Graph analytics workflows enactment on just in time data centres, Position Paper

TL;DR

This position paper envisions a flexible, virtualized data centre architecture that dynamically supports graph analytics workflows across edge, fog, and data centre layers, enabling adaptive decision-making in data science.

Contribution

It proposes a novel concept of a disaggregated, virtual data centre that dynamically allocates resources for graph analytics workflows across multiple layers.

Findings

Conceptual framework for multirole decision-making systems

Design principles for disaggregated data centres

Potential for improved resource utilization and flexibility

Abstract

This paper discusses our vision of multirole-capable decision-making systems across a broad range of Data Science (DS) workflows working on graphs through disaggregated data centres. Our vision is that an alternative is possible to work on a disaggregated solution for the provision of computational services under the notion of a disaggregated data centre. We define this alternative as a virtual entity that dynamically provides resources crosscutting the layers of edge, fog and data centre according to the workloads submitted by the workflows and their Service Level Objectives.