Title :
Situation aware computing for big data
Author :
Chan, Eric S. ; Gawlick, Dieter ; Ghoneimy, Adel ; Zhen Hua Liu
Author_Institution :
Oracle Corp., Redwood Shores, CA, USA
Abstract :
Big Data applications need a situation aware computing model to manage data, knowledge, and processes in an ever increasing amount, complexity, and speed while reacting as efficiently and timely as possible to any evolving situation. We introduce a Knowledge Intensive Data-processing System (KIDS) that empowers Big Data applications to support situation awareness. Frameworks such as Apache Hadoop YARN can be leveraged for repeated and near real-time execution of knowledge intensive applications. KIDS bridges the gap between the world of low-value data and the world of high-value information and knowledge, which are best handled by state of the art databases. These databases provide a host of much needed functions such as multi-temporality, flashback, provenance, and registered queries. With KIDS model, Big Data applications are well structured and can evolve perpetually.
Keywords :
Big Data; distributed processing; query processing; ubiquitous computing; Apache Hadoop YARN; KIDS; big data applications; high-value information; knowledge intensive data-processing system; multitemporality; registered queries; situation aware computing model; Big data; Computational modeling; Context modeling; Data models; Databases; Real-time systems; Yarn; Bi-Temporal; Big Data; Database; Hadoop; Knowledge; Provenance; Situation Awareness; YARN;
Conference_Titel :
Big Data (Big Data), 2014 IEEE International Conference on
Conference_Location :
Washington, DC
DOI :
10.1109/BigData.2014.7004415
