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30 March 2019, Volume 3 Issue 1

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Frontier and Comprehensive Review

Support of the Internet of things for energy transformation

Yusheng XUE,Hongbo ZHU,Qin WANG,Haitao ZHAO

2019, 3(1):  1-7.  doi:10.11959/j.issn.2096-3750.2019.00084

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The trend of energy transformation is to integrate smart grid into comprehensive energy.The research method is to establish the framework of energy information,physics and social system research.The active support of power transformation is the guarantee of the success of energy transformation.The proposed scheme emphasized the importance of social factors in practical engineering and research.As a new research methodology,it was compatible with mixed simulation of data,model and behavior.The widely used method in engineering was extended to economics and sociology,and the decision-making method based on subjective experience was made more scientific.In addition,in the definition of the Internet of things,the idea of removing the limitations of the Internet was proposed,and a unified framework was used to reflect the impact of the combination of the Internet/private network and other technologies.

Theory and Technology

Channel state information acquisition algorithm based on deep learning for IoT

Yong LIAO,Haimei YAO,Yuanxiao HUA

2019, 3(1):  8-13.  doi:10.11959/j.issn.2096-3750.2019.00085

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To solve the problem of high feedback overhead when the user sends channel state information (CSI) to the base station in massive multiple input multiple output (MIMO) based on Internet of things system,a CSI feedback network based on deep learning was proposed to feedback CSI.Firstly,the proposed network used convolutional neural network (CNN) to extract channel feature vectors and maxpooling to compress the data.Then the compressed CSI was decompressed by using full connection and CNN to restore the original channel.The simulation results show that compared with the existing CSI feedback methods,the CSI recovered by the proposed CSI feedback network is closer to the original channel,and the reconstruction quality is improved significantly.

Joint resource allocation algorithm for clustering cognitive Internet of things

Xin LIU

2019, 3(1):  14-19.  doi:10.11959/j.issn.2096-3750.2019.00086

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Cognitive Internet of things (CIoT) can improve spectrum utilization effectively through spectrum sensing and sharing,but spectrum sensing may generate overhead.Clustering CIoT was proposed to decrease sensing overhead,whose transmission rate could be improved through joint resource allocation.The network model and frame structure of the CIoT were proposed firstly,and the average transmission rate and interference power of the CIoT were deduced.Then,an optimization model was built to maximize the transmission rate through jointly optimizing the sensing time,sensing cluster head and transmission power,and a joint optimization algorithm was given to solve the optimization problem.Finally,the node clustering and cluster head selection algorithm of the CIoT was presented.The simulations show that the maximal transmission rate through joint resource allocation can be achieved and the transmission performance compared with the traditional schemes can be improved by the proposed scheme.

Research on incentive mechanism for IoT based on mobile hotspot sharing

Huaizhe LIU,Lin GAO

2019, 3(1):  20-29.  doi:10.11959/j.issn.2096-3750.2019.00093

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Many devices in the Internet of things,especially energy-constrained sensor devices,often lack efficient network connectivity.If the networking method based on mobile hotspot sharing is adopted,large-area network coverage can be realized efficiently.The basic idea of the networking mode is to activate some mobile node in the cellular network (such as the holders of smart phones and other smart devices) to open mobile hotspot,provide Wi-Fi connections for resource-constrained node,and satisfy the communication needs of these node,so as to achieve efficient access to the mobile Internet.In this networking mode,how to encourage mobile users to contribute hotspot is the key.The incentive mechanism in mobile hotspot sharing network and the impact on network performance was studied mainly,and a novel incentive mechanism was designed to enable some users to obtain certain benefits by contributing Wi-Fi hotspot.Firstly,the optimal sharing decision of different types of users under the incentive mechanism and the influence of decision-making among different users were studied.Then,the evolution of user behavior,the overall state of the network with time and the equilibrium state of the system were analyzed.The simulation results show that under the equilibrium state of the system,the number of mobile hotspot contributors increases with the increase of free traffic ratio,which also leads to an increase in the number of hotspot.If the price of unit traffic is too high,the number of users will be reduced,which is not conducive to the operation of the network.In addition,compared with the non-hotspot sharing network,if the mobile hotspot sharing networking mode is adopted,the network performance can be increased by up to 148%.

