There is a great thrust in industry toward the development of more feasible and viable tools for storing fast-growing volume, velocity, and diversity of data, termed ＇big data＇. The structural shift of the storage m...There is a great thrust in industry toward the development of more feasible and viable tools for storing fast-growing volume, velocity, and diversity of data, termed ＇big data＇. The structural shift of the storage mechanism from traditional data management systems to NoSQL technology is due to the intention of fulfilling big data storage requirements. However, the available big data storage technologies are inefficient to provide consistent, scalable, and available solutions for continuously growing heterogeneous data. Storage is the preliminary process of big data analytics for real-world applications such as scientific experiments, healthcare, social networks, and e-business. So far, Amazon, Google, and Apache are some of the industry standards in providing big data storage solutions, yet the literature does not report an in-depth survey of storage technologies available for big data, investigating the performance and magnitude gains of these technologies. The primary objective of this paper is to conduct a comprehensive investigation of state-of-the-art storage technologies available for big data. A well-defined taxonomy of big data storage technologies is presented to assist data analysts and researchers in understanding and selecting a storage mecha- nism that better fits their needs. To evaluate the performance of different storage architectures, we compare and analyze the ex- isling approaches using Brewer＇s CAP theorem. The significance and applications of storage technologies and support to other categories are discussed. Several future research challenges are highlighted with the intention to expedite the deployment of a reliable and scalable storage system.展开更多
The possibility to achieve unprecedented multiplexing of light-matter interaction in nanoscale is of virtue importance from both fundamental science and practical application points of view. Cylindrical vector beams(C...The possibility to achieve unprecedented multiplexing of light-matter interaction in nanoscale is of virtue importance from both fundamental science and practical application points of view. Cylindrical vector beams(CVBs) manifested as polarization vortices represent a robust and emerging degree of freedom for information multiplexing with increased capacities. Here, we propose and demonstrate massivelyencoded optical data storage(ODS) by harnessing spatially variant electric fields mediated by segmented CVBs. By tight focusing polychromatic segmented CVBs to plasmonic nanoparticle aggregates, recordhigh multiplexing channels of ODS through different combinations of polarization states and wavelengths have been experimentally demonstrated with a low error rate. Our result not only casts new perceptions for tailoring light-matter interactions utilizing structured light but also enables a new prospective for ultra-high capacity optical memory with minimalist system complexity by combining CVB’s compatibility with fiber optics.展开更多
文摘There is a great thrust in industry toward the development of more feasible and viable tools for storing fast-growing volume, velocity, and diversity of data, termed ＇big data＇. The structural shift of the storage mechanism from traditional data management systems to NoSQL technology is due to the intention of fulfilling big data storage requirements. However, the available big data storage technologies are inefficient to provide consistent, scalable, and available solutions for continuously growing heterogeneous data. Storage is the preliminary process of big data analytics for real-world applications such as scientific experiments, healthcare, social networks, and e-business. So far, Amazon, Google, and Apache are some of the industry standards in providing big data storage solutions, yet the literature does not report an in-depth survey of storage technologies available for big data, investigating the performance and magnitude gains of these technologies. The primary objective of this paper is to conduct a comprehensive investigation of state-of-the-art storage technologies available for big data. A well-defined taxonomy of big data storage technologies is presented to assist data analysts and researchers in understanding and selecting a storage mecha- nism that better fits their needs. To evaluate the performance of different storage architectures, we compare and analyze the ex- isling approaches using Brewer＇s CAP theorem. The significance and applications of storage technologies and support to other categories are discussed. Several future research challenges are highlighted with the intention to expedite the deployment of a reliable and scalable storage system.
基金the financial support from the National Key R&D Program of China (2018YFB1107200)the National Natural Science Foundation of China (91750110, 11674130, 61605061, 11674110 and 11874020)+2 种基金the Guangdong Provincial Innovation and Entrepreneurship Project (2016ZT06D081)the Natural Science Foundation of Guangdong Province (2016A030306016, 2016TQ03X981 and 2016A030308010)Pearl River S and T Nova Program of Guangzhou (201806010040)。
文摘The possibility to achieve unprecedented multiplexing of light-matter interaction in nanoscale is of virtue importance from both fundamental science and practical application points of view. Cylindrical vector beams(CVBs) manifested as polarization vortices represent a robust and emerging degree of freedom for information multiplexing with increased capacities. Here, we propose and demonstrate massivelyencoded optical data storage(ODS) by harnessing spatially variant electric fields mediated by segmented CVBs. By tight focusing polychromatic segmented CVBs to plasmonic nanoparticle aggregates, recordhigh multiplexing channels of ODS through different combinations of polarization states and wavelengths have been experimentally demonstrated with a low error rate. Our result not only casts new perceptions for tailoring light-matter interactions utilizing structured light but also enables a new prospective for ultra-high capacity optical memory with minimalist system complexity by combining CVB’s compatibility with fiber optics.
