Fog Computing Paradigm: Multilayer Data Processing and Aggregating Framework for Latency-sensitive Service

• Main Authors: Wu, Meng-Chian, 吳孟謙
• Other Authors: Yuan, Shyan-Ming
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/4s4556

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 105 === Recently years, there are a lot of interests in fog computing in the distributing computing field. Fog computing is a new computing architecture extended from cloud computing, and proposed to solve problems met on latency-sensitive and location-awareness IoT services. Although there are several fog computing-based theories and applications have been proposed, most of them only evaluated their works by theoretical simulations. Those are far from real situations and difficult to be applied into practice. Motivated by previous works, this study is aimed to propose a client-fog-cloud multilayer data processing and aggregation framework, based on fog computing paradigm. The proposed framework is designed to help latency-sensitive applications in IOT context, which meet requirements: widely distribution, massive uploading, low latency, and real-time interaction. Authors used the child abduction alert service as a sample to evaluate the proposed framework in practical scenarios, and compare performance and feasibility to the conventional cloud solution. Results showed that this framework can reduce about 32% response time and 30% data transferred to the cloud.