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Research output: Contribution to Journal/Magazine › Letter › peer-review
Research output: Contribution to Journal/Magazine › Letter › peer-review
}
TY - JOUR
T1 - On-demand Service Deployment Strategies for Fog-as-a-Service Scenarios
AU - Bozorgchenani, Arash
AU - Tarchi, Daniele
AU - Cerroni, Walter
N1 - ©2021 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2021/1/29
Y1 - 2021/1/29
N2 - Service deployment at the network edge is a promising area that has been studied recently in the literature. In this work we have investigated a Fog-as-a-Service scenario, where multiple Server Fog Nodes (SFNs) can serve multiple Client FogNodes (CFNs) by exploiting different service deployment models, i.e., SaaS, PaaS, and IaaS, in a flexible way. The system has been modeled as a Size-Constrained Weighted Set Cover Problem aiming at maximizing the amount of satisfied CFNs exploiting a heterogeneous service deployment architecture, while minimizing the service completion time in a computation offloading scenario. In the simulation results section, we analyze the performance of different methods in terms of percentage of CFNs’ offloading requests satisfaction and offloading delay.
AB - Service deployment at the network edge is a promising area that has been studied recently in the literature. In this work we have investigated a Fog-as-a-Service scenario, where multiple Server Fog Nodes (SFNs) can serve multiple Client FogNodes (CFNs) by exploiting different service deployment models, i.e., SaaS, PaaS, and IaaS, in a flexible way. The system has been modeled as a Size-Constrained Weighted Set Cover Problem aiming at maximizing the amount of satisfied CFNs exploiting a heterogeneous service deployment architecture, while minimizing the service completion time in a computation offloading scenario. In the simulation results section, we analyze the performance of different methods in terms of percentage of CFNs’ offloading requests satisfaction and offloading delay.
KW - Fog Computing
KW - Service Deployment
KW - Computation offloading
KW - Optimization
KW - Weighted Set Cover Problem
U2 - 10.1109/LCOMM.2021.3055535
DO - 10.1109/LCOMM.2021.3055535
M3 - Letter
VL - 25
SP - 1500
EP - 1504
JO - IEEE Communications Letters
JF - IEEE Communications Letters
SN - 1089-7798
IS - 5
ER -