficiency and energy conversion. In addition, compared with an on-board sensor independently perception scheme, our proposed data fusion scheme improves the overall traffic flow, congestion time, and passenger comfort as well as energy efficiency under various CAV penetration rates.
Chenghao Li; Zhiqun Hu; Zhaoming Lu; Xiangming Wen. Cooperative Intersection with Misperception in Partially Connected and Automated Traffic. Sensors 2021, 21, 5003 .
AMA StyleChenghao Li, Zhiqun Hu, Zhaoming Lu, Xiangming Wen. Cooperative Intersection with Misperception in Partially Connected and Automated Traffic. Sensors. 2021; 21 (15):5003.
Chicago/Turabian StyleChenghao Li; Zhiqun Hu; Zhaoming Lu; Xiangming Wen. 2021. "Cooperative Intersection with Misperception in Partially Connected and Automated Traffic." Sensors 21, no. 15: 5003.
Edge-assisted vehicular crowdsensing (EAVC) system is an emerging data collection paradigm in Internet of Vehicles (IoV), where intelligent vehicles collaboratively perform complex sensing tasks under the guidance of the edge server. One of the main characteristics of EAVC is that large and balanced spatiotemporal coverage is of paramount importance to support various crowdsensing applications. Most existing works have focused on recruiting pervasive non-dedicated vehicles to conduct data collection. However, the collected data of non-dedicated vehicles cannot satisfy the requirement of spatiotemporal coverage in terms of evenness and coverage rate, as the trajectories are not uniformly distributed in spatial and temporal domain. In this paper, we propose a collaborative data collection architecture based on edge intelligence, where non-dedicated and dedicated vehicles cooperate to carry out large-scale and fine-grained data collection with the assistance of the edge server. Particularly, we propose an objective function to better evaluate the spatiotemporal evenness of collected data in consideration of different spatiotemporal partitions based on entropy theory. With the objective function, the offline and online scheduling algorithms are designed to guide dedicated vehicles to proactively participate in crowdsensing tasks, using dynamic programming and greedy theories. Through extensive simulations, we have shown the necessity of introducing dedicated vehicles to assist data collection in vehicular crowdsensing system and the effectiveness and superiority of the proposed schemes.
Luning Liu; Zhaoming Lu; Luhan Wang; Yawen Chen; Xiangming Wen; Yong Liu; Meiling Li. Evenness-Aware Data Collection for Edge-Assisted Mobile Crowdsensing in Internet of Vehicles. IEEE Internet of Things Journal 2021, PP, 1 -1.
AMA StyleLuning Liu, Zhaoming Lu, Luhan Wang, Yawen Chen, Xiangming Wen, Yong Liu, Meiling Li. Evenness-Aware Data Collection for Edge-Assisted Mobile Crowdsensing in Internet of Vehicles. IEEE Internet of Things Journal. 2021; PP (99):1-1.
Chicago/Turabian StyleLuning Liu; Zhaoming Lu; Luhan Wang; Yawen Chen; Xiangming Wen; Yong Liu; Meiling Li. 2021. "Evenness-Aware Data Collection for Edge-Assisted Mobile Crowdsensing in Internet of Vehicles." IEEE Internet of Things Journal PP, no. 99: 1-1.
Unmanned aerial vehicles (UAVs) can be utilized to provide communication services for the areas where the communication is unavailable due to the high mobility, agility and low cost. In this letter, we investigate the energy efficient UAVs deployment and the movement for emergency response in the multi-UAVs enabled wireless communication system. The positions of the UAVs, the users association and the transmit power of the ground users are jointly optimized to maximize the energy efficiency of all ground users. And when one UAV leaves because of the breakdown or the drained battery, how the other UAVs move with the minimum energy cost is also studied. An alternating algorithm based on successive convex approximation (SCA) technique is proposed to solve the formulated optimization problems. Numerical results show the proposed multi-UAVs deployment and movement outperform the benchmarks.
Linpei Li; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Haijun Zhang. Energy-Efficient Multi-UAVs Deployment and Movement for Emergency Response. IEEE Communications Letters 2021, 25, 1625 -1629.
