Pub Date : 2021-10-11DOI: 10.12142/ZTECOM.202103008
Zhang Man, Li Dapeng, Liu Zhuang, Gao Yin
{"title":"QoE Management for 5G New Radio","authors":"Zhang Man, Li Dapeng, Liu Zhuang, Gao Yin","doi":"10.12142/ZTECOM.202103008","DOIUrl":"https://doi.org/10.12142/ZTECOM.202103008","url":null,"abstract":"","PeriodicalId":61991,"journal":{"name":"ZTE Communications","volume":"19 1","pages":"64-72"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48102897","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 : 2021-10-11DOI: 10.12142/ZTECOM.202103010
S. Kenji, Z. Xiaobo
{"title":"Semiconductor Optical Amplifier and Gain Chip Used in Wavelength Tunable Lasers","authors":"S. Kenji, Z. Xiaobo","doi":"10.12142/ZTECOM.202103010","DOIUrl":"https://doi.org/10.12142/ZTECOM.202103010","url":null,"abstract":"","PeriodicalId":61991,"journal":{"name":"ZTE Communications","volume":"19 1","pages":"81-87"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47189876","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 : 2021-10-11DOI: 10.12142/ZTECOM.202103005
Liu Xiuxian, Li Zhetao, Ouyang Yan, Duan Haohua, Xiang Liyao
{"title":"Using UAV to Detect Truth for Clean Data Collection in Sensor‑Cloud Systems","authors":"Liu Xiuxian, Li Zhetao, Ouyang Yan, Duan Haohua, Xiang Liyao","doi":"10.12142/ZTECOM.202103005","DOIUrl":"https://doi.org/10.12142/ZTECOM.202103005","url":null,"abstract":"","PeriodicalId":61991,"journal":{"name":"ZTE Communications","volume":"19 1","pages":"30-45"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46435707","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 : 2021-10-11DOI: 10.12142/ZTECOM.202103006
Liu Weichen, Shen Mengqi, Zhang Anda, Chen Yiting, Z. Wenqiang
{"title":"Artificial Intelligence Rehabilitation Evaluation and Training System for Degeneration of Joint Disease","authors":"Liu Weichen, Shen Mengqi, Zhang Anda, Chen Yiting, Z. Wenqiang","doi":"10.12142/ZTECOM.202103006","DOIUrl":"https://doi.org/10.12142/ZTECOM.202103006","url":null,"abstract":"","PeriodicalId":61991,"journal":{"name":"ZTE Communications","volume":"19 1","pages":"46-55"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42928938","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 : 2021-07-27DOI: 10.12142/ZTECOM.202102004
Liu Junyu, Yongjian Yang, Wang En
With the emergence of mobile crowdsensing (MCS), merchants can use their mo⁃ bile devices to collect data that customers are interested in. Now there are many mobile crowdsensing platforms in the market, such as Gigwalk, Uber and Checkpoint, which pub⁃ lish and select the right workers to complete the task of some specific locations (for example, taking photos to collect the price of goods in a shopping mall). In mobile crowdsensing, in or⁃ der to select the right workers, the platform needs the actual location information of workers and tasks, which poses a risk to the location privacy of workers and tasks. In this paper, we study privacy protection in MCS. The main challenge is to assign the most suitable worker to a task without knowing the task and the actual location of the worker. We propose a bilateral privacy protection framework based on matrix multiplication, which can protect the location privacy between the task and the worker, and keep their relative distance unchanged.
