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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.
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.
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.
Automated driving emerges as a potential technology for safe, convenient, and efficient transportation systems. In order to assist autonomous vehicles with large-volume data dissemination such as high definition (HD) map, cellular network becomes more inevitable to provide vehicles with the ability of accessing Internet. However, due to the bottleneck of wireless bandwidth and the high mobility of vehicles, efficient data dissemination assisted by cellular network is a challenging task. In this work, we investigate the large-volume data dissemination problem for cellular-assisted automated driving within given delay limit. Firstly, a data dissemination scheme is designed that transmits data from the base stations to the target vehicle via a collection of relay vehicles. Secondly, a novel user satisfaction model is derived by considering the vehicular mobility patterns and erasure coding, and the data dissemination is formulated into an optimization problem. Then, to solve this NP-hard problem, a low-complexity dynamic programming based data dissemination solution with edge intelligence is proposed. Finally, by carrying out extensive simulation, the effectiveness of proposed data dissemination scheme for cellular-assisted automated driving is demonstrated, in comparison with the optimal solution based on CPLEX as well as other conventional schemes.
Luning Liu; Zhaoming Lu; Luhan Wang; Xin Chen; Xiangming Wen. Large-volume data dissemination for cellular-assisted automated driving with edge intelligence. Journal of Network and Computer Applications 2020, 155, 102535 .
AMA StyleLuning Liu, Zhaoming Lu, Luhan Wang, Xin Chen, Xiangming Wen. Large-volume data dissemination for cellular-assisted automated driving with edge intelligence. Journal of Network and Computer Applications. 2020; 155 ():102535.
Chicago/Turabian StyleLuning Liu; Zhaoming Lu; Luhan Wang; Xin Chen; Xiangming Wen. 2020. "Large-volume data dissemination for cellular-assisted automated driving with edge intelligence." Journal of Network and Computer Applications 155, no. : 102535.
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.
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.
Xing Zhao; Tao Lei; Zhaoming Lu; Xiangming Wen; Shan Jiang. Introducing Network Situation Awareness into Software Defined Wireless Networks. KSII Transactions on Internet and Information Systems 2018, 12, 1063 -1082.
AMA StyleXing Zhao, Tao Lei, Zhaoming Lu, Xiangming Wen, Shan Jiang. Introducing Network Situation Awareness into Software Defined Wireless Networks. KSII Transactions on Internet and Information Systems. 2018; 12 (3):1063-1082.
Chicago/Turabian StyleXing Zhao; Tao Lei; Zhaoming Lu; Xiangming Wen; Shan Jiang. 2018. "Introducing Network Situation Awareness into Software Defined Wireless Networks." KSII Transactions on Internet and Information Systems 12, no. 3: 1063-1082.
Network function virtualization (NFV) has become an emerging issue in both academia and industry. By outsourcing network functions (NFs) from dedicated hardware to virtualization platform, NFV promises to significantly improve the scalability and flexibility of network management and orchestration. One of the main challenges for NFV deployment is to realize coordinated service function chaining on NFV-based infrastructures. This challenge is referred to as the coordinated NFV resource allocation (coordinated NFV-RA) problem which is proved to be NP-hard. In order to response timely to the service variation, many heuristic or meta-heuristic algorithms are proposed to reduce the computing complexity. However, it is very difficult to evaluate the approach degree between obtained sub-optimal solutions and the optima, since finding the optimal solution is a non-trivial task. In this paper, a novel modeling approach called Homogeneous Link Mapping (HLM) is proposed to find the optimal solutions of a typical three-stage coordinated NFV-RA model with CPLEX. Then we further establish a service function chain (SFC) deployment database with optimal solutions and the results in the database can be used as a criterion to evaluate other SFC algorithms. In order to imitate different practical networks, the SFC deployments are conducted on three type network topologies. And we also analyze the SFC deploying performance on different topologies. Lastly, we make the optimal modeling approach open source, and upload the database on http://www.opensource5g.org/database.
Hang Li; Luhan Wang; Xiangming Wen; Zhaoming Lu; Lu Ma. Constructing Service Function Chain Test Database: An Optimal Modeling Approach for Coordinated Resource Allocation. IEEE Access 2017, 6, 1 -1.
AMA StyleHang Li, Luhan Wang, Xiangming Wen, Zhaoming Lu, Lu Ma. Constructing Service Function Chain Test Database: An Optimal Modeling Approach for Coordinated Resource Allocation. IEEE Access. 2017; 6 (99):1-1.