AMA StyleLinpei Li, Xiangming Wen, Zhaoming Lu, Wenpeng Jing, Haijun Zhang. Energy-Efficient Multi-UAVs Deployment and Movement for Emergency Response. IEEE Communications Letters. 2021; 25 (5):1625-1629.
Chicago/Turabian StyleLinpei Li; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Haijun Zhang. 2021. "Energy-Efficient Multi-UAVs Deployment and Movement for Emergency Response." IEEE Communications Letters 25, no. 5: 1625-1629.
Electric vehicles (EVs) are becoming increasingly popular, but the frequent charging and large charging latency remain major obstacles to the EV industry. This article focuses on the charging scheduling of on-the-move EVs in a transportation network to minimize EVs' charging latency, including driving time to charging stations (CSs), wait time and charging time. We formulate this charging scheduling problem as a graphical game to characterize the strong couplings of charging latency among neighboring EV players. Specially, we investigate correlated equilibrium (CE) to describe the joint strategies of EV players, which is expected to further reduce the charging latency of EVs compared with Nash equilibrium (NE). It is shown that CE always exists in a finite game, and can be found by linear programming tools. In addition, we propose a method of wait time prediction, which can improve the prediction accuracy by combining the data of deterministic EV arrivals and the stochastic property of potential EV arrivals. Simulation studies are used to examine the performance of the proposed game-based approach, the efficiency of CE, the preciseness of our proposed wait time prediction method, the impacts of CS deployment on EVs' charging latency, etc. We can draw a conclusion that our method has apparent advantages in situations where the locations of EV players are in dense manners.
Chunlei Sun; Xiangming Wen; Zhaoming Lu; Junshan Zhang; Xi Chen. A Graphical Game Approach to Electrical Vehicle Charging Scheduling: Correlated Equilibrium and Latency Minimization. IEEE Transactions on Intelligent Transportation Systems 2020, 22, 505 -517.
AMA StyleChunlei Sun, Xiangming Wen, Zhaoming Lu, Junshan Zhang, Xi Chen. A Graphical Game Approach to Electrical Vehicle Charging Scheduling: Correlated Equilibrium and Latency Minimization. IEEE Transactions on Intelligent Transportation Systems. 2020; 22 (1):505-517.
Chicago/Turabian StyleChunlei Sun; Xiangming Wen; Zhaoming Lu; Junshan Zhang; Xi Chen. 2020. "A Graphical Game Approach to Electrical Vehicle Charging Scheduling: Correlated Equilibrium and Latency Minimization." IEEE Transactions on Intelligent Transportation Systems 22, no. 1: 505-517.
In heterogeneous MIMO wireless LANs (WLANs), a multi-dimensional carrier sense multiple access (MDCSMA) based MAC protocols is developed by researchers to support multiple independent APs to communicate with its clients on the same channel, taking advantage of the extra degrees of freedom provided by nodes with more antennas. In this paper, we present an analytical model based on Markov chain to characterize the performance in throughput and mean access delay of this MDCSMA protocol in heterogeneous MIMO network. In MDCSMA protocol, nodes with more antennas than contention winner can allowed to continue to carry out carrier sense but in a space orthogonal to the ongoing transmissions. In each dimension carrier sense, we adopt p-persistent CSMA scheme to contend for the medium and dynamically adjust the average backoff time of p-persistent according to the number of nodes participated in and the available duration of average data transmission.Simulation and analysis results show that the analytical model can give close prediction of the network throughput of the multi-dimension carrier sense MAC protocol.
Zhiqun Hu; Hang Qi; Xiangming Wen; Zhaoming Lu; Wenpeng Jing. Performance analysis based Markov chain in random access heterogeneous MIMO networks. Computer Networks 2020, 180, 107415 .
AMA StyleZhiqun Hu, Hang Qi, Xiangming Wen, Zhaoming Lu, Wenpeng Jing. Performance analysis based Markov chain in random access heterogeneous MIMO networks. Computer Networks. 2020; 180 ():107415.
Chicago/Turabian StyleZhiqun Hu; Hang Qi; Xiangming Wen; Zhaoming Lu; Wenpeng Jing. 2020. "Performance analysis based Markov chain in random access heterogeneous MIMO networks." Computer Networks 180, no. : 107415.
