The management of Fog Computing applications is a challenging task that requires dealing with a dynamic and resource-scarce environment. We argue that approaches leveraging Value-of-Information (VoI) concepts and tools are particularly interesting to support the realization of that objective. This paper describes innovative methodologies and reference models for the service fabric management of Fog Computing services. First, we formalize the VoI concept and discuss its adoption in Fog Computing environments. Then, we propose a model that aims at maximizing the allocation of Fog services from a value-based perspective. To overcome the complexity of this model, we present two possible solutions (a simplified user-specific VoI model and a distance based heuristic) and we compare them by adopting meta-heuristics as optimization techniques. Then, we investigate the adoption of a hybrid model, which combines the distance based heuristic with the simplified user-specific VoI model. Experimental results prove the validity of all presented approaches and highlight the soundness of the distance based heuristic, which is capable of reaching the 91% performance of the simplified user-specific VoI model in a very short amount of time. This makes it a suitable approach for online optimization of resources in Fog Computing.

A Value‐of‐Information‐based management framework for fog services

Poltronieri, Filippo
Primo
;
Tortonesi, Mauro
Secondo
;
Stefanelli, Cesare
Penultimo
;
2022

Abstract

The management of Fog Computing applications is a challenging task that requires dealing with a dynamic and resource-scarce environment. We argue that approaches leveraging Value-of-Information (VoI) concepts and tools are particularly interesting to support the realization of that objective. This paper describes innovative methodologies and reference models for the service fabric management of Fog Computing services. First, we formalize the VoI concept and discuss its adoption in Fog Computing environments. Then, we propose a model that aims at maximizing the allocation of Fog services from a value-based perspective. To overcome the complexity of this model, we present two possible solutions (a simplified user-specific VoI model and a distance based heuristic) and we compare them by adopting meta-heuristics as optimization techniques. Then, we investigate the adoption of a hybrid model, which combines the distance based heuristic with the simplified user-specific VoI model. Experimental results prove the validity of all presented approaches and highlight the soundness of the distance based heuristic, which is capable of reaching the 91% performance of the simplified user-specific VoI model in a very short amount of time. This makes it a suitable approach for online optimization of resources in Fog Computing.
2022
Poltronieri, Filippo; Tortonesi, Mauro; Morelli, Alessandro; Stefanelli, Cesare; Suri, Niranjan
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2470607
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