Pub Date : 2020-08-01DOI: 10.1109/SmartIoT49966.2020.00057
Qingguang Yu, Zhicheng Jiang, Yuming Liu, G. Long
With the development of the nearly zero energy buildings (NEZB) technology and IOT, people have higher requirements for power energy management. In this paper, design and accomplishment of control strategy with IOT based on NEZB in smart microgrid were proposed. The structure of smart microgrid supervisory control and data acquisition (SCADA) system was designed to achieve online monitoring of energy consumption and environment parameters. The control strategy of power management was carried out. Finally, the designed control strategy of smart microgrid is adopted in the actual project of NEZB.
{"title":"Research of Power Energy Management Control Strategy with IOT in NZEB","authors":"Qingguang Yu, Zhicheng Jiang, Yuming Liu, G. Long","doi":"10.1109/SmartIoT49966.2020.00057","DOIUrl":"https://doi.org/10.1109/SmartIoT49966.2020.00057","url":null,"abstract":"With the development of the nearly zero energy buildings (NEZB) technology and IOT, people have higher requirements for power energy management. In this paper, design and accomplishment of control strategy with IOT based on NEZB in smart microgrid were proposed. The structure of smart microgrid supervisory control and data acquisition (SCADA) system was designed to achieve online monitoring of energy consumption and environment parameters. The control strategy of power management was carried out. Finally, the designed control strategy of smart microgrid is adopted in the actual project of NEZB.","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"261 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115216819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/SmartIoT49966.2020.00029
Cankut Ergen, B. Gulbahar
Potential of intrusion during smart meter data collection is an important problem for household privacy in next-generation smart homes. There are various privacy protection methods such as hiding the real usage with renewable batteries (RBs) and encrypted communication. There are privacy threats due to the detection of the energy transfer through RBs while encryption-based methods result in high computational complexity. In this study, a novel privacy improvement mechanism is proposed based on the routing of energy through multiple smart meters among multiple houses in a neighborhood. The optimization of privacy based on uniform randomization is theoretically modeled and some heuristic solutions are presented. In this method, energy transfer is randomly distributed among multiple smart meters, real usage of a house is buffered with the RB and smart meter indices are randomly selected. In numerical simulations, privacy improvement is shown by utilizing the random selection of smart meter indices for randomizing the energy routing and the buffers of RBs. Furthermore, energy privacy (EP) metric validating the simulation results is defined. Energy routing with multiple smart meters provides a practical and low complexity privacy protection mechanism for next-generation smart grid architectures.
{"title":"Theoretical Modelling of Smart Meter Privacy Protection with Multi-meter Energy Routing","authors":"Cankut Ergen, B. Gulbahar","doi":"10.1109/SmartIoT49966.2020.00029","DOIUrl":"https://doi.org/10.1109/SmartIoT49966.2020.00029","url":null,"abstract":"Potential of intrusion during smart meter data collection is an important problem for household privacy in next-generation smart homes. There are various privacy protection methods such as hiding the real usage with renewable batteries (RBs) and encrypted communication. There are privacy threats due to the detection of the energy transfer through RBs while encryption-based methods result in high computational complexity. In this study, a novel privacy improvement mechanism is proposed based on the routing of energy through multiple smart meters among multiple houses in a neighborhood. The optimization of privacy based on uniform randomization is theoretically modeled and some heuristic solutions are presented. In this method, energy transfer is randomly distributed among multiple smart meters, real usage of a house is buffered with the RB and smart meter indices are randomly selected. In numerical simulations, privacy improvement is shown by utilizing the random selection of smart meter indices for randomizing the energy routing and the buffers of RBs. Furthermore, energy privacy (EP) metric validating the simulation results is defined. Energy routing with multiple smart meters provides a practical and low complexity privacy protection mechanism for next-generation smart grid architectures.","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122474073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/SmartIoT49966.2020.00011
Axida Shan, Xiumei Fan, Xinghui Zhang
Mobile ad hoc networks (MANETs) are kinds of wireless networks that are various features like dynamic mobility, constraint resources, fully decentralized etc. The communication among the nodes highly depends on the cooperation between nodes. Data forwarding is the main task during the communication process. Because of constraint of limited resources, it is rational that some nodes behave selfishly and refuse to burden forwarding tasks for others. In this paper, we quantitatively investigate the impacts of node selfishness in MANETs from various aspects, including mobility, presence, and combination of selfish nodes. The network performance is assessed in terms of average packet delivery ratio and average end-to-end delay. We carried out extensive simulations on OMNeT++ platform and analyzed the results. Our results quantitatively showed that node selfishness has significant impacts on the communication performance in MANETs. As a result, our experimental results imply that the impact of node selfishness should be evaluated in an integrated way of mobility, presence and combination.