Recent years have witnessed the great potential of adopting Channel State Information (CSI) for human-computer interaction by gestures. However, most current solutions either depend on specialized hardware or demand priori learning of wireless signal patterns, which face critical downsides in availability, reliability and extensibility. Hence this paper presents AirDraw, a novel learning-free in-air handwriting system by passive gesture tracking using only three commodity WiFi devices. First, we denoise CSI measurements by the ratio between two close-by antennas, and further separate the reflected signal from noise by performing Principal Component Analysis. Besides, we propose a robust signal calibration algorithm for tracking correction by eliminating the static components unrelated to hand motion. The prototype of AirDraw is fully realized and evaluated in real scenario. Extensive experiments yield that AirDraw can track user’s hand trace with a median error lower than 2.2 cm.
Zijun Han; Zhaoming Lu; Xiangming Wen; Jingbo Zhao; Lingchao Guo; Yue Liu. In-Air Handwriting by Passive Gesture Tracking Using Commodity WiFi. IEEE Communications Letters 2020, 24, 2652 -2656.
AMA StyleZijun Han, Zhaoming Lu, Xiangming Wen, Jingbo Zhao, Lingchao Guo, Yue Liu. In-Air Handwriting by Passive Gesture Tracking Using Commodity WiFi. IEEE Communications Letters. 2020; 24 (11):2652-2656.
Chicago/Turabian StyleZijun Han; Zhaoming Lu; Xiangming Wen; Jingbo Zhao; Lingchao Guo; Yue Liu. 2020. "In-Air Handwriting by Passive Gesture Tracking Using Commodity WiFi." IEEE Communications Letters 24, no. 11: 2652-2656.
Traffic light-free intersection control is envisioned to alleviate congestion and manage vehicles intelligently. With the help of vehicle-to-infrastructure (V2I) communication and edge computing (EC), vehicles are instructed to cross the intersection with high vehicle safety and traffic efficiency without traffic lights. However, unstable channel conditions can lead to the reduction of traveling safety. In this paper, we propose a robust autonomous intersection control (AIC) approach with global optimization scheduling, which protects connected autonomous vehicles from collision under any channel conditions while achieving decent traffic efficiency. In particular, we propose an AIC model that gives vehicles certain autonomy under centralized control to ensure the traveling safety in case of some emergencies. By conducting an interference graph, we simplify the AIC problem as a weighted maximal clique problem with restriction. To improve the fairness and efficiency in terms of vehicle passage, multiple factors such as travel delay, traffic of the current lane and passengers’ desired speed are considered. Furthermore, we propose a heuristic algorithm to search the solution space. For further optimization, a particle swarm optimization algorithm is proposed, achieving a near-optimal result with adjustable overhead. Finally, we build the simulation model and conduct a comparative performance evaluation. Simulation results demonstrate the superiority of our proposed scheme.
Yuheng Zhang; Luning Liu; Zhaoming Lu; Luhan Wang; Xiangming Wen. Robust Autonomous Intersection Control Approach for Connected Autonomous Vehicles. IEEE Access 2020, 8, 124486 -124502.
AMA StyleYuheng Zhang, Luning Liu, Zhaoming Lu, Luhan Wang, Xiangming Wen. Robust Autonomous Intersection Control Approach for Connected Autonomous Vehicles. IEEE Access. 2020; 8 ():124486-124502.
Chicago/Turabian StyleYuheng Zhang; Luning Liu; Zhaoming Lu; Luhan Wang; Xiangming Wen. 2020. "Robust Autonomous Intersection Control Approach for Connected Autonomous Vehicles." IEEE Access 8, no. : 124486-124502.