Load-aware user association algorithm based on potential game theory for UDN with CoMP

Jia YU,Yachao LIANG,Shushi GU,Ye WANG

2019, 3(1):  30-36.  doi:10.11959/j.issn.2096-3750.2019.00090

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A load-aware user association (LAUA) algorithm based on potential game theory for ultra dense network (UDN) with coordinated multi-point (CoMP) transmission technique was proposed.LAUA algorithm was capable to balance the load of base stations on the premise of satisfying users’ demand for quality of service,avoid over loading problem in heterogeneous UDN.This algorithm was applicable to the Internet of things application scenario that required uploading vedio data and other data transmission rates.The effectiveness of the proposed algorithm was proved by the simulation experiment.

Performance analysis of dual non-orthogonal multiple access technology in the Internet of things

Dongbo LI,Min JIA,Qing GUO,Xuemai GU,Xiaofeng LIU

2019, 3(1):  37-44.  doi:10.11959/j.issn.2096-3750.2019.00092

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With the rapid development of many technologies such as smart city,artificial intelligence and edge computing,the future Internet of things will face the problems of massive terminal access and spectrum resource constraints.A dual non-orthogonal multiple access (D-NOMA) technology based on high spectral efficiency secure access (HSESA) was proposed,which combined non-orthogonal access in the code domain and non-orthogonal multiplexing in the frequency domain,and had good spectral efficiency performance.The sender and receiver were optimized,and multiple users were mapped directly to the overlapping subcarriers through the sparse codebook.The performance analysis under the Rician channel shows that D-NOMA has better bit error rate performance than HSESA.

Research on multi-target recognition method based on WSN and blind source separation

Pengju HE,Gangyi LIU,Siyi LIU

2019, 3(1):  45-50.  doi:10.11959/j.issn.2096-3750.2019.00095

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Aiming at the problem of signal aliasing in multi-target detection and recognition using wireless sensor network (WSN),a blind source separation algorithm was proposed,which can determine the number of targets and obtain the accurate source signals.In this algorithm,the multichannel mixed signal was used as the analysis object,the number of source signals was determined based on the eigenvalue method and then the blind source separation algorithm based on the non-negative matrix factorization was used to obtain the separation signals.The experimental results indicate that the number of targets can be determined and the accurate separation signals can be obtained by the proposed scheme.It can be applied to solve the problem of signal aliasing in multi-target detection and recognition.

Task collaborative offloading scheme in vehicle multi-access edge computing network

Guanhua QIAO,Supeng LENG,Hao LIU,Kaisheng HUANG,Fan WU

2019, 3(1):  51-59.  doi:10.11959/j.issn.2096-3750.2019.00089

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In order to solve the problem that traditional mobile edge computing network can’t be straightforwardly applied to the Internet of vehicles (IoV) due to high speed mobility and dynamic network topology,a vehicular edge multi-access computing network (VE-MACN) was introduced to realize collaborative computing offloading between roadside units and smart vehicles.In this context,the collaborative computation offloading was formulated as a joint multi-access model selection and task assignment problem to realize the good balance between long-term system utility,diverse needs of IoV applications and energy consumption.Considering the complex joint optimization problem,a deep reinforcement learning-based collaborative computing offloading scheme was designed to overcome the curse of dimensionality for Q-learning algorithm.The simulation results demonstrate that the feasibility and effectiveness of proposed offloading scheme.

Design and implementation of buffer memory management in industrial Internet of things

Chao WU,Chengqun WANG,Shenghong ZHU,Weiqiang XU,Yubo JIA

2019, 3(1):  60-64.  doi:10.11959/j.issn.2096-3750.2019.00088

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Aiming at the problem of how to store traffic jam efficiently in high-speed communication of industrial Internet of things,the method of memory management was introduced.On the basis of researching the storage principle of SDRAM,a SDRAM partition memory management system based on field programmable gate array (FPGA) was designed.FPGA was used as the main controller,SDRAM was divided into two parts:index area and data area.In order to facilitate memory management,SDRAM data was further divided into memory blocks with the same size of 1 kB to achieve the purpose of reading and writing data through index.The simulation and experimental results show that the unreliable problems such as data disorder caused by reading multiple data frames from SDRAM after traffic congestion in high-speed communication can be solved effectively,and the stability of communication system can be improved by the memory management system combined with FIFO.

Privacy cloud storage scheme based on fog computing

Jiyuan ZHOU,Hao LUO,Lei QIU,Tian WANG

2019, 3(1):  65-72.  doi:10.11959/j.issn.2096-3750.2019.00087

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As one of the core applications in cloud computing field,cloud storage attracts a large number of users depending on its powerful storage capacity.However,in this storage schema,users’ data is stored completely in cloud server.In other word,users’ right of control on data is lost and users are facing privacy leakage risk.Traditional privacy protection scheme is usually based on encryption technology,but the attack from the inside of cloud server can’t be resisted effectively by these kinds of methods.Once the password gets compromised,users’ data will be stolen.In order to solve this problem,a three-level secure cloud storage scheme based on fog computing was proposed and a Hash-Solomon code algorithm was designed.A small part of data was stored in local machine and fog server,which can take full advantage of cloud storage and protect the privacy of data.Through the theoretical safety analysis and experimental test,the feasibility of our scheme is proved,and it is really a powerful supplement to existing cloud storage scheme.

