
arXiv: 2504.00761
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.
Accepted for publication in the 9th IEEE International Conference on Fog and Edge Computing 2025
Computer Science - Networking and Internet Architecture, Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Neural and Evolutionary Computing, Distributed, Parallel, and Cluster Computing (cs.DC), Neural and Evolutionary Computing (cs.NE)
Computer Science - Networking and Internet Architecture, Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Neural and Evolutionary Computing, Distributed, Parallel, and Cluster Computing (cs.DC), Neural and Evolutionary Computing (cs.NE)
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