The data volume is exploding due to various newly-developing applications that call for stringent communication requirements towards 5th generation wireless systems. Fortunately, mobile edge computing makes it possible to relieve the heavy computation pressure of ground users and decrease the latency and energy consumption. What is more, the unmanned aerial vehicle has the advantages of agility and easy deployment, which gives the unmanned aerial vehicle enabled mobile edge computing system opportunities to fly towards areas with communication demand, such as hotspot areas. However, the limited endurance time of unmanned aerial vehicle affects the performance of mobile edge computing services, which results in the incomplete mobile edge computing services under the time limit. Consequently, this paper concerns the energy-efficient scheme design of the unmanned aerial vehicle while providing high-quality offloading services for ground users, particularly in the regions where the ground communication infrastructures are overloaded or damaged after natural disasters. Firstly, the model of energy-efficient design of the unmanned aerial vehicle is set up taking the constraints of the energy limitation of the unmanned aerial vehicle, the data causality, and the speed of the unmanned aerial vehicle into account. Subsequently, aiming at maximizing the energy efficiency of the unmanned aerial vehicle in the unmanned aerial vehicle enabled mobile edge computing system, the bits allocation in each time slot and the trajectory of the unmanned aerial vehicle are jointly optimized. Secondly, a successive convex approximation based alternating algorithm is brought forward to deal with the non-convex energy efficiency maximization problem. Finally, it is proved that the proposed energy efficient scheme design of the unmanned aerial vehicle is superior to other benchmark schemes by the simulation results. Besides, how the performance of proposed scheme design change under different parameters is discussed.
Linpei Li; Xiangming Wen; Zhaoming Lu; Wenpeng Jing. An Energy Efficient Design of Computation Offloading Enabled by UAV. Sensors 2020, 20, 1 .
AMA StyleLinpei Li, Xiangming Wen, Zhaoming Lu, Wenpeng Jing. An Energy Efficient Design of Computation Offloading Enabled by UAV. Sensors. 2020; 20 (12):1.
Chicago/Turabian StyleLinpei Li; Xiangming Wen; Zhaoming Lu; Wenpeng Jing. 2020. "An Energy Efficient Design of Computation Offloading Enabled by UAV." Sensors 20, no. 12: 1.
In order to meet the ever-increasing traffic demand of Wireless Local Area Networks (WLANs), channel bonding is introduced in IEEE 802.11 standards. Although channel bonding effectively increases the transmission rate, the wider channel reduces the number of non-overlapping channels and is more susceptible to interference. Meanwhile, the traffic load differs from one access point (AP) to another and changes significantly depending on the time of day. Therefore, the primary channel and channel bonding bandwidth should be carefully selected to meet traffic demand and guarantee the performance gain. In this paper, we proposed an On-Demand Channel Bonding (O-DCB) algorithm based on Deep Reinforcement Learning (DRL) for heterogeneous WLANs to reduce transmission delay, where the APs have different channel bonding capabilities. In this problem, the state space is continuous and the action space is discrete. However, the size of action space increases exponentially with the number of APs by using single-agent DRL, which severely affects the learning rate. To accelerate learning, Multi-Agent Deep Deterministic Policy Gradient (MADDPG) is used to train O-DCB. Real traffic traces collected from a campus WLAN are used to train and test O-DCB. Simulation results reveal that the proposed algorithm has good convergence and lower delay than other algorithms.
Hang Qi; Hao Huang; Zhiqun Hu; Xiangming Wen; Zhaoming Lu. On-Demand Channel Bonding in Heterogeneous WLANs: A Multi-Agent Deep Reinforcement Learning Approach. Sensors 2020, 20, 2789 .
AMA StyleHang Qi, Hao Huang, Zhiqun Hu, Xiangming Wen, Zhaoming Lu. On-Demand Channel Bonding in Heterogeneous WLANs: A Multi-Agent Deep Reinforcement Learning Approach. Sensors. 2020; 20 (10):2789.
Chicago/Turabian StyleHang Qi; Hao Huang; Zhiqun Hu; Xiangming Wen; Zhaoming Lu. 2020. "On-Demand Channel Bonding in Heterogeneous WLANs: A Multi-Agent Deep Reinforcement Learning Approach." Sensors 20, no. 10: 2789.
Human sensing based on commodity Wi-Fi devices has made significant advances in indoor localization, activity recognition, walking speed monitoring, etc. However, all past human sensing systems using Wi-Fi capture limited information about humans. Hence in this paper, we try to make commodity Wi-Fi devices act as cameras to directly capture human poses, i.e., fine-grained human skeleton images. We use a synchronized camera to capture human skeletons as annotations for Wi-Fi signals and design a novel neural network to convertWi-Fi signals into images. We utilize three transceivers coordinately and use amplitude and phase information of Channel State Information (CSI) jointly to improve the resolution of Wi-Fi signals. We also introduce a method to extract useful and accurate CSI corresponding to humans and construct CSI images which are input of the neural network. Experimental results show that commodity Wi-Fi devices can capture human poses almost as fine-grained as cameras.
