Big data has a strong demand for a network infrastructure with the capability to support data sharing and retrieval efficiently. Information-centric networking （ICN） is an emerging approach to satisfy this demand, w...Big data has a strong demand for a network infrastructure with the capability to support data sharing and retrieval efficiently. Information-centric networking （ICN） is an emerging approach to satisfy this demand, where big data is cached ubiquitously in the network and retrieved using data names. However, existing authentication and authorization schemes rely mostly on centralized servers to provide certification and mediation services for data retrieval. This causes considerable traffic overhead for the secure distributed sharing of data. To solve this problem, we employ identity-based cryptography （IBC） to propose a Distributed Authentication and Authorization Scheme （DAAS）, where an identity-based signature （IBS） is used to achieve distributed verifications of the identities of publishers and users. Moreover, Ciphertext-Policy Attribnte-based encryption （CP-ABE） is used to enable the distributed and fine-grained authorization. DAAS consists of three phases： initialization, secure data publication, and secure data retrieval, which seamlessly integrate authentication and authorization with the in- terest/data communication paradigm in ICN. In particular, we propose trustworthy registration and Network Operator and Authority Manifest （NOAM） dissemination to provide initial secure registration and enable efficient authentication for global data retrieval. Meanwhile, Attribute Manifest （AM） distribution coupled with automatic attribute update is proposed to reduce the cost of attribute retrieval. We examine the performance of the proposed DAAS, which shows that it can achieve a lower bandwidth cost than existing schemes.展开更多
In this paper, we explore network architecture anal key technologies for content-centric networking （CCN）, an emerging networking technology in the big-data era. We descrihe the structure anti operation mechanism of...In this paper, we explore network architecture anal key technologies for content-centric networking （CCN）, an emerging networking technology in the big-data era. We descrihe the structure anti operation mechanism of tl CCN node. Then we discuss mobility management, routing strategy, and caching policy in CCN. For better network performance, we propose a probability cache replacement policy that is based on cotent popularity. We also propose and evaluate a probability cache with evicted copy-up decision policy.展开更多
Advances in Information Technology (IT) have enhanced our ability to gather, collect and analyze information from individuals and specific groups of people online. The emergence of online networks has facilitated conn...Advances in Information Technology (IT) have enhanced our ability to gather, collect and analyze information from individuals and specific groups of people online. The emergence of online networks has facilitated connections between individuals by leveraging data exchange in a variety of fields. Online networking in life sciences transforms data collection into actionable information that will improve individual and population health, deliver effective therapies and, consequently, reduce the cost of healthcare. These novel tools might also have a direct impact in personalized medicine programs, since the adoption of new products by health care professionals in life sciences and peer-to-peer learning could be improved using social networks and big data analytics. However, one of the main concerns of information exchange online is data privacy. In this article, we will review how online networks and big data analytics are impacting the life sciences sector.展开更多
As the rapid development of automotive telematics,modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding enviro...As the rapid development of automotive telematics,modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding environment. By significantly expanding the network scale and conducting both real-time and long-term information processing, the traditional Vehicular AdHoc Networks(VANETs) are evolving to the Internet of Vehicles(Io V), which promises efficient and intelligent prospect for the future transportation system. On the other hand, vehicles are not only consuming but also generating a huge amount and enormous types of data, which is referred to as Big Data. In this article, we first investigate the relationship between Io V and big data in vehicular environment, mainly on how Io V supports the transmission, storage, computing of the big data, and how Io V benefits from big data in terms of Io V characterization,performance evaluation and big data assisted communication protocol design. We then investigate the application of Io V big data in autonomous vehicles. Finally, the emerging issues of the big data enabled Io V are discussed.展开更多
Causal analysis is a powerful tool to unravel the data complexity and hence provide clues to achieving, say, better platform design, efficient interoperability and service management, etc. Data science will surely ben...Causal analysis is a powerful tool to unravel the data complexity and hence provide clues to achieving, say, better platform design, efficient interoperability and service management, etc. Data science will surely benefit from the advancement in this field. Here we introduce into this community a recent finding in physics on causality and the subsequent rigorous and quantitative causality analysis. The resulting formula is concise in form, involving only the common statistics namely sample covariance. A corollary is that causation implies correlation, but not vice versa, resolving the long-standing philosophical debate over correlation versus causation. The applicability to big data analysis is validated with time series purportedly generated with hidden processes. As a demonstration, a preliminary application to the gross domestic product (GDP) data of United States, China, and Japan reveals some subtle USA-China-Japan relations in certain periods. 展开更多
