A framework for optimizing data transfers between edge devices and the cloud using compression utilities
Date of Award
Doctor of Philosophy (PhD)
Electrical and Computer Engineering
B. Earl Wells
Data compression (Telecommunications), Wireless communication systems., Computer networks., Cloud computing.
An exponential growth of data traffic that originates on edge devices and a shift toward cloud computing necessitate finding new approaches to optimize file transfers. Whereas compression utilities can improve effective throughput and energy efficiency of file transfers between edge devices and the cloud, finding a best-performing utility for a given file transfer is a challenging task. In this dissertation, we introduce a framework for optimizing file transfers between edge devices and the cloud using compression utilities. The proposed framework involves agents running on edge devices and the cloud that are responsible for selecting an effective transfer mode by considering characteristics of transferred files, network conditions, and device performance. The framework agents deployed on a smartphone and a workstation are experimentally evaluated with transfers of varied datasets to and from a local server and cloud instances over networks with varying levels of throughput. The results of the experimental evaluation demonstrate that the framework improves throughput and energy efficiency and reduces costs of file transfers.
Dzhagaryan, Armen A., "A framework for optimizing data transfers between edge devices and the cloud using compression utilities" (2016). Dissertations. 98.