Lingchao Guo; Zhaoming Lu; Xiangming Wen; Shuang Zhou; Zijun Han. From Signal to Image: Capturing Fine-Grained Human Poses With Commodity Wi-Fi. IEEE Communications Letters 2019, 24, 802 -806.
AMA StyleLingchao Guo, Zhaoming Lu, Xiangming Wen, Shuang Zhou, Zijun Han. From Signal to Image: Capturing Fine-Grained Human Poses With Commodity Wi-Fi. IEEE Communications Letters. 2019; 24 (4):802-806.
Chicago/Turabian StyleLingchao Guo; Zhaoming Lu; Xiangming Wen; Shuang Zhou; Zijun Han. 2019. "From Signal to Image: Capturing Fine-Grained Human Poses With Commodity Wi-Fi." IEEE Communications Letters 24, no. 4: 802-806.
The Internet of Things (IoT) is a new heterogeneous system integrated by the various end users (sensors and terminals) with different technologies. However, the limiting factor is bandwidth in the IoT due to the exploding end users and the network bandwidth requirements. A novel IoT model, which integrates the power-line carrier (PLC) and the wireless network (WN), is proposed to solve the bandwidth problem from the architecture, especially in the areas lacking network facilities. In addition, we exploit an effective virtual layer (EVL) which allows the different end users to access the system model seamlessly. Then, the attractor selection algorithm based on Markov chain (MASA) is employed to select an optimal path among the PLC or WN. The simulation results demonstrate that the proposed system model has the smaller average queuing delay than other algorithms and makes the model more stable and robust.
Huan Wu; Xiangming Wen; Zhaoming Lu; Yao Nie; Shuyang Huang. Adaptive Multipath Selection-Based Markov Chain in the Heterogeneous Internet of Things. Wireless Communications and Mobile Computing 2019, 2019, 1 -15.
AMA StyleHuan Wu, Xiangming Wen, Zhaoming Lu, Yao Nie, Shuyang Huang. Adaptive Multipath Selection-Based Markov Chain in the Heterogeneous Internet of Things. Wireless Communications and Mobile Computing. 2019; 2019 ():1-15.
Chicago/Turabian StyleHuan Wu; Xiangming Wen; Zhaoming Lu; Yao Nie; Shuyang Huang. 2019. "Adaptive Multipath Selection-Based Markov Chain in the Heterogeneous Internet of Things." Wireless Communications and Mobile Computing 2019, no. : 1-15.
The unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) system is attracting a lot of attentions for the potential of low latency and low transmission energy consumption, due to the advantages of high mobility and easy deployment. It has been widely applied to provide communication and computing services, especially in Internet of Things (IoT). However, there are still some challenges in the UAV-enabled MEC system. Firstly, the endurance of the UAV is limited and further impacts the performance of the system. Secondly, mobile devices are battery-powered and the batteries of some devices are hard to change. Therefore, in this paper, a UAV-enabled MEC system in which the UAV is empowered to have computing capability and provides tasks offloading service is studied. The total energy consumption of the UAV-enabled system, which includes the energy consumption of the UAV and the energy consumption of the ground users, is minimized under the constraints of the UAV’s energy budget, the number of each task’s bits, the causality of the data and the velocity of the UAV. The bits allocation of uploading data, computing data, downloading data and the trajectory of the UAV are jointly optimized with the goal of minimizing the total energy consumption. Moreover, a two-stage alternating algorithm is proposed to solve the non-convex formulated problem. Finally, the simulation results show the superiority of the proposed scheme compared with other benchmark schemes. Finally, the performance of the proposed scheme is demonstrated under different settings.
Linpei Li; Xiangming Wen; Zhaoming Lu; Qi Pan; Wenpeng Jing And Zhiqun Hu. Energy-Efficient UAV-Enabled MEC System: Bits Allocation Optimization and Trajectory Design. Sensors 2019, 19, 4521 .
