Computer Science
An Experimental study on the impact of execution location in edge-cloud computing
Document Type
Conference Paper
Abstract
On the one hand, edge computing has the advantage of distributing the load to the edges of a computer network. Local computation at the edge is bandwidth-efficient and anonymous. On the other hand, cloud computing is the choice when it comes to computationally demanding tasks and big data. In this paper, we argue for edge-cloud computing (which blends the two together) with an experimental study on the impact of execution location on application performance. We answer the question of how to determine whether it should compute a task at the edge or on the cloud and what the criteria are. We analyze the factors of response time, memory space, data availability and privacy policy. We experimentally evaluate the impact of these factors on execution location based on a network visualizer software.
Publication Title
Proceedings - 2020 6th International Conference on Big Data Computing and Communications, BigCom 2020
Publication Date
2020
First Page
145
Last Page
151
ISBN
9781728182759
DOI
10.1109/BigCom51056.2020.00028
Keywords
cloud computing, edge computing, location of execution
Repository Citation
Melissourgos, Dimitrios; Wang, Sishun; Chen, Shigang; Zhang, Youlin; Odegbile, Olufemi; and Wang, Yuanda, "An Experimental study on the impact of execution location in edge-cloud computing" (2020). Computer Science. 177.
https://commons.clarku.edu/faculty_computer_sciences/177
APA Citation
Melissourgos, D., Wang, S., Chen, S., Zhang, Y., Odegbile, O., & Wang, Y. (2020, July). An Experimental Study on the Impact of Execution Location in Edge-Cloud Computing. In 2020 6th International Conference on Big Data Computing and Communications (BIGCOM) (pp. 145-151). IEEE.