Towards a Decentralised Application-Centric Orchestration Framework in the Cloud-Edge Continuum

TL;DR

Swarmchestrate introduces a decentralised, application-centric orchestration framework for the Cloud-Edge continuum, inspired by swarm self-organisation. It defines an OS composed of Resource Agents, Knowledge Management, and a Swarm-based execution model to deploy TOSCA-described applications across heterogeneous cloud and edge resources, leveraging Kubernetes for cluster management. The paper presents a simulation-based evaluation comparing Cost Function and Borda voting for resource selection, demonstrating how QoS priorities and reliability influence deployment efficiency, cost, and energy usage. Initial results indicate the approach can coordinate multi-provider resources and enable scalable, efficient deployment, with ongoing work to implement runtime self-organisation and real-world prototyping. The work is supported by a European Horizon project and open-source tooling for reproducibility.

Abstract

The efficient management of complex distributed applications in the Cloud-Edge continuum, including their deployment on heterogeneous computing resources and run-time operations, presents significant challenges. Resource management solutions -- also called orchestrators -- play a pivotal role by automating and managing tasks such as resource discovery, optimisation, application deployment, and lifecycle management, whilst ensuring the desired system performance. This paper introduces Swarmchestrate, a decentralised, application-centric orchestration framework inspired by the self-organising principles of Swarms. Swarmchestrate addresses the end-to-end management of distributed applications, from submission to optimal resource allocation across cloud and edge providers, as well as dynamic reconfiguration. Our initial findings include the implementation of the application deployment phase within a Cloud-Edge simulation environment, demonstrating the potential of Swarmchestrate. The results offer valuable insight into the coordination of resource offerings between various providers and optimised resource allocation, providing a foundation for designing scalable and efficient infrastructures.

Figures (3)

• Figure 1: Swarmchestrate architecture
• Figure 2: Illustrative example of application deployment in Swarmchestrate
• Figure 3: Energy consumption per node with energy priority (left) and latency priority (right)