AMA StyleLinpei Li, Xiangming Wen, Zhaoming Lu, Qi Pan, Wenpeng Jing And Zhiqun Hu. Energy-Efficient UAV-Enabled MEC System: Bits Allocation Optimization and Trajectory Design. Sensors. 2019; 19 (20):4521.
Chicago/Turabian StyleLinpei Li; Xiangming Wen; Zhaoming Lu; Qi Pan; Wenpeng Jing And Zhiqun Hu. 2019. "Energy-Efficient UAV-Enabled MEC System: Bits Allocation Optimization and Trajectory Design." Sensors 19, no. 20: 4521.
Mobile edge caching is regarded as a promising way to reduce the backhaul load of the base stations (BSs). However, the capacity of BSs' cache tends to be small, while mobile users' content preferences are diverse. Furthermore, both the locations of users and user-BS association are uncertain in wireless networks. All of these pose great challenges on the content caching and content delivery. This paper studies the joint optimization of the content placement and content delivery schemes in the cache-enabled ultra-dense small-cell network (UDN) with constrained-backhaul link. Considering the differences in decision time-scales, the content placement and content delivery are investigated separately, but their interplay is taken into consideration. Firstly, a content placement problem is formulated, where the uncertainty of user-BS association is considered. Specifically, different from the existing works, the specific multi-location request pattern is considered that users tend to send content requests from more than one but limited locations during one day. Secondly, a user-BS association and wireless resources allocation problem is formulated, with the objective of maximizing users' data rates under the backhaul bandwidth constraint. Due to the non-convex nature of these two problems, the problem transformation and variables relaxation are adopted, which convert the original problems into more tractable forms. Then, based on the convex optimization methods, a content placement algorithm, and a cache-aware user association and resources allocation algorithm are proposed, respectively. Finally, simulation results are given, which validate that the proposed algorithms have obvious performance advantages in terms of the network utility, the hit ratio of the cache, and the quality of service guarantee, and are suitable for the cache-enabled UDN with constrained-backhaul link.
Wenpeng Jing; Xiangming Wen; Zhaoming Lu; Haijun Zhang. Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN. Sensors 2019, 19, 2449 .
AMA StyleWenpeng Jing, Xiangming Wen, Zhaoming Lu, Haijun Zhang. Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN. Sensors. 2019; 19 (11):2449.
Chicago/Turabian StyleWenpeng Jing; Xiangming Wen; Zhaoming Lu; Haijun Zhang. 2019. "Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN." Sensors 19, no. 11: 2449.
Chenyu Zhang; Wei Zheng; Xiangming Wen; Zhaoming Lu; Luhan Wang; Zhengying Wang. TAP: A High-Precision Network Timing Method Over Air Interface Based on Physical-Layer Signals. IEEE Access 2019, 7, 175959 -175969.
AMA StyleChenyu Zhang, Wei Zheng, Xiangming Wen, Zhaoming Lu, Luhan Wang, Zhengying Wang. TAP: A High-Precision Network Timing Method Over Air Interface Based on Physical-Layer Signals. IEEE Access. 2019; 7 ():175959-175969.
Chicago/Turabian StyleChenyu Zhang; Wei Zheng; Xiangming Wen; Zhaoming Lu; Luhan Wang; Zhengying Wang. 2019. "TAP: A High-Precision Network Timing Method Over Air Interface Based on Physical-Layer Signals." IEEE Access 7, no. : 175959-175969.
Wanqing Guan; Xiangming Wen; Luhan Wang; Zhaoming Lu. On-Demand Cooperation Among Multiple Infrastructure Networks for Multi-Tenant Slicing: a Complex Network Perspective. IEEE Access 2018, 6, 78689 -78699.
AMA StyleWanqing Guan, Xiangming Wen, Luhan Wang, Zhaoming Lu. On-Demand Cooperation Among Multiple Infrastructure Networks for Multi-Tenant Slicing: a Complex Network Perspective. IEEE Access. 2018; 6 ():78689-78699.
Chicago/Turabian StyleWanqing Guan; Xiangming Wen; Luhan Wang; Zhaoming Lu. 2018. "On-Demand Cooperation Among Multiple Infrastructure Networks for Multi-Tenant Slicing: a Complex Network Perspective." IEEE Access 6, no. : 78689-78699.
