Towards a Cognitive Compute Continuum: An Architecture for Ad-Hoc Self-Managed Swarms

In this paper we introduce our vision of a Cognitive Computing Continuum to address the changing IT service provisioning towards a distributed, opportunistic, self-managed collaboration between heterogeneous devices outside the traditional data center boundaries. The focal point of this continuum are cognitive devices, which have to make decisions autonomously using their on-board computation and storage capacity based on information sensed from their environment. Such devices are moving and cannot rely on fixed infrastructure elements, but instead realise on-the-fly networking and thus frequently join and leave temporal swarms. All this creates novel demands for the underlying architecture and resource management, which must bridge the gap from edge to cloud environments, while keeping the QoS parameters within required boundaries. The paper presents an initial architecture and a resource management framework for the implementation of this type of IT service provisioning.Comment: 8 pages, CCGrid 2021 Cloud2Things Worksho

FogLearn: Leveraging Fog-based Machine Learning for Smart System Big Data Analytics

Big data analytics with the cloud computing are one of the emerging area for processing and analytics. Fog computing is the paradigm where fog devices help to reduce latency and increase throughput for assisting at the edge of the client. This paper discussed the emergence of fog computing for mining analytics in big data from geospatial and medical health applications. This paper proposed and developed fog computing based framework i.e. FogLearn for application of K-means clustering in Ganga River Basin Management and realworld feature data for detecting diabetes patients suffering from diabetes mellitus. Proposed architecture employed machine learning on deep learning framework for analysis of pathological feature data that obtained from smart watches worn by the patients with diabetes and geographical parameters of River Ganga basin geospatial database. The results showed that fog computing hold an immense promise for analysis of medical and geospatial big data