  By bringing computing capacity from a remote cloud environment closer to the
user, fog computing is introduced. As a result, users can access the services
from more nearby computing environments, resulting in better quality of service
and lower latency on the network. From the service providers' point of view,
this addresses the network latency and congestion issues. This is achieved by
deploying the services in cloud and fog computing environments. The
responsibility of service providers is to manage the heterogeneous resources
available in both computing environments. In recent years, resource management
strategies have made it possible to efficiently allocate resources from nearby
fog and clouds to users' applications. Unfortunately, these existing resource
management strategies fail to give the desired result when the service
providers have the opportunity to allocate the resources to the users'
application from fog nodes that are at a multi-hop distance from the nearby fog
node. The complexity of this resource management problem drastically increases
in a MultiFog-Cloud environment. This problem motivates us to revisit and
present a novel Heuristic Resource Allocation and Optimization algorithm in a
MultiFog-Cloud (HeRAFC) environment. Taking users' application priority,
execution time, and communication latency into account, HeRAFC optimizes
resource utilization and minimizes cloud load. The proposed algorithm is
evaluated and compared with related algorithms. The simulation results show the
efficiency of the proposed HeRAFC over other algorithms.
