Talks and Poster Presentations (with Proceedings-Entry):

I. Murturi, M. Barzegaran, S. Dustdar:
"A Decentralized Approach for Determining Configurator Placement in Dynamic Edge Networks";
Talk: IEEE 2nd International Conference on Cognitive Machine Intelligence (CogMI 2020) - Online Conference, Atlanta, Georgia, USA; 2020-12-01 - 2020-12-03; in: "Proceedings of the IEEE 2nd International Conference on Cognitive Machine Intelligence (CogMI 2020)", IEEE, (2020), ISBN: 978-1-7281-4145-9; 147 - 156.

English abstract:
In today's IoT infrastructures, increasingly newly added computational resources at the edge of a network are added to acquire faster response and increased privacy. Such edge networks bring an opportunity for deploying edge application services in proximity to IoT domains and the end-users. In this paper, we consider the problem of utilizing various computational resources established by multiple heterogeneous edge devices in dynamic edge networks. A new lightweight decentralized mechanism (i.e., configurator) is required to monitor an edge infrastructure to enable deploying, orchestrating, and monitoring edge applications at the edge. In this setting, one critical task is to determine the node where the configurator should be placed (deployed) and run (executed) at the edge. In this paper, we propose an efficient approach that solves the configurator's placement problem on the most suited edge device in a given dynamic edge network. Our approach supports the system coping with the dynamicity and uncertainty of the environment and adapts based on the configurator's service quality. We discuss the architecture, processes of the approach, and the simulations we conducted to validate its feasibility.

Edge Computing, Internet of Things, Decentralized, Resource Management

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Related Projects:
Project Head Wolfgang Kastner:

Created from the Publication Database of the Vienna University of Technology.