Fog Computing can facilitate the adoption of the Everything-as-a-Service paradigm in infrastructure segments that are located closer to the end user, or to the data source, compared to typical Cloud solutions. This enables combining the advantages of flexible service deployment models with the need to cope with the strict requirements – especially in terms of latency – of emerging applications in softwarized networks. Along comes the need to consider aspects of service orchestration specific to the Fog environment and its intrinsically dynamic nature. In this paper we propose an architecture for flexible Fog Computing service orchestration, with a particular focus on the awareness of service deployment models. We discuss the design choices and describe the components and operations of the proposed orchestration system. We then present a complete working implementation of such architecture, including insights on its ability to handle critical orchestration functions such as service discovery and resource monitoring. We also report on the experimental validation of the system and the performance evaluation on real-world equipment, proving the feasibility and the effectiveness of the approach on a dynamic Fog infrastructure. We complement the work by presenting the results of a combinatorial analysis, validated by simulation, of the service model-aware resource selection process. As a result of our investigation, we show that Fog services can be effectively deployed in a matter of a few seconds, or even in less than one second when suitable Fog nodes are available, taking advantage of the awareness of the available service models.

A Fog Computing Orchestrator Architecture with Service Model Awareness / Davoli G.; Cerroni W.; Borsatti D.; Valieri M.; Tarchi D.; Raffaelli C.. - In: IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT. - ISSN 1932-4537. - ELETTRONICO. - 19:3(2022), pp. 9638988.2131-9638988.2147. [10.1109/TNSM.2021.3133354]

A Fog Computing Orchestrator Architecture with Service Model Awareness

Davoli G.;Cerroni W.;Borsatti D.;Tarchi D.;Raffaelli C.
2022

Abstract

Fog Computing can facilitate the adoption of the Everything-as-a-Service paradigm in infrastructure segments that are located closer to the end user, or to the data source, compared to typical Cloud solutions. This enables combining the advantages of flexible service deployment models with the need to cope with the strict requirements – especially in terms of latency – of emerging applications in softwarized networks. Along comes the need to consider aspects of service orchestration specific to the Fog environment and its intrinsically dynamic nature. In this paper we propose an architecture for flexible Fog Computing service orchestration, with a particular focus on the awareness of service deployment models. We discuss the design choices and describe the components and operations of the proposed orchestration system. We then present a complete working implementation of such architecture, including insights on its ability to handle critical orchestration functions such as service discovery and resource monitoring. We also report on the experimental validation of the system and the performance evaluation on real-world equipment, proving the feasibility and the effectiveness of the approach on a dynamic Fog infrastructure. We complement the work by presenting the results of a combinatorial analysis, validated by simulation, of the service model-aware resource selection process. As a result of our investigation, we show that Fog services can be effectively deployed in a matter of a few seconds, or even in less than one second when suitable Fog nodes are available, taking advantage of the awareness of the available service models.
2022
A Fog Computing Orchestrator Architecture with Service Model Awareness / Davoli G.; Cerroni W.; Borsatti D.; Valieri M.; Tarchi D.; Raffaelli C.. - In: IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT. - ISSN 1932-4537. - ELETTRONICO. - 19:3(2022), pp. 9638988.2131-9638988.2147. [10.1109/TNSM.2021.3133354]
Davoli G.; Cerroni W.; Borsatti D.; Valieri M.; Tarchi D.; Raffaelli C.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/859018
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