Human-centric storage resource mechanism for big data on cloud service architecture
Jul. 2016. By Young-Sik Jeong
Keyword: Human-centric resource management, Big data storage, Legacy desktop computer, Resource-integrated mechanism, Distributed file system, Fault tolerance, Media-driven service
With the rapid advancement of information technology in recent years, significant research addressing the efficient storage of big data has been conducted. Traditionally, big data with media-driven service have simply implied extensive amounts of data. However, this definition has evolved to include the extraction of values, analysis, and the prediction of results from a vast volume of unstructured and varied datasets. Because of the explosive growth of computer processing technologies, the creation of big data has originated from unstructured data, text data, image data, and location data created by a variety of digital devices. Classically, the storage of big data has been administered by companies that provide storage services or by specialized storage companies. Significant cost is incurred to store big data efficiently and maintain sufficient storage requirements, which increase continuously.
In this research, a human-centric Resource-Integrated System for Big Data (RISBD) is proposed that utilizes the resources of legacy desktop computers for big data storage to future communication. This is advantageous in terms of the cost of implementing a new storage system. Furthermore, it provides high storage scalability because it is an XML-based standard storage integration system developed using software.