{"title":"Quantitative Study on Impact of Node Selfishness on Performance of MANETs","authors":"Axida Shan, Xiumei Fan, Xinghui Zhang","doi":"10.1109/SmartIoT49966.2020.00011","DOIUrl":"https://doi.org/10.1109/SmartIoT49966.2020.00011","url":null,"abstract":"Mobile ad hoc networks (MANETs) are kinds of wireless networks that are various features like dynamic mobility, constraint resources, fully decentralized etc. The communication among the nodes highly depends on the cooperation between nodes. Data forwarding is the main task during the communication process. Because of constraint of limited resources, it is rational that some nodes behave selfishly and refuse to burden forwarding tasks for others. In this paper, we quantitatively investigate the impacts of node selfishness in MANETs from various aspects, including mobility, presence, and combination of selfish nodes. The network performance is assessed in terms of average packet delivery ratio and average end-to-end delay. We carried out extensive simulations on OMNeT++ platform and analyzed the results. Our results quantitatively showed that node selfishness has significant impacts on the communication performance in MANETs. As a result, our experimental results imply that the impact of node selfishness should be evaluated in an integrated way of mobility, presence and combination.","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128457462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/SmartIoT49966.2020.00058
M. Ao, Xin Zhang
The problem of overheads caused by resource allocation in vehicle ad hoc network (VANET) has become an issue attracting more and more attention. Recently, 3GPP has introduced channel state information (CSI) report into NR V2X as a new and important technical feature. Therefore, by considering the channel state of the vehicle nodes, this paper proposes an improved permutation model based on our previous work where the overheads related to channel state were not treated in a differentiated manner. It is assumed that the nodes in good channel state would have priority to occupy resources first, while the nodes in bad channel state are not allowed to participate in resource allocation, and the CSIs representing bad channel state are assumed to be compressed or saved. In this way, the overheads of resource allocation in VANET can be reduced, thus leading to the potential performance improvement of the overall system. This result is verified by simulation experiments, which show the proposed model may work as a better optimizing guideline for achieving good performance gain.
{"title":"Analysis of Resource Allocation Overheads in Vehicle Ad Hoc Network Considering CSI","authors":"M. Ao, Xin Zhang","doi":"10.1109/SmartIoT49966.2020.00058","DOIUrl":"https://doi.org/10.1109/SmartIoT49966.2020.00058","url":null,"abstract":"The problem of overheads caused by resource allocation in vehicle ad hoc network (VANET) has become an issue attracting more and more attention. Recently, 3GPP has introduced channel state information (CSI) report into NR V2X as a new and important technical feature. Therefore, by considering the channel state of the vehicle nodes, this paper proposes an improved permutation model based on our previous work where the overheads related to channel state were not treated in a differentiated manner. It is assumed that the nodes in good channel state would have priority to occupy resources first, while the nodes in bad channel state are not allowed to participate in resource allocation, and the CSIs representing bad channel state are assumed to be compressed or saved. In this way, the overheads of resource allocation in VANET can be reduced, thus leading to the potential performance improvement of the overall system. This result is verified by simulation experiments, which show the proposed model may work as a better optimizing guideline for achieving good performance gain.","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123090106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An Internet-of-Things (IoT) system is generally composed of endpoint clients, network devices, and cloud servers. As such, data transfers in the network are full of security concerns. Besides, coming booming IoT applications will accelerate the network infrastructure to provide timely and safe information exchange services. Existing network could have a shortcoming of static key authentication. To enable an automatic key-update mechanism for IoT devices to enhance security in Machine-toĮMachine (M2M) communications, we implemented a lightweight key-update mechanism based on the libcoap library. Experimental results show that just 1.03% latency overhead is added for a better security performance.