The rapid development of renewable energy in the energy Internet is expected to alleviate the increasingly severe power problem in data centers, such as the huge power costs and pollution. This paper focuses on the eco-friendly power cost minimization for geo-distributed data centers supplied by multi-source power, where the geographical scheduling of workload and temporal scheduling of batteries' charging and discharging are both considered. Especially, we innovatively propose the Pollution Index Function to model the pollution of different kinds of power, which can encourage the use of cleaner power and improve power savings. We first formulate the eco-friendly power cost minimization problem as a multi-objective and mixed-integer programming problem, and then simplify it as a single-objective problem with integer constraints. Secondly, we propose a Sequential Convex Programming (SCP) algorithm to find the globally optimal non-integer solution of the simplified problem, which is non-convex, and then propose a low-complexity searching method to seek for the quasi-optimal mixed-integer solution of it. Finally, simulation results reveal that our method can improve the clean energy usage up to 50\%--60\% and achieve power cost savings up to 10\%--30\%, as well as reduce the delay of requests.
Chunlei Sun; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Michele Zorzi. Eco-friendly Power Cost Minimization for Geo-distributed Data Centers Considering Workload Scheduling. 2018, 1 .
AMA StyleChunlei Sun, Xiangming Wen, Zhaoming Lu, Wenpeng Jing, Michele Zorzi. Eco-friendly Power Cost Minimization for Geo-distributed Data Centers Considering Workload Scheduling. . 2018; ():1.
Chicago/Turabian StyleChunlei Sun; Xiangming Wen; Zhaoming Lu; Wenpeng Jing; Michele Zorzi. 2018. "Eco-friendly Power Cost Minimization for Geo-distributed Data Centers Considering Workload Scheduling." , no. : 1.
With the new advancements in flight control and integrated circuit (IC) technology, unmanned aerial vehicles (UAVs) have been widely used in various applications. One of the typical application scenarios is data collection for large-scale and remote sensor devices in the Internet of things (IoT). However, due to the characteristics of massive connections, access collisions in the MAC layer lead to high power consumption for both sensor devices and UAVs, and low efficiency for the data collection. In this paper, a dynamic speed control algorithm for UAVs (DSC-UAV) is proposed to maximize the data collection efficiency, while alleviating the access congestion for the UAV-based base stations. With a cellular network considered for support of the communication between sensor devices and drones, the connection establishment process was analyzed and modeled in detail. In addition, the data collection efficiency is also defined and derived. Based on the analytical models, optimal speed under different sensor device densities is obtained and verified. UAVs can dynamically adjust the speed according to the sensor device density under their coverages to keep high data collection efficiency. Finally, simulation results are also conducted to verify the accuracy of the proposed analytical models and show that the DSC-UAV outperforms others with the highest data collection efficiency, while maintaining a high successful access probability, low average access delay, low block probability, and low collision probability.
Qi Pan; Xiangming Wen; Zhaoming Lu; Linpei Li; Wenpeng Jing. Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things. Sensors 2018, 18, 3951 .
AMA StyleQi Pan, Xiangming Wen, Zhaoming Lu, Linpei Li, Wenpeng Jing. Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things. Sensors. 2018; 18 (11):3951.
Chicago/Turabian StyleQi Pan; Xiangming Wen; Zhaoming Lu; Linpei Li; Wenpeng Jing. 2018. "Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things." Sensors 18, no. 11: 3951.
The traffic explosion and the rising of diverse requirements lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. To meet new requirements in the 5G era, service based architecture is introduced into mobile networks. The monolithic network elements (e.g., MME, PGW, etc.) are split into smaller network functions to provide customized services. However, the management and deployment of network functions in service based 5G core network are still big challenges. In this paper, we propose a novel management architecture for 5G service based core network based on NFV and SDN. Combined with SDN, NFV and edge computing, the proposed framework can provide distributed and on-demand deployment of network functions, service guaranteed network slicing, flexible orchestration of network functions and optimal workload allocation. Simulations are conducted to show that the proposed framework and algorithm are effective in terms of reducing network operating cost.
Lu Ma; Xiangming Wen; Luhan Wang; Zhaoming Lu; Raymond Knopp. An SDN/NFV based framework for management and deployment of service based 5G core network. China Communications 2018, 15, 86 -98.
