The vision of the future Internet of Things is posing new challenges and opportunities for data management and analysis technology. Gigabytes of data are generated everyday by millions of sensors, actuators, RFID tags, and other devices. As the volume of data is growing dramatically, so is the demand for performance enhancement. When it comes to this Big Data problem, much attention has been paid to cloud computing and virtualization for their unlimited resource capacity, exible resource allocation and management, and distributed processing ability that promise high scalability and availability. On the other hand, the types and nature of data are getting more and more various. Data can come in any format, structured or unstructured, ranging from text and number to audio, picture, or even video. Data are generated, stored, and transferred across multiple nodes. Data can be updated and queried in real time or on demand. Hence, the traditional and dominant relational database systems have been questioned whether they can still be the best choice for current systems with all the new requirements. It has been realized that the emphasis on data consistency and the constraint of using relational data model cannot well with the variety of modern data and their distributed trend. This led to the emergence of NoSQL databases with their support for a schema-less data model and horizontal scaling on clusters of nodes. NoSQL databases have gained much attention from the community and are increasingly considered as a viable alternative to traditional databases.
목차
Abstract 1. Introduction 2. Internet of Things vision Things-oriented Vision Internet-oriented Vision Semantic-oriented Vision 3. Internet of Things Data 4. Cloud Databases Amazon Web Services Scalability Replication Sharding 5. Database performance of SQL vs. NoSQL Internet of Things storage Conclusion References
키워드
IoTCloudDatabaseAWSSQLNoSQLStorageIoT Data
저자
Ajit Singh [ Department of Computer Science, Patna Women's College, India ]
한국AI디지털융합학회(구 한국디지털융합학회) [The Korean Academic Society of AI Digital Convergence]
설립연도
2015
분야
사회과학>경영학
소개
본 학회는 디지털 경영에 관련된 디지털 미디어, 디지털 통신, 디지털 방송, 디지털 콘텐츠, 디지털 문화, 디지털 사회, 디지털 유통, 디지털 금융, 디지털 물류, 디지털 정책, 디지털 기술, 디지털 교육 그리고 디지털과 아날로그의 비교 등에 대한 학제간 연구와 실사구시적인 적용을 통하여 디지털 경영의 발전과 한국이 세계적인 디지털 강국으로 성장하기 위한 학술적인 기반과 실무적인 지침을 조성하는 것을 목적으로 하고 있습니다.
간행물
간행물명
IJICTDC [International Journal of Information Communication Technology and Digital Convergence]