{"title":"An Automatic Key-update Mechanism for M2M Communication and IoT Security Enhancement","authors":"Weng-Chung Tsai, Tzu-Hsuan Tsai, Guang-Hao Xiao, Te-Jen Wang, Yu-Ruei Lian, Song-Hao Huang","doi":"10.1109/SmartIoT49966.2020.00067","DOIUrl":"https://doi.org/10.1109/SmartIoT49966.2020.00067","url":null,"abstract":"An Internet-of-Things (IoT) system is generally composed of endpoint clients, network devices, and cloud servers. As such, data transfers in the network are full of security concerns. Besides, coming booming IoT applications will accelerate the network infrastructure to provide timely and safe information exchange services. Existing network could have a shortcoming of static key authentication. To enable an automatic key-update mechanism for IoT devices to enhance security in Machine-toĮMachine (M2M) communications, we implemented a lightweight key-update mechanism based on the libcoap library. Experimental results show that just 1.03% latency overhead is added for a better security performance.","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"111 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132058364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/SmartIoT49966.2020.00031
V. K. Nguyen, Minh-Hieu Phan, W. Zhang, Quan Z. Sheng, T. D. Vo
Appliance Load Monitoring (ALM) has become a crucial task in energy sector since the residential loads have been ever-increasing in the recent years. Several studies have been undertaken to monitor energy consumption of household appliances while also analyze the power data to obtain more useful insights of consumers’ behaviors. The remaining challenge of the recent approaches is automatic appliance recognition. In this work, we propose a novel hybrid method which includes two main processes, namely the feature importance process and the appliance identification process. In the first phase, feature importance process extracts the temporal trends. We then replace the classification layer of Convolutional Neural Network (CNN) by the SVM classifier; thereby achieving a set of important features which is data input for the next phase. After that, we set the CNN’s weights based on the analyzed feature importance of SVM, instead of initializing weights randomly. As a result, the proposed method of this study outperformed other approaches with more than 90% for both of accuracy and macro F1-score.
{"title":"A Hybrid Approach for Intrusive Appliance Load Monitoring in Smart Home","authors":"V. K. Nguyen, Minh-Hieu Phan, W. Zhang, Quan Z. Sheng, T. D. Vo","doi":"10.1109/SmartIoT49966.2020.00031","DOIUrl":"https://doi.org/10.1109/SmartIoT49966.2020.00031","url":null,"abstract":"Appliance Load Monitoring (ALM) has become a crucial task in energy sector since the residential loads have been ever-increasing in the recent years. Several studies have been undertaken to monitor energy consumption of household appliances while also analyze the power data to obtain more useful insights of consumers’ behaviors. The remaining challenge of the recent approaches is automatic appliance recognition. In this work, we propose a novel hybrid method which includes two main processes, namely the feature importance process and the appliance identification process. In the first phase, feature importance process extracts the temporal trends. We then replace the classification layer of Convolutional Neural Network (CNN) by the SVM classifier; thereby achieving a set of important features which is data input for the next phase. After that, we set the CNN’s weights based on the analyzed feature importance of SVM, instead of initializing weights randomly. As a result, the proposed method of this study outperformed other approaches with more than 90% for both of accuracy and macro F1-score.","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132004185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/smartiot49966.2020.00002
{"title":"SmartIoT 2020 Commentary","authors":"","doi":"10.1109/smartiot49966.2020.00002","DOIUrl":"https://doi.org/10.1109/smartiot49966.2020.00002","url":null,"abstract":"","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"60 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130836522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/SmartIoT49966.2020.00010
K. Mayes
The Internet of Things (IoT) may be considered as a distributed, critical infrastructure, consisting of billions of devices, many of which having limited processing capability. However, the security of IoT must not be compromised by these limitations, and defenses need to protect against today's threats, and those predicted for the future. This requires protection against implementation attacks, as well as the ability to load, replace and run, best-practice cryptographic algorithms. Post-Quantum cryptographic algorithms are attracting great interest, and NIST standardization has a competition to find the best. Prior research demonstrated that a Learning With Errors candidate algorithm could be implemented on a smart card chip, however this was a low-level implementation, and not representative of loading the algorithm onto a secured IoT chip platform. In this paper we present analysis from a practical implementation of the Kyber768 CPAPKE public key encryption component on a MULTOS IoT Trust-Anchor chip. The investigation considered memory and speed requirements, and optimizations, and compared the NTT transform version of Kyber, presented in Round 1 of the NIST competition, with the Kroenecker multiplier technique that exploits a hardware crypto-coprocessor. The work began with a generic multi-round multiplier approach, which was then improved using a novel modification of the input data, allowing a built-in modular multiply function to be used, significantly increasing the speed of a multiplication round, and doubling the useable size of the hardware multiplier.
