Fog computing promises to support many emerging classes of applications that can't be rely on a cloud-only backend. Fog-to-Fog (F2F) cooperation is suggested in the openFog's Fog computing Reference Architecture, now adopted as an IEEE standard, as a way to improve the computation service provided by this computing delivery model.In this paper, we propose DFR-Distributed Fair Randomized, a distributed F2F cooperation algorithm that allows for sharing computation resources among fog providers that agree on a (reasonable) measure of fairness. We adopt an analytical approach to study the cooperation problem of providers subject to different load conditions. We initially put the cooperation problem in the light of a simple game-theory framework to capture the selfish behavior of providers without any fairness criteria and its consequence in limiting cooperation. Then, we cast the problem as an optimization problem that incorporates fairness. Preliminary simulations results show how DFR converges to the predicted optimal value. © 2019 IEEE.

Distributed fair randomized (DFR): A resource sharing protocol for fog providers / Beraldi, R.; Alnuweiri, H.. - (2019), pp. 29-36. (Intervento presentato al convegno 4th International Conference on Fog and Mobile Edge Computing, FMEC 2019 tenutosi a Roma; Italy) [10.1109/FMEC.2019.8795339].

Distributed fair randomized (DFR): A resource sharing protocol for fog providers

Beraldi R.
;
2019

Abstract

Fog computing promises to support many emerging classes of applications that can't be rely on a cloud-only backend. Fog-to-Fog (F2F) cooperation is suggested in the openFog's Fog computing Reference Architecture, now adopted as an IEEE standard, as a way to improve the computation service provided by this computing delivery model.In this paper, we propose DFR-Distributed Fair Randomized, a distributed F2F cooperation algorithm that allows for sharing computation resources among fog providers that agree on a (reasonable) measure of fairness. We adopt an analytical approach to study the cooperation problem of providers subject to different load conditions. We initially put the cooperation problem in the light of a simple game-theory framework to capture the selfish behavior of providers without any fairness criteria and its consequence in limiting cooperation. Then, we cast the problem as an optimization problem that incorporates fairness. Preliminary simulations results show how DFR converges to the predicted optimal value. © 2019 IEEE.
2019
4th International Conference on Fog and Mobile Edge Computing, FMEC 2019
Computation theory; Edge computing; Fog; Game theory; IEEE Standards
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Distributed fair randomized (DFR): A resource sharing protocol for fog providers / Beraldi, R.; Alnuweiri, H.. - (2019), pp. 29-36. (Intervento presentato al convegno 4th International Conference on Fog and Mobile Edge Computing, FMEC 2019 tenutosi a Roma; Italy) [10.1109/FMEC.2019.8795339].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1320330
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