Swarmchestrate Towards a Fully Decentralised Framework for Orchestrating Applications in the Cloud-to-Edge Continuum /

Collecting and analysing large amounts of data in the Cloud-to-Edge computing continuum raises novel challenges that traditional centralised orchestration solutions cannot handle efficiently. To overcome the limitations of current centralised application management approaches, this paper presents a...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Kiss T
Ullah A
Terstyanszky G
Kao O
Becker S
Verginadis Y
Michalas A
Stankovski V
Kertész Attila
Ricci E
Altmann J
Egger B
Tusa F
Kovács József
Lovas Róbert
Dokumentumtípus: Cikk
Megjelent: 2024
Sorozat:Lecture Notes on Data Engineering and Communications Technologies 203
Tárgyszavak:
doi:10.1007/978-3-031-57931-8_9

mtmt:34795721
Online Access:http://publicatio.bibl.u-szeged.hu/36211
Leíró adatok
Tartalmi kivonat:Collecting and analysing large amounts of data in the Cloud-to-Edge computing continuum raises novel challenges that traditional centralised orchestration solutions cannot handle efficiently. To overcome the limitations of current centralised application management approaches, this paper presents a fully decentralised application-level orchestrator, based on the notion of self-organised interdependent Swarms. Application microservices are managed in a dynamic Orchestration Space by decentralised Orchestration Agents, governed by distributed intelligence that provides matchmaking between application requirements and resources, and supports the dynamic self-organisation of Swarms. Knowledge and trust, essential for the operation of the Orchestration Space, are managed through blockchain-based trusted solutions and the utilisation of emerging methods such as Self-Sovereign Identities (SSI) and Distributed Identifiers (DID). End-to-end security of the overall system is assured by utilising state-of-the-art cryptographic and privacy-preserving data analytics algorithms. A digital twin, that runs in parallel to the physical system, further improves its behaviour with predictive feedback. The presented concept is going to be implemented in the EU-funded Swarmchestrate project that starts in 2024. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Terjedelem/Fizikai jellemzők:89-100
ISSN:2367-4512