{"title":"Performance Evaluation and Optimisation for Kyber on the MULTOS IoT Trust-Anchor","authors":"K. Mayes","doi":"10.1109/SmartIoT49966.2020.00010","DOIUrl":"https://doi.org/10.1109/SmartIoT49966.2020.00010","url":null,"abstract":"The Internet of Things (IoT) may be considered as a distributed, critical infrastructure, consisting of billions of devices, many of which having limited processing capability. However, the security of IoT must not be compromised by these limitations, and defenses need to protect against today's threats, and those predicted for the future. This requires protection against implementation attacks, as well as the ability to load, replace and run, best-practice cryptographic algorithms. Post-Quantum cryptographic algorithms are attracting great interest, and NIST standardization has a competition to find the best. Prior research demonstrated that a Learning With Errors candidate algorithm could be implemented on a smart card chip, however this was a low-level implementation, and not representative of loading the algorithm onto a secured IoT chip platform. In this paper we present analysis from a practical implementation of the Kyber768 CPAPKE public key encryption component on a MULTOS IoT Trust-Anchor chip. The investigation considered memory and speed requirements, and optimizations, and compared the NTT transform version of Kyber, presented in Round 1 of the NIST competition, with the Kroenecker multiplier technique that exploits a hardware crypto-coprocessor. The work began with a generic multi-round multiplier approach, which was then improved using a novel modification of the input data, allowing a built-in modular multiply function to be used, significantly increasing the speed of a multiplication round, and doubling the useable size of the hardware multiplier.","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116697432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/SmartIoT49966.2020.00060
Zhijie Ma, Qinglin Zhao, Jianwen Yuan, Xiaobo Zhou, Li Feng
In Blockchain, fork is a fundamental impediment to consensus mechanisms such as Proof-of-Work (PoW). In this paper, we study the fork probability of the famous Proof-of-Useful-Work (PoUW) consensus mechanism, which has recently been proposed to solve the huge waste of computing resources in PoW. With PoUW, each miner first does useful work (e.g., data classification), and then competes for the leader according to the number of the executed CPU instructions. Compared with conventional factors such as network delay, the time of doing useful work is a new and salient factor leading to a fork for a PoUW-based blockchain. Taking into account some important factors (e.g., the time of doing useful work, computational power, network delay), we propose a theoretical model to characterize the impact of these factors on the PoUW fork probability. Extensive simulations verify that our model is very accurate. This study is helpful for providing guidance of configuring PoUW parameters.
{"title":"Fork Probability Analysis of PoUW Consensus Mechanism","authors":"Zhijie Ma, Qinglin Zhao, Jianwen Yuan, Xiaobo Zhou, Li Feng","doi":"10.1109/SmartIoT49966.2020.00060","DOIUrl":"https://doi.org/10.1109/SmartIoT49966.2020.00060","url":null,"abstract":"In Blockchain, fork is a fundamental impediment to consensus mechanisms such as Proof-of-Work (PoW). In this paper, we study the fork probability of the famous Proof-of-Useful-Work (PoUW) consensus mechanism, which has recently been proposed to solve the huge waste of computing resources in PoW. With PoUW, each miner first does useful work (e.g., data classification), and then competes for the leader according to the number of the executed CPU instructions. Compared with conventional factors such as network delay, the time of doing useful work is a new and salient factor leading to a fork for a PoUW-based blockchain. Taking into account some important factors (e.g., the time of doing useful work, computational power, network delay), we propose a theoretical model to characterize the impact of these factors on the PoUW fork probability. Extensive simulations verify that our model is very accurate. This study is helpful for providing guidance of configuring PoUW parameters.","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125885867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.1109/SmartIoT49966.2020.00035
Xuelei Zhao, Xinsheng Ji, Shuxin Liu, Zanyuan He
Link prediction aims to predict undetected or unknown links through network information. Most prediction indicators depend on local topology but ignore the pivot role of nodes. Aiming at the problem of topological sparseness in some directed scale-free networks, a preference attachment method based on Shannon theory is proposed to measure the relevance of information from the perspective of nodes. This paper defined the nodes self-information while analyzing nodes interaction process and the conditional information while analyzing the conditional probability of effective interaction based on information theory, and use them designed a new predict indicator. Experiments on 9 scale-free networks show that the proposed method has a better improvement under the Precision metrics.
{"title":"Link Prediction Based on Information Preference Connection for Directed Network","authors":"Xuelei Zhao, Xinsheng Ji, Shuxin Liu, Zanyuan He","doi":"10.1109/SmartIoT49966.2020.00035","DOIUrl":"https://doi.org/10.1109/SmartIoT49966.2020.00035","url":null,"abstract":"Link prediction aims to predict undetected or unknown links through network information. Most prediction indicators depend on local topology but ignore the pivot role of nodes. Aiming at the problem of topological sparseness in some directed scale-free networks, a preference attachment method based on Shannon theory is proposed to measure the relevance of information from the perspective of nodes. This paper defined the nodes self-information while analyzing nodes interaction process and the conditional information while analyzing the conditional probability of effective interaction based on information theory, and use them designed a new predict indicator. Experiments on 9 scale-free networks show that the proposed method has a better improvement under the Precision metrics.","PeriodicalId":399187,"journal":{"name":"2020 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124285003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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