Chicago/Turabian StyleHang Li; Luhan Wang; Xiangming Wen; Zhaoming Lu; Lu Ma. 2017. "Constructing Service Function Chain Test Database: An Optimal Modeling Approach for Coordinated Resource Allocation." IEEE Access 6, no. 99: 1-1.
To solve the policy optimizing problem in many scenarios of smart wireless network management using a single universal algorithm, this letter proposes a universal learning framework which is called AI Framework based on Deep Reinforcement Learning (DRL). This framework can also solve the problem that the state is painful to design in traditional Reinforcement Learning (RL). This AI Framework adopts Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to model the potential spatial features (i.e. location information) and sequential features from the raw wireless signal automatically. These features can be taken as the state definition of DRL. Meanwhile, this framework is suitable for many scenarios such as resource management and access control due to DRL. The mean value of throughput, the standard deviation of throughput and handover counts are used to evaluate its performance on the mobility management problem in Wireless Local Area Network (WLAN) on a practical testbed. The results show that the framework gets significant improvements and learns intuitive features automatically.
Gang Cao; Zhaoming Lu; Xiangming Wen; Tao Lei; Zhiqun Hu. AIF: An Artificial Intelligence Framework for Smart Wireless Network Management. IEEE Communications Letters 2017, 22, 400 -403.
AMA StyleGang Cao, Zhaoming Lu, Xiangming Wen, Tao Lei, Zhiqun Hu. AIF: An Artificial Intelligence Framework for Smart Wireless Network Management. IEEE Communications Letters. 2017; 22 (2):400-403.
Chicago/Turabian StyleGang Cao; Zhaoming Lu; Xiangming Wen; Tao Lei; Zhiqun Hu. 2017. "AIF: An Artificial Intelligence Framework for Smart Wireless Network Management." IEEE Communications Letters 22, no. 2: 400-403.
To support distributed energy generators and improve energy utilization, energy Internet has attracted global research focus. In China, energy Internet has been proposed as an important issue of government and institutes. However, managing a large amount of distributed generators requires smart, low-latency, reliable, and safe networking infrastructure, which cannot be supported by traditional networks in power grids. In order to design and construct smart and flexible energy Internet, we proposed a software defined network framework with both microgrid cluster level and global grid level designed by a hierarchical manner, which will bring flexibility, efficiency, and reliability for power grid networks. Finally, we evaluate and verify the performance of this framework in terms of latency, reliability, and security by both theoretical analysis and real-world experiments.
Zhaoming Lu; Chunlei Sun; Jinqian Cheng; Yang Li; Yong Li; Xiangming Wen. SDN-Enabled Communication Network Framework for Energy Internet. Journal of Computer Networks and Communications 2017, 2017, 1 -13.
AMA StyleZhaoming Lu, Chunlei Sun, Jinqian Cheng, Yang Li, Yong Li, Xiangming Wen. SDN-Enabled Communication Network Framework for Energy Internet. Journal of Computer Networks and Communications. 2017; 2017 ():1-13.
Chicago/Turabian StyleZhaoming Lu; Chunlei Sun; Jinqian Cheng; Yang Li; Yong Li; Xiangming Wen. 2017. "SDN-Enabled Communication Network Framework for Energy Internet." Journal of Computer Networks and Communications 2017, no. : 1-13.
Due to the rapid growth of mobile data traffic, more and more basestations and access points (APs) have been densely deployed to provide users with ubiquitous network access, which make current wireless network a complex heterogeneous network (HetNet). However, traditional wireless networks are designed with network-centric approaches where different networks have different quality of service (QoS) strategies and cannot easily cooperate with each other to serve network users. Massive network infrastructures could not assure users perceived network and service quality, which is an indisputable fact. To address this issue, we design a new framework for heterogeneous wireless networks with the principle of user-centricity, refactoring the network from users’ perspective to suffice their requirements and preferences. Different from network-centric approaches, the proposed framework takes advantage of Software Defined Networking (SDN) and virtualization technology, which will bring better perceived services quality for wireless network users. In the proposed user-centric framework, control plane and data plane are decoupled to manage the HetNets in a flexible and coadjutant way, and resource virtualization technology is introduced to abstract physical resources of HetNets into unified virtualized resources. Hence, ubiquitous and undifferentiated network connectivity and QoE (quality of experience) driven fine-grained resource management could be achieved for wireless network users.
