Pub Date : 2018-10-01DOI: 10.1109/CYBERC.2018.00059
Jiping Chen, Huijuan Wu, Xiangrong Liu, Yao Xiao, Mengjiao Wang, Mingru Yang, Y. Rao
Intelligent event recognition along the fiber is still a challenging problem in long distance pipeline monitoring with distributed optical fiber sensors (DOFS), because the complicated burying environments are changing from time to time, and the interference sources are unpredictable at different fiber locations. The fixed hand crafted feature extraction is always time-consuming and laborious, and the update of algorithm always lags behind the environmental change, which restricts its practical scale applications. Thus in this paper, we propose a real-time distributed deep learning model by using the efficient 1-D convolutional neural network (1-D CNN), to learn the distinguishable features of different disturbances and identify them automatically by training the raw event data (signal), which also can be updated easily. The experimental results from the real field data for the safety monitoring of oil pipelines demonstrate the effectiveness of the proposed method, which performs better than the 2-D CNN in terms of both recognition metrics and speed.
{"title":"A Real-Time Distributed Deep Learning Approach for Intelligent Event Recognition in Long Distance Pipeline Monitoring with DOFS","authors":"Jiping Chen, Huijuan Wu, Xiangrong Liu, Yao Xiao, Mengjiao Wang, Mingru Yang, Y. Rao","doi":"10.1109/CYBERC.2018.00059","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00059","url":null,"abstract":"Intelligent event recognition along the fiber is still a challenging problem in long distance pipeline monitoring with distributed optical fiber sensors (DOFS), because the complicated burying environments are changing from time to time, and the interference sources are unpredictable at different fiber locations. The fixed hand crafted feature extraction is always time-consuming and laborious, and the update of algorithm always lags behind the environmental change, which restricts its practical scale applications. Thus in this paper, we propose a real-time distributed deep learning model by using the efficient 1-D convolutional neural network (1-D CNN), to learn the distinguishable features of different disturbances and identify them automatically by training the raw event data (signal), which also can be updated easily. The experimental results from the real field data for the safety monitoring of oil pipelines demonstrate the effectiveness of the proposed method, which performs better than the 2-D CNN in terms of both recognition metrics and speed.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125762250","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 : 2018-10-01DOI: 10.1109/CYBERC.2018.00039
R. Kodali, Krishna Yogi Borra, N. SharanSaiG., Honey Jehova Domma
Internet of Things (IoT) plays a fundamental role in connecting the ecological things around us to a network. It helps us monitor the parameters of the things with the usage of sensors that are familiarize for remote sensing of the specific data and forward the information over the network cloud by means of Internet Connection. This paper centers around the idea of knowing the status of parking availability in a parking lot through Internet with the help of Internet of Things Technology. This uses Ultrasonic sensor to detect the vehicle in the parking slot, TTGO-ESP32-LoRa (transmitter) boards placed at different parking lots in different places to transmit the data. TTGO-ESP32-LoRa (receiver) receives the data which is placed near to the parking lots and also sends the slot information to IBM Watson IoT platform through WiFi protocol present in the Esp32 board. The status of the parking availability can also be viewed in the Android Phone
{"title":"An IoT Based Smart Parking System Using LoRa","authors":"R. Kodali, Krishna Yogi Borra, N. SharanSaiG., Honey Jehova Domma","doi":"10.1109/CYBERC.2018.00039","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00039","url":null,"abstract":"Internet of Things (IoT) plays a fundamental role in connecting the ecological things around us to a network. It helps us monitor the parameters of the things with the usage of sensors that are familiarize for remote sensing of the specific data and forward the information over the network cloud by means of Internet Connection. This paper centers around the idea of knowing the status of parking availability in a parking lot through Internet with the help of Internet of Things Technology. This uses Ultrasonic sensor to detect the vehicle in the parking slot, TTGO-ESP32-LoRa (transmitter) boards placed at different parking lots in different places to transmit the data. TTGO-ESP32-LoRa (receiver) receives the data which is placed near to the parking lots and also sends the slot information to IBM Watson IoT platform through WiFi protocol present in the Esp32 board. The status of the parking availability can also be viewed in the Android Phone","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127285357","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 : 2018-10-01DOI: 10.1109/CYBERC.2018.00014
Liping Li, Qinglei Zhou, Bin Li, Xueming Si
Identity authentication is the first line of defense to ensure the security of information systems, and passwords are the most widely used authentication method. Choosing a valid password structure is an effective way to prevent password attacks, such as password dictionary attack. This article talked 68386069 real plaintext passwords with statistical their various features, summarized several rules for generating highly utilized passwords in certain styles. Based on these statistical features and rules, it generated high-probability password structure gene banks. With them, it formulates a dictionary to generate the candidate passwords. Thereby, this can enhance the efficiency of password recovery. We conducted extensive experiments by the real password test data, and the experimental results, compared with the dictionary provided by major websites, show that the dictionary of high probability password structure hit rate increased by about 30%. At the same time, this dictionary can save about one-third of the running time.
