A roadmap on learning and reasoning for distributed computing continuum ecosystems

Morichetta, Andrea; Pujol, Víctor Casamayor; Dustdar, Schahram

doi:10.1109/edge53862.2021.00021

Cited by 15 publications

(2 citation statements)

References 26 publications

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“…In more detail, Morichetta et al [99] recognize for example the following particular research topics in relation to CCM:…”

Section: A Computing Continuum Management Modelmentioning

confidence: 99%

Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration

Kokkonen¹,

Lovén²,

Motlagh³

et al. 2022

Preprint

Self Cite

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Future AI applications require performance, reliability, and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and focus on AI for edge, that is, the AI methods used in resource orchestration. We claim that to support the constantly growing requirements of intelligent applications in the device-edge-cloud computing continuum, resource orchestration needs to embrace edge AI and emphasize local autonomy and intelligence. To justify the claim, we provide a general definition for continuum orchestration, and look at how current and emerging orchestration paradigms are suitable for the computing continuum. We describe certain major emerging research themes that may affect future orchestration, and provide an early vision of an orchestration paradigm that embraces those research themes. Finally, we survey current key edge AI methods and look at how they may contribute into fulfilling the vision of future continuum orchestration.

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“…In more detail, Morichetta et al [99] recognize for example the following particular research topics in relation to CCM:…”

Section: A Computing Continuum Management Modelmentioning

confidence: 99%

Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration

Kokkonen¹,

Lovén²,

Motlagh³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…ML approaches have been used in continuum management [13], but mostly for single and isolated purposes, such as predicting future loads, optimising service locations, etc. Despite some attempts toward unified approaches based on specific AI techniques [14], what is still missing is the capability to create joint and coordinated learning and reasoning [15]. The complex architecture of the continuum also means the traditional single-model ML will not work in practice for real-time continuum management, and novel edge-native AI is needed [16].…”

Section: Related Work Summary and Outlookmentioning

confidence: 99%

Towards Cognitive Self-Management of IoT-Edge-Cloud Continuum based on User Intents

Song

Soylu

Roman

2022

2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC)

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Elasticity of the computing continuum with ondemand availability allows for automated provisioning and release of computing resources as needed; however, this selfmanagement capability is severely limited due to the lack of knowledge on historical and timely resource utilisation and means for stakeholders to express their needs in a high-level manner. In this paper, we introduce and discuss a new conceptintent-based cognitive continuum for sustainable elasticity.

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1The Future of Business Management with the Power of Distributed Systems and Computing

Podile,

Kulshrestha,

Goswami

et al. 2024

Meta Heuristic Algorithms for Advanced Distributed Systems

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A roadmap on learning and reasoning for distributed computing continuum ecosystems

Cited by 15 publications

References 26 publications

Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration

Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration

Towards Cognitive Self-Management of IoT-Edge-Cloud Continuum based on User Intents

1The Future of Business Management with the Power of Distributed Systems and Computing

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