AMA StyleLu Ma, Xiangming Wen, Luhan Wang, Zhaoming Lu, Raymond Knopp. An SDN/NFV based framework for management and deployment of service based 5G core network. China Communications. 2018; 15 (10):86-98.
Chicago/Turabian StyleLu Ma; Xiangming Wen; Luhan Wang; Zhaoming Lu; Raymond Knopp. 2018. "An SDN/NFV based framework for management and deployment of service based 5G core network." China Communications 15, no. 10: 86-98.
Virtualization technology is considered an effective measure to enhance resource utilization and interference management via radio resource abstraction in heterogeneous networks (HetNet). The critical challenge in wireless virtualization is virtual resource allocation on which substantial works have been done. However, most existing researches on virtual resource allocation focus on improving total utility. Different from the existing works, we investigate the dynamic-aware virtual radio resource allocation in virtualization based HetNet considering utility and fairness. A virtual radio resource management framework is proposed, where the radio resources of different physical networks are virtualized into a virtual resource pool and mobile virtual network operators (MVNOs) compete for virtual resources from the pool to provide service to users. A virtual radio resource allocation algorithm based on biological model is developed, considering system utility, fairness, and dynamics. Simulation results are provided to verify that the proposed virtual resource allocation algorithm not only converges within a few iterations, but also achieves a better trade-off between total utility and fairness than existing algorithm. Besides, it can also be utilized to analyze the population dynamics of system.
Lu Ma; Xiangming Wen; Luhan Wang; Zhaoming Lu; Raymond Knopp; Irfan Ghauri. A Biological Model for Resource Allocation and User Dynamics in Virtualized HetNet. Wireless Communications and Mobile Computing 2018, 2018, 1 -11.
AMA StyleLu Ma, Xiangming Wen, Luhan Wang, Zhaoming Lu, Raymond Knopp, Irfan Ghauri. A Biological Model for Resource Allocation and User Dynamics in Virtualized HetNet. Wireless Communications and Mobile Computing. 2018; 2018 ():1-11.
Chicago/Turabian StyleLu Ma; Xiangming Wen; Luhan Wang; Zhaoming Lu; Raymond Knopp; Irfan Ghauri. 2018. "A Biological Model for Resource Allocation and User Dynamics in Virtualized HetNet." Wireless Communications and Mobile Computing 2018, no. : 1-11.
For fifth-generation wireless communication systems, network slicing has emerged as a key concept to meet the diverse requirements of various use cases. By slicing an infrastructure network into multiple dedicated logical networks, wireless networks can support a wide range of services. However, how to fast deploy the end-to-end slices is the main issue in a multi-domain wireless network infrastructure. In this paper, a mathematical model is used to construct network slice requests and map them to the infrastructure network. The mapping process consists of two steps: the placement of virtual network functions and the selection of link paths chaining them. To efficiently utilize the limited physical resources, we pay attention to the service-oriented deployment by offering different deployment policies for three typical slices: eMBB slices, mMTC slices, and uRLLC slices. Furthermore, we adopt complex network theory to obtain the topological information of slices and infrastructure network. With the topological information, we define a node importance metric to rank the nodes in node mapping. To evaluate the performance of deployment policy we proposed, extensive simulations have been conducted. The results have shown that our algorithm performed better in terms of resource efficiency and acceptance ratio. In addition, the average execute time of our algorithm is in a linear growth with the increase of infrastructure network size.
Wanqing Guan; Xiangming Wen; Luhan Wang; Zhaoming Lu; Yidi Shen. A Service-Oriented Deployment Policy of End-to-End Network Slicing Based on Complex Network Theory. IEEE Access 2018, 6, 19691 -19701.
AMA StyleWanqing Guan, Xiangming Wen, Luhan Wang, Zhaoming Lu, Yidi Shen. A Service-Oriented Deployment Policy of End-to-End Network Slicing Based on Complex Network Theory. IEEE Access. 2018; 6 ():19691-19701.
Chicago/Turabian StyleWanqing Guan; Xiangming Wen; Luhan Wang; Zhaoming Lu; Yidi Shen. 2018. "A Service-Oriented Deployment Policy of End-to-End Network Slicing Based on Complex Network Theory." IEEE Access 6, no. : 19691-19701.