{"title":"An Algorithm to Generate Password Structure Dictionary Based on Gene Bank","authors":"Liping Li, Qinglei Zhou, Bin Li, Xueming Si","doi":"10.1109/CYBERC.2018.00014","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00014","url":null,"abstract":"Identity authentication is the first line of defense to ensure the security of information systems, and passwords are the most widely used authentication method. Choosing a valid password structure is an effective way to prevent password attacks, such as password dictionary attack. This article talked 68386069 real plaintext passwords with statistical their various features, summarized several rules for generating highly utilized passwords in certain styles. Based on these statistical features and rules, it generated high-probability password structure gene banks. With them, it formulates a dictionary to generate the candidate passwords. Thereby, this can enhance the efficiency of password recovery. We conducted extensive experiments by the real password test data, and the experimental results, compared with the dictionary provided by major websites, show that the dictionary of high probability password structure hit rate increased by about 30%. At the same time, this dictionary can save about one-third of the running time.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133689956","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 : 2018-10-01DOI: 10.1109/CYBERC.2018.00064
Hui Huang, Chunlong Li, Chao Wu, Fan Wu, Luming Li
In wireless sensor network, nodes with limited energy bring negative impact of network data aggregation. This paper solves the problem based on the RF transfer technology. We first study the impact of simultaneous transmission of wireless information and energy method SWIPT on data aggregation energy consumption, and obtains the result that the TS-SWIPT method can improve the initial energy efficiency of the node, and use node's redundancy energy to optimize the energy efficiency of the network. The paper also proposes an energy transfer time slot optimization method CSAS to develop an efficient TS-SWIPT transmission strategy. In order to solve the CSAS slot allocation problem, a heuristic algorithm is given to obtain a set of feasible solutions reasonably and effectively based on the energy consumption distribution of nodes. The final simulation results show that the CSAS allocation strategy can make reasonable use of the node's redundant energy, improve the initial energy efficiency of the node, and prolong the life of the high-load node. Compared with the DOEE algorithm which does not use the TS-SWIPT method, the proposed algorithm improves the performance of network lifetime and total data aggregation to some degree.
{"title":"Energy Efficiency Optimization Method Under the Scene of Wireless Information and Energy Simultaneous Transmission","authors":"Hui Huang, Chunlong Li, Chao Wu, Fan Wu, Luming Li","doi":"10.1109/CYBERC.2018.00064","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00064","url":null,"abstract":"In wireless sensor network, nodes with limited energy bring negative impact of network data aggregation. This paper solves the problem based on the RF transfer technology. We first study the impact of simultaneous transmission of wireless information and energy method SWIPT on data aggregation energy consumption, and obtains the result that the TS-SWIPT method can improve the initial energy efficiency of the node, and use node's redundancy energy to optimize the energy efficiency of the network. The paper also proposes an energy transfer time slot optimization method CSAS to develop an efficient TS-SWIPT transmission strategy. In order to solve the CSAS slot allocation problem, a heuristic algorithm is given to obtain a set of feasible solutions reasonably and effectively based on the energy consumption distribution of nodes. The final simulation results show that the CSAS allocation strategy can make reasonable use of the node's redundant energy, improve the initial energy efficiency of the node, and prolong the life of the high-load node. Compared with the DOEE algorithm which does not use the TS-SWIPT method, the proposed algorithm improves the performance of network lifetime and total data aggregation to some degree.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131449206","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}
In order to simplify the detection complexity of the receiver and improve the bit error rate (BER) performance of the two-group Alamouti system in correlated channel, we design a nonlinear precoding scheme for two-group Alamouti system in multiple input multiple output (MIMO) correlated channel in this paper. We apply the geometric mean decomposition (GMD) algorithm to the equivalent channel matrix and the dirty paper coding (DPC) technique to the transmitter of the system. Thus, interference between signals can be eliminated at the transmitter, meanwhile, sub-channel with equal gain are obtained. However, a high peak power ratio is caused by the dirty paper coding technique at the transmitter. To solve this problem, Tomlinson-Harashima Precoding (THP) with modulo operation is applied to the transmitter. From the simulation results, it is observed that the proposed system can significantly improve the BER performance as well as Peak-to-Average Power Ratio (PAPR) performance.
