Talks and Poster Presentations (with Proceedings-Entry):
S. Dustdar, I. Murturi:
"Towards Distributed Edge-based Systems";
Talk: IEEE 2nd International Conference on Cognitive Machine Intelligence (CogMI 2020) - Online Conference,
Atlanta, Georgia, USA;
- 2020-12-03; in: "Proceedings of the IEEE 2nd International Conference on Cognitive Machine Intelligence (CogMI 2020)",
In the past few years, researchers from academia and industry stakeholders suggest adding more computational resources (i.e., storage, networking, and processing) closer to the end-users and IoT domain, respectively, at the edge of the network. Such computation entities perceived as edge devices aim to overcome high-latency issues between the cloud and the IoT domain. Thus, processing IoT data streams closer to the end-users and IoT domain can solve several operational challenges. Since then, a plethora of application-specific IoT systems are introduced, mainly hard-coded, inflexible, and limited extensibility for future changes. Additionally, most IoT systems maintain a centralized design to operate without considering the dynamic nature of edge networks. In this paper, we discuss some of the research issues, challenges, and potential solutions to enable: i) deploying edge functions on edge resources in a distributed manner and ii) deploying and scaling edge applications on-premises of Edge-Cloud infrastructure. Additionally, we discuss in detail the three-tier Edge-Cloud architecture. Finally, we introduce a conceptual framework that aims to enable easy configuration and deployment of edge-based systems on top of heterogeneous edge infrastructure and present our vision within a smart city scenario.
Edge-Cloud Continuum, Edge-based Systems, Distributed Edge Function
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Project Head Schahram Dustdar:
Created from the Publication Database of the Vienna University of Technology.