TY - GEN
T1 - Distributed fair randomized (DFR)
T2 - 4th International Conference on Fog and Mobile Edge Computing, FMEC 2019
AU - Beraldi, Roberto
AU - Alnuweiri, Hussein
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85071673285&partnerID=8YFLogxK
U2 - 10.1109/FMEC.2019.8795339
DO - 10.1109/FMEC.2019.8795339
M3 - Conference contribution
AN - SCOPUS:85071673285
T3 - 2019 4th International Conference on Fog and Mobile Edge Computing, FMEC 2019
SP - 29
EP - 36
BT - 2019 4th International Conference on Fog and Mobile Edge Computing, FMEC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 June 2019 through 13 June 2019
ER -