  In this paper, we intend to reduce the operational cost of cloud data centers
with the help of fog devices, which can avoid the revenue loss due to wide-area
network propagation delay and save network bandwidth cost by serving nearby
cloud users. Since fog devices may not be owned by a cloud service provider,
they should be compensated for serving the requests of cloud users. When taking
economical compensation into consideration, the optimal number of requests
processed locally by each fog device should be decided. As a result, existing
load balancing schemes developed for cloud data centers can not be applied
directly and it is very necessary to redesign a cost-ware load balancing
algorithm for the fog-cloud system. To achieve the above aim, we first
formulate a fog-assisted operational cost minimization problem for the cloud
service provider. Then, we design a parallel and distributed load balancing
algorithm with low computational complexity based on Proximal Jacobian
Alternating Direction Method of Multipliers (PJ-ADMM). Finally, extensive
simulation results show the effectiveness of the proposed algorithm.
