Description

Nowadays, the quantity of collected data from many different sources is increasing dramatically. As the traditional on-hand computing resources are not sufficient enough to handle Big data, deploying the processing services into clouds is becoming an inevitable trend. In this data-driven society, we are collecting a massive amount of data from people, actions, sensors, algorithms and the web; handling “Big Data” has become a major challenge. When an organization uses BI technology to improve services, we characterize it as a “smart organization”. The smart features of these organizations have different levels which depend on the accuracy of decisions; greater accuracy of data analysis provides “smarter” organizations. For this reason, we are collecting a massive amount of data from people, actions, sensors, algorithms, and the web which forms “Big Data.” This digital data collection grows exponentially each year. According to big data refers to datasets whose size is beyond the ability of typical database software tools and applications to capture, store, manage and analyze. An important task of any organization is to analyze data. Analysis could change a large volume of data to a smaller amount of valuable data, but we still require collecting a massive amount of data. This project provides an overview of service-generated big data and Big Data-as-aService. First, three types of service-generated big data (service trace logs, service QoS information, and service relationship) are exploited to enhance system performance.