Zhaoming Lu; Tao Lei; Xiangming Wen; Luhan Wang; Xin Chen. SDN Based User-Centric Framework for Heterogeneous Wireless Networks. Mobile Information Systems 2016, 2016, 1 -9.
AMA StyleZhaoming Lu, Tao Lei, Xiangming Wen, Luhan Wang, Xin Chen. SDN Based User-Centric Framework for Heterogeneous Wireless Networks. Mobile Information Systems. 2016; 2016 ():1-9.
Chicago/Turabian StyleZhaoming Lu; Tao Lei; Xiangming Wen; Luhan Wang; Xin Chen. 2016. "SDN Based User-Centric Framework for Heterogeneous Wireless Networks." Mobile Information Systems 2016, no. : 1-9.
Information security has been received more and more attention for next-generation wireless sensor networks. In this paper, we consider the problem of resource management based on security satisfaction ratio with fairness-aware in two-way relay networks. Multiple source nodes exchange information with the help of relay node in the presence of an eavesdropper, and diverse security requirements are taken into account with coexistence of security users and normal users. The joint problem of power allocation, and subchannel pairing and allocation aims to maximize the security satisfaction ratio for legitimate users subject to limited power and subchannel constraints. We model the security resource management problem as a mixed integer programming problem, which is decomposed into three subproblems, distributed power allocation, distributed subchannel allocation, and distributed subchannel pairing, and then solved it in constraint particle swarm optimization (CPSO), binary CPSO (B_CPSO), and classic Hungarian algorithm (CHA) method, respectively. Moreover, a suboptimal subchannel pairing algorithm is proposed to reduce the computational complexity compared with the CHA. Simulations are conducted to evaluate the effectiveness of the proposed algorithms.
Jun Zhao; Zhaoming Lu; Xiangming Wen; Haijun Zhang; Shenghua He; Wenpeng Jing. Resource Management Based on Security Satisfaction Ratio with Fairness-Aware in Two-Way Relay Networks. International Journal of Distributed Sensor Networks 2015, 11, 1 .
AMA StyleJun Zhao, Zhaoming Lu, Xiangming Wen, Haijun Zhang, Shenghua He, Wenpeng Jing. Resource Management Based on Security Satisfaction Ratio with Fairness-Aware in Two-Way Relay Networks. International Journal of Distributed Sensor Networks. 2015; 11 (7):1.
Chicago/Turabian StyleJun Zhao; Zhaoming Lu; Xiangming Wen; Haijun Zhang; Shenghua He; Wenpeng Jing. 2015. "Resource Management Based on Security Satisfaction Ratio with Fairness-Aware in Two-Way Relay Networks." International Journal of Distributed Sensor Networks 11, no. 7: 1.
When a group of machine type communication (MTC) ‘smart mobile devices’ in vehicular area network move together as a single unit, the network requires to resolve how to manage the group-based location transition and handoff for all group members with efficient signaling exchange and congestion mitigation. As an attractive solution, the Session Initiation Protocol (SIP) based Network Mobility (SIP-NEMO) has attracted much interests among the industry and academia. However, SIP-NEMO is vulnerable to the simultaneous handoff problem and weak in supporting seamless services, because of the direct binding updates between both mobile SIP nodes, as well as a potentially large number of mobile devices. In this paper, we investigate a novel group-based SIP sessions mobility management scheme for the MTC devices that are onboard traveling among long term evolution base stations. Firstly, some novel basic attributes of the SIP protocol are defined and the corresponding key SIP session procedures, including session setup, location registration and location update, are optimized. Then, we propose a predictive resource reservation algorithm for group-based handoff to achieve seamless services. Furthermore, we develop an analytical model to study the performance from the aspect of the average handoff delay. The simulation results indicate that the network congestion caused by the simultaneous handoff of a group of MTC devices onboard could be reduced effectively.
Yang Shimin; Wen Xiangming; Lu Zhaoming. Group-Based Predictive Handoff for SIP Sessions in Vehicular M2M Network Mobility Management. Wireless Personal Communications 2015, 84, 3109 -3125.
AMA StyleYang Shimin, Wen Xiangming, Lu Zhaoming. Group-Based Predictive Handoff for SIP Sessions in Vehicular M2M Network Mobility Management. Wireless Personal Communications. 2015; 84 (4):3109-3125.
Chicago/Turabian StyleYang Shimin; Wen Xiangming; Lu Zhaoming. 2015. "Group-Based Predictive Handoff for SIP Sessions in Vehicular M2M Network Mobility Management." Wireless Personal Communications 84, no. 4: 3109-3125.