Research on energy management of multi-user mobile edge computing offloading

Luyao WANG,Wenqian ZHANG,Guanglin ZHANG

2019, 3(1):  73-81.  doi:10.11959/j.issn.2096-3750.2019.00091

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In mobile edge computing system,the quality of computing experience can be improved greatly by offloading computing tasks from mobile devices to mobile edge computing servers.Consider incorporating renewable energy into a multi-user mobile edge system.Moreover,a battery as an energy harvesting device was added to the model to harvest energy and storage.The task allocation strategy in mobile edge computing system was formulated through the resource management algorithm based on reinforcement learning,which achieved the cost minimization of mobile devices (including delay cost and computing cost).The simulation results show that the proposed algorithm significantly minimizes the cost of mobile devices compared with other algorithms.

Service and Application

Potential and methods of wireless communications for Internet of things based on UAV

Qingheng SONG,Fuchun ZHENG

2019, 3(1):  82-89.  doi:10.11959/j.issn.2096-3750.2019.00096

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In the absence of terrestrial infrastructure for Internet of things (IoT),an effective low-cost wireless connection can be provided by an unmanned aerial vehicle (UAV) based wireless communication platform.Compared with the terrestrial IoT communication platform,the low-altitude UAV wireless communication system enjoys the advantage of rapid deployment,low cost,on-demand deployment,flexible configuration and better communication channel quality due to short-range line-of-sight links.On the other hand,several new challenges must be overcome due to the high mobility and energy consumption limitations of UAV.An overview of UAV enabled IoT wireless communication was provided,including the air-to-ground channel model,the power consumption model,as well as the applications in UAV based data dissemination/collection and relay,with particular reference to the new opportunities and solutions in these application areas.

Application of EdgeFlow mobile edge computing in Internet of things

Shuchang CONG,Chao YAO,Chao YAO,Pengfei WANG,Zijie ZHENG

2019, 3(1):  90-96.  doi:10.11959/j.issn.2096-3750.2019.00098

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In order to meet the requirements of higher computing speed,lower communication delay and higher access density in the future Internet of things,a computational framework of EdgeFlow for mobile edge computing and a task unloading algorithm considering blocking and non-blocking state were proposed.The simulation experiments on the universal software radio platform show that the computational efficiency can be improved significantly and the communication delay can be reduced by EdgeFlow.It points out a new development direction,lays a theoretical and practical foundation for solving the problem of higher computational requirements of the Internet of things.And it will be widely used in the Internet of things scenarios.

3D gesture recognition based on dynamic template matching algorithm for intelligent wearable devices

Yunhe LI

2019, 3(1):  97-105.  doi:10.11959/j.issn.2096-3750.2019.00094

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With the popularity of Internet of things equipment,the smart wearing equipment industry develops rapidly,in which wristband smart bracelets and watches are the mainstream.Intelligent wearable devices have abundant sensors and certain computing power.As human-computer interaction for itself and other devices of the Internet of things through gesture recognition,they have a wide range of needs.A 3D gesture recognition system based on dynamic template matching algorithm was proposed.The gesture meaning was judged by collecting user’s specific gesture from hand-held smart devices,and the control of smart devices was realized by using more natural human-computer interaction technology.The motion sensor of intelligent devices was used to read the corresponding 3D gesture data,and the optimized dynamic time warping algorithm was used to recognize gesture.Based on the characteristics of mobile devices and dynamic programming,the curve path was defined by slope.At the same time,the calculation of template matching and the cost of gesture recognition were reduced by pre-storage distortion threshold.The test is carried out on mobile phones,compared with the traditional algorithm,the proposed algorithm takes less time,has higher recognition efficiency and accuracy,and can bring better human-computer interaction experience.

Current situation and development of municipal engineering Internet of things construction

Baixiang QIANG,Tianli HU,Jiong ZHANG

2019, 3(1):  106-110.  doi:10.11959/j.issn.2096-3750.2019.00099

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The current situation and characteristics of the municipal engineering Internet of things (IoT) system were expounded.The IoT system of municipal engineering based on things,people and things and people was analyzed.And the key problems,the solutions and development directions were put forward.