Abstract:
Fog Computing" (FC) is a collection of abstracted computer resources. An Internet-based growth where
resources are offered as a service through the Internet which is rapidly scalable and abstracted has grown
to be a serious issue. The Fog server optimization routine becomes a difficult problem in fog computing. It
primarily focuses on Load Balancing (LB) in fog data centers to increase the performance of