The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after a...The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after another and created strong interdependence among one another. For example, IoT applications that generate small data with large volume and fast velocity will need 5G with characteristics of high data rate and low latency to transmit such data faster and cheaper. On the other hand, those data also need Cloud to process and to store and furthermore, SDN to provide scalable network infrastructure to transport this large volume of data in an optimal way. This article explores the technical relationships among the development of IoT, Big Data, Cloud, and SDN in the coming 5G era and illustrates several ongoing programs and applications at National Chiao Tung University that are based on the converging of those technologies.展开更多
The era of open information in healthcare has arrived. E-healthcare supported by big data supports the move toward greater trans-parency in healthcare by making decades of stored health data searchable and usable. Thi...The era of open information in healthcare has arrived. E-healthcare supported by big data supports the move toward greater trans-parency in healthcare by making decades of stored health data searchable and usable. This paper gives an overview the e-health-care architecture. We discuss the four layers of the architecture-data collection, data transport, data storage, and data analysis-as well as the challenges of data security, data privacy, real-time delivery, and open standard interface. We discuss the necessity of establishing an impeccably secure access mechanism and of enacting strong laws to protect patient privacy.展开更多
Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the cir- cumstances of dynamic production. A Bayesian network and...Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the cir- cumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian net- work of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly pro- portionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The inte- gration ofbigdata analytics and BN method offers a whole new perspective in manufacturing quality control.展开更多
Mobile operators face the challenge of how to best design a service-centric network that can effectively process the rapidly increasing number of bandwidth-intensive user requests while providing a higher quality of e...Mobile operators face the challenge of how to best design a service-centric network that can effectively process the rapidly increasing number of bandwidth-intensive user requests while providing a higher quality of experience(QoE). Existing content distribution networks(CDN) and mobile content distribution networks(mCDN) have both latency and throughput limitations due to being multiple network hops away from end-users. Here, we first propose a new Personalized Edge Caching System(PECS) architecture that employs big data analytics and mobile edge caching to provide personalized service access at the edge of the mobile network. Based on the proposed system architecture, the edge caching strategy based on user behavior and trajectory is analyzed. Employing our proposed PECS strategies, we use data mining algorithms to analyze the personalized trajectory and service usage patterns. Our findings provide guidance on how key technologies of PECS can be employed for current and future networks. Finally, we highlight the challenges associated with realizing such a system in 5G and beyond.展开更多
文摘Big data has a strong demand for a network infrastructure with the capability to support data sharing and retrieval efficiently. Information-centric networking （ICN） is an emerging approach to satisfy this demand, where big data is cached ubiquitously in the network and retrieved using data names. However, existing authentication and authorization schemes rely mostly on centralized servers to provide certification and mediation services for data retrieval. This causes considerable traffic overhead for the secure distributed sharing of data. To solve this problem, we employ identity-based cryptography （IBC） to propose a Distributed Authentication and Authorization Scheme （DAAS）, where an identity-based signature （IBS） is used to achieve distributed verifications of the identities of publishers and users. Moreover, Ciphertext-Policy Attribnte-based encryption （CP-ABE） is used to enable the distributed and fine-grained authorization. DAAS consists of three phases： initialization, secure data publication, and secure data retrieval, which seamlessly integrate authentication and authorization with the in- terest/data communication paradigm in ICN. In particular, we propose trustworthy registration and Network Operator and Authority Manifest （NOAM） dissemination to provide initial secure registration and enable efficient authentication for global data retrieval. Meanwhile, Attribute Manifest （AM） distribution coupled with automatic attribute update is proposed to reduce the cost of attribute retrieval. We examine the performance of the proposed DAAS, which shows that it can achieve a lower bandwidth cost than existing schemes.
基金supported by National Natural Science Foundation of China under Grant No.60872018 and No. 60902015Major National Science and Technology Project No. 2011ZX03005-004-03
文摘In this paper, we explore network architecture anal key technologies for content-centric networking （CCN）, an emerging networking technology in the big-data era. We descrihe the structure anti operation mechanism of tl CCN node. Then we discuss mobility management, routing strategy, and caching policy in CCN. For better network performance, we propose a probability cache replacement policy that is based on cotent popularity. We also propose and evaluate a probability cache with evicted copy-up decision policy.
文摘Advances in Information Technology (IT) have enhanced our ability to gather, collect and analyze information from individuals and specific groups of people online. The emergence of online networks has facilitated connections between individuals by leveraging data exchange in a variety of fields. Online networking in life sciences transforms data collection into actionable information that will improve individual and population health, deliver effective therapies and, consequently, reduce the cost of healthcare. These novel tools might also have a direct impact in personalized medicine programs, since the adoption of new products by health care professionals in life sciences and peer-to-peer learning could be improved using social networks and big data analytics. However, one of the main concerns of information exchange online is data privacy. In this article, we will review how online networks and big data analytics are impacting the life sciences sector.