{"title":"A Nonlinear Precoding Design for Two-Group Alamouti System in MIMO Correlated Channel","authors":"Yingbo Shang, Xinying Guo, Youyou Zhao, X. Mu, Jiankang Zhang","doi":"10.1109/CYBERC.2018.00068","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00068","url":null,"abstract":"In order to simplify the detection complexity of the receiver and improve the bit error rate (BER) performance of the two-group Alamouti system in correlated channel, we design a nonlinear precoding scheme for two-group Alamouti system in multiple input multiple output (MIMO) correlated channel in this paper. We apply the geometric mean decomposition (GMD) algorithm to the equivalent channel matrix and the dirty paper coding (DPC) technique to the transmitter of the system. Thus, interference between signals can be eliminated at the transmitter, meanwhile, sub-channel with equal gain are obtained. However, a high peak power ratio is caused by the dirty paper coding technique at the transmitter. To solve this problem, Tomlinson-Harashima Precoding (THP) with modulo operation is applied to the transmitter. From the simulation results, it is observed that the proposed system can significantly improve the BER performance as well as Peak-to-Average Power Ratio (PAPR) performance.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134365207","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 : 2018-10-01DOI: 10.1109/CYBERC.2018.00061
Jian Zhang, Yaozong Pan
Bike-sharing systems allow people to rent a bicycle at a near dock, ride for a short journey and return it to any dock near your destination. In bike-sharing systems, dock location and capacity planning are two key issues that bike managers should solve. In this paper, station capacity and bike rebalancing are mainly considered. We propose three indexes for visualization. A novel visual method is put forward, which is used to analyze large-scale taxi and bike-sharing data conjointly for planning the scale of bicycle docks. We can get more important information through the visualization of taxi and bike data than only use of bicycle data. It is evaluated based on the Citibike and yellow_taxi data. The results indicate that the visual method we present is very effective in planning station capacity and in bike rebalancing operations.
{"title":"Planning Station Capacity and Bike Rebalance Based on Visual Analytics of Taxi and Bike-Sharing Data","authors":"Jian Zhang, Yaozong Pan","doi":"10.1109/CYBERC.2018.00061","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00061","url":null,"abstract":"Bike-sharing systems allow people to rent a bicycle at a near dock, ride for a short journey and return it to any dock near your destination. In bike-sharing systems, dock location and capacity planning are two key issues that bike managers should solve. In this paper, station capacity and bike rebalancing are mainly considered. We propose three indexes for visualization. A novel visual method is put forward, which is used to analyze large-scale taxi and bike-sharing data conjointly for planning the scale of bicycle docks. We can get more important information through the visualization of taxi and bike data than only use of bicycle data. It is evaluated based on the Citibike and yellow_taxi data. The results indicate that the visual method we present is very effective in planning station capacity and in bike rebalancing operations.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126284483","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 : 2018-10-01DOI: 10.1109/CYBERC.2018.00062
Xiaofen Gu, Hao Zhou, Lei Fan
The growing volume of credit card and personal loan applications has spurred the need for financial institutions to improve their credit scoring methods to make intelligent decisions. In this paper, we introduce a novel credit scoring framework based on transaction sequence classification. This framework involves a CNN-based structure for sequential feature extraction. It can be applied to both raw transaction sequences and feature matrixes aggregated by time window to capture short-term and long-term sequential features. Other non-sequential personal features are also integrated to the model to help making the final decision. In the experiments, evaluations on the performance of model-based, feature-based sequence classification and the whole framework are done respectively. Our sequence classification method as well as the credit scoring framework outperforms other state-of-art methods in the experiments on real-world labelled application and transaction data from a major payment organization.