{"title":"BPPF: Bilateral Privacy-Preserving Framework for Mobile Crowdsensing","authors":"Liu Junyu, Yongjian Yang, Wang En","doi":"10.12142/ZTECOM.202102004","DOIUrl":"https://doi.org/10.12142/ZTECOM.202102004","url":null,"abstract":"With the emergence of mobile crowdsensing (MCS), merchants can use their mo⁃ bile devices to collect data that customers are interested in. Now there are many mobile crowdsensing platforms in the market, such as Gigwalk, Uber and Checkpoint, which pub⁃ lish and select the right workers to complete the task of some specific locations (for example, taking photos to collect the price of goods in a shopping mall). In mobile crowdsensing, in or⁃ der to select the right workers, the platform needs the actual location information of workers and tasks, which poses a risk to the location privacy of workers and tasks. In this paper, we study privacy protection in MCS. The main challenge is to assign the most suitable worker to a task without knowing the task and the actual location of the worker. We propose a bilateral privacy protection framework based on matrix multiplication, which can protect the location privacy between the task and the worker, and keep their relative distance unchanged.","PeriodicalId":61991,"journal":{"name":"ZTE Communications","volume":"19 1","pages":"20-28"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46381110","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 : 2021-07-27DOI: 10.12142/ZTECOM.202102002
Suning Han, Xiuhua Li, Sun Chuan, Xiaofei Wang, Victor C. M. Leung
Edge caching is an emerging technology for supporting massive content access in mobile edge networks to address rapidly growing Internet of Things (IoT) services and con⁃ tent applications. However, the edge server is limited with the computation/storage capacity, which causes a low cache hit. Cooperative edge caching jointing neighbor edge servers is re⁃ garded as a promising technique to improve cache hit and reduce congestion of the net⁃ works. Further, recommender systems can provide personalized content services to meet us⁃ er’s requirements in the entertainment-oriented mobile networks. Therefore, we investigate the issue of joint cooperative edge caching and recommender systems to achieve additional cache gains by the soft caching framework. To measure the cache profits, the optimization problem is formulated as a 0–1 Integer Linear Programming (ILP), which is NP-hard. Spe⁃ cifically, the method of processing content requests is defined as server actions, we deter⁃ mine the server actions to maximize the quality of experience (QoE). We propose a cachefriendly heuristic algorithm to solve it. Simulation results demonstrate that the proposed framework has superior performance in improving the QoE.
{"title":"RecCac: Recommendation-Empowered Cooperative Edge Caching for Internet of Things","authors":"Suning Han, Xiuhua Li, Sun Chuan, Xiaofei Wang, Victor C. M. Leung","doi":"10.12142/ZTECOM.202102002","DOIUrl":"https://doi.org/10.12142/ZTECOM.202102002","url":null,"abstract":"Edge caching is an emerging technology for supporting massive content access in mobile edge networks to address rapidly growing Internet of Things (IoT) services and con⁃ tent applications. However, the edge server is limited with the computation/storage capacity, which causes a low cache hit. Cooperative edge caching jointing neighbor edge servers is re⁃ garded as a promising technique to improve cache hit and reduce congestion of the net⁃ works. Further, recommender systems can provide personalized content services to meet us⁃ er’s requirements in the entertainment-oriented mobile networks. Therefore, we investigate the issue of joint cooperative edge caching and recommender systems to achieve additional cache gains by the soft caching framework. To measure the cache profits, the optimization problem is formulated as a 0–1 Integer Linear Programming (ILP), which is NP-hard. Spe⁃ cifically, the method of processing content requests is defined as server actions, we deter⁃ mine the server actions to maximize the quality of experience (QoE). We propose a cachefriendly heuristic algorithm to solve it. Simulation results demonstrate that the proposed framework has superior performance in improving the QoE.","PeriodicalId":61991,"journal":{"name":"ZTE Communications","volume":"19 1","pages":"2-10"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43233480","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 : 2021-07-27DOI: 10.12142/ZTECOM.202102009
Z. Tian, Li Hui, Yang Xin, Wang Han, Z. Ming, Guo Haisheng, Wang Dezheng
{"title":"Differentially Authorized Deduplication System Based on Blockchain","authors":"Z. Tian, Li Hui, Yang Xin, Wang Han, Z. Ming, Guo Haisheng, Wang Dezheng","doi":"10.12142/ZTECOM.202102009","DOIUrl":"https://doi.org/10.12142/ZTECOM.202102009","url":null,"abstract":"","PeriodicalId":61991,"journal":{"name":"ZTE Communications","volume":"19 1","pages":"67-76"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44194942","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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