基金supported by the National Natural Science Foundation of China(91638204)Natural Sciences and Engineering Research Council(NSERC)
文摘As the rapid development of automotive telematics,modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding environment. By significantly expanding the network scale and conducting both real-time and long-term information processing, the traditional Vehicular AdHoc Networks(VANETs) are evolving to the Internet of Vehicles(Io V), which promises efficient and intelligent prospect for the future transportation system. On the other hand, vehicles are not only consuming but also generating a huge amount and enormous types of data, which is referred to as Big Data. In this article, we first investigate the relationship between Io V and big data in vehicular environment, mainly on how Io V supports the transmission, storage, computing of the big data, and how Io V benefits from big data in terms of Io V characterization,performance evaluation and big data assisted communication protocol design. We then investigate the application of Io V big data in autonomous vehicles. Finally, the emerging issues of the big data enabled Io V are discussed.
文摘Causal analysis is a powerful tool to unravel the data complexity and hence provide clues to achieving, say, better platform design, efficient interoperability and service management, etc. Data science will surely benefit from the advancement in this field. Here we introduce into this community a recent finding in physics on causality and the subsequent rigorous and quantitative causality analysis. The resulting formula is concise in form, involving only the common statistics namely sample covariance. A corollary is that causation implies correlation, but not vice versa, resolving the long-standing philosophical debate over correlation versus causation. The applicability to big data analysis is validated with time series purportedly generated with hidden processes. As a demonstration, a preliminary application to the gross domestic product (GDP) data of United States, China, and Japan reveals some subtle USA-China-Japan relations in certain periods.
文摘The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after another and created strong interdependence among one another. For example, IoT applications that generate small data with large volume and fast velocity will need 5G with characteristics of high data rate and low latency to transmit such data faster and cheaper. On the other hand, those data also need Cloud to process and to store and furthermore, SDN to provide scalable network infrastructure to transport this large volume of data in an optimal way. This article explores the technical relationships among the development of IoT, Big Data, Cloud, and SDN in the coming 5G era and illustrates several ongoing programs and applications at National Chiao Tung University that are based on the converging of those technologies.
基金the Natural Science Foundation of Guangdong Province, China (No.9151009001000021)the Ministry of Education of Guangdong Province Special Fund Funded Projects through the Cooperative of China (No.2009B090300341)+2 种基金the National Natural Science Foundation of China (No.61262013)the Open Fund of Guangdong Province Key Laboratory of Precision Equipment and Manufacturing Technology (No.PEMT1303)the Higher Vocational Education Teaching Reform Project of Guangdong Province (No.20130301011) for their support in this research
文摘The era of open information in healthcare has arrived. E-healthcare supported by big data supports the move toward greater trans-parency in healthcare by making decades of stored health data searchable and usable. This paper gives an overview the e-health-care architecture. We discuss the four layers of the architecture-data collection, data transport, data storage, and data analysis-as well as the challenges of data security, data privacy, real-time delivery, and open standard interface. We discuss the necessity of establishing an impeccably secure access mechanism and of enacting strong laws to protect patient privacy.
基金Supported by 2015 Special Funds for Intelligent Manufacturing of China MIIT(Grant No.2015-415)National Natural Science Foundation of China(Grant No.71632008)
文摘Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the cir- cumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian net- work of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly pro- portionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The inte- gration ofbigdata analytics and BN method offers a whole new perspective in manufacturing quality control.
基金supported in part by the Fundamental Research Funds for the Central Universities of China (No. 2018CUCTJ078, CUC18A002-2)
文摘Mobile operators face the challenge of how to best design a service-centric network that can effectively process the rapidly increasing number of bandwidth-intensive user requests while providing a higher quality of experience(QoE). Existing content distribution networks(CDN) and mobile content distribution networks(mCDN) have both latency and throughput limitations due to being multiple network hops away from end-users. Here, we first propose a new Personalized Edge Caching System(PECS) architecture that employs big data analytics and mobile edge caching to provide personalized service access at the edge of the mobile network. Based on the proposed system architecture, the edge caching strategy based on user behavior and trajectory is analyzed. Employing our proposed PECS strategies, we use data mining algorithms to analyze the personalized trajectory and service usage patterns. Our findings provide guidance on how key technologies of PECS can be employed for current and future networks. Finally, we highlight the challenges associated with realizing such a system in 5G and beyond.