{"title":"Credit Scoring Based on Transaction Sequence Classification","authors":"Xiaofen Gu, Hao Zhou, Lei Fan","doi":"10.1109/CYBERC.2018.00062","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00062","url":null,"abstract":"The growing volume of credit card and personal loan applications has spurred the need for financial institutions to improve their credit scoring methods to make intelligent decisions. In this paper, we introduce a novel credit scoring framework based on transaction sequence classification. This framework involves a CNN-based structure for sequential feature extraction. It can be applied to both raw transaction sequences and feature matrixes aggregated by time window to capture short-term and long-term sequential features. Other non-sequential personal features are also integrated to the model to help making the final decision. In the experiments, evaluations on the performance of model-based, feature-based sequence classification and the whole framework are done respectively. Our sequence classification method as well as the credit scoring framework outperforms other state-of-art methods in the experiments on real-world labelled application and transaction data from a major payment organization.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122090794","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 : 2018-10-01DOI: 10.1109/CYBERC.2018.00020
Wei Yang, Y. Wang, Zhixiang Lai, Yadong Wan, Zhuo Cheng
RPL is a routing protocol for Low-Power and Lossy Networks, which is the routing protocol standardized for the Internet of Things (IoT). However, RPL has many serious vulnerabilities which can be exploited by attackers. In this paper, we adopt an finite state machines(FSM) based vulnerability discovering approach to analyze the security vulnerabilities of RPL, which can successfully discover sinkhole attack, selective-forwarding attack and hello flood attack. Then we propose some security countermeasures to defend against the attacks. Finally, we run a thorough set of simulations to assess the impact of the sinkhole attack and the effectiveness of proposed countermeasure. The results show that the attack can significantly damage the RPL and the countermeasure can successfully detect the malicious node.
{"title":"Security Vulnerabilities and Countermeasures in the RPL-Based Internet of Things","authors":"Wei Yang, Y. Wang, Zhixiang Lai, Yadong Wan, Zhuo Cheng","doi":"10.1109/CYBERC.2018.00020","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00020","url":null,"abstract":"RPL is a routing protocol for Low-Power and Lossy Networks, which is the routing protocol standardized for the Internet of Things (IoT). However, RPL has many serious vulnerabilities which can be exploited by attackers. In this paper, we adopt an finite state machines(FSM) based vulnerability discovering approach to analyze the security vulnerabilities of RPL, which can successfully discover sinkhole attack, selective-forwarding attack and hello flood attack. Then we propose some security countermeasures to defend against the attacks. Finally, we run a thorough set of simulations to assess the impact of the sinkhole attack and the effectiveness of proposed countermeasure. The results show that the attack can significantly damage the RPL and the countermeasure can successfully detect the malicious node.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125544177","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 : 2018-10-01DOI: 10.1109/CYBERC.2018.00096
Haowei Lin, Xiaolong Xu
In order to improve the efficiency and accuracy of data analysis, excellent data screening algorithms are needed in this era of big data. This paper proposes a binary-digit-based data screening algorithm (BDDS), utilizing the binary storage form of data in hardware and recording the data changes over a period of time with a binary-bit recorder, whose number of digits in the binary form is used to remove the influence of the medium-distance data from the current data, left shift of the binary form is used to reduce the influence of the data which are very close to the current data, and the decimal meaning is used to determine whether the data are valid data. Experiments have proved that the algorithm, as an auxiliary algorithm, can be better combined with the current mainstream data analysis algorithms to reduce the impact of marginal data, save additional storage space, and improve the accuracy and efficiency of subsequent data analysis.
{"title":"BDDS: An Efficient Data Screening Algorithm Based on Binary Digit","authors":"Haowei Lin, Xiaolong Xu","doi":"10.1109/CYBERC.2018.00096","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00096","url":null,"abstract":"In order to improve the efficiency and accuracy of data analysis, excellent data screening algorithms are needed in this era of big data. This paper proposes a binary-digit-based data screening algorithm (BDDS), utilizing the binary storage form of data in hardware and recording the data changes over a period of time with a binary-bit recorder, whose number of digits in the binary form is used to remove the influence of the medium-distance data from the current data, left shift of the binary form is used to reduce the influence of the data which are very close to the current data, and the decimal meaning is used to determine whether the data are valid data. Experiments have proved that the algorithm, as an auxiliary algorithm, can be better combined with the current mainstream data analysis algorithms to reduce the impact of marginal data, save additional storage space, and improve the accuracy and efficiency of subsequent data analysis.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132365495","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 : 2018-10-01DOI: 10.1109/CYBERC.2018.00071
Lina Xu, Ning Cao
As small cells and network Access Points (APs) have been massively deployed in the cities, industrial, academic campuses, communication techniques utilising same or different spectrum bands are required to coordinate each other and coexist in harmony. Meanwhile, User Equipments (UEs) including Internet of Things (IoT) devices are more advanced in terms of communication ability. Simultaneously supporting data transmission through multiple network interfaces is prevalent nowadays. The current networks have many diversities and will continually involves more user scenarios and more advanced smart devices. The communication between those devices, is mostly through wireless media, such as, bluetooth, WiFi or LTE. Meanwhile, with the evolution of wireless technology, the communication in most systems will migrate to Heterogeneous Networks (HetNets)/5G networks. The devices in those systems will be able to support 5G communication, enabling more than one radio access interfaces through Multiple-In-Multiple-Out (MIMO) antennas. In order to realise 5G communication, massive regulations and standards are proposed and HetNets have become one popular means since it can utilise the existing infrastructure. The focus of 5G has changes since the last generation from operator centric to user centric services. For purpose of achieving Quality of user Experience (QoE) supported 5G, network selection in HetNets based approach is necessary and also should be intelligent. In this paper, we have proposed that the classic utility function can be applied in such a HetNets scenario. With modifications on the classic utility approach, more advanced features can be enhanced to support QoE aware communication in HetNets based 5G networks. Furthermore, we have demonstrated this idea through a LTE and WiFi integrated network. A solution for smart network selection is delivered in order to achieve 1) better user experience, 2) manageable resource allocation and 3) price control. Based on the analysis, we argue that such a solution can also be extended and implemented for more complex 5G networks to accomplish QoE awareness.
{"title":"A Smart QoE Aware Network Selection Solution for IoT Systems in HetNets Based 5G Scenarios","authors":"Lina Xu, Ning Cao","doi":"10.1109/CYBERC.2018.00071","DOIUrl":"https://doi.org/10.1109/CYBERC.2018.00071","url":null,"abstract":"As small cells and network Access Points (APs) have been massively deployed in the cities, industrial, academic campuses, communication techniques utilising same or different spectrum bands are required to coordinate each other and coexist in harmony. Meanwhile, User Equipments (UEs) including Internet of Things (IoT) devices are more advanced in terms of communication ability. Simultaneously supporting data transmission through multiple network interfaces is prevalent nowadays. The current networks have many diversities and will continually involves more user scenarios and more advanced smart devices. The communication between those devices, is mostly through wireless media, such as, bluetooth, WiFi or LTE. Meanwhile, with the evolution of wireless technology, the communication in most systems will migrate to Heterogeneous Networks (HetNets)/5G networks. The devices in those systems will be able to support 5G communication, enabling more than one radio access interfaces through Multiple-In-Multiple-Out (MIMO) antennas. In order to realise 5G communication, massive regulations and standards are proposed and HetNets have become one popular means since it can utilise the existing infrastructure. The focus of 5G has changes since the last generation from operator centric to user centric services. For purpose of achieving Quality of user Experience (QoE) supported 5G, network selection in HetNets based approach is necessary and also should be intelligent. In this paper, we have proposed that the classic utility function can be applied in such a HetNets scenario. With modifications on the classic utility approach, more advanced features can be enhanced to support QoE aware communication in HetNets based 5G networks. Furthermore, we have demonstrated this idea through a LTE and WiFi integrated network. A solution for smart network selection is delivered in order to achieve 1) better user experience, 2) manageable resource allocation and 3) price control. Based on the analysis, we argue that such a solution can also be extended and implemented for more complex 5G networks to accomplish QoE awareness.","PeriodicalId":282903,"journal":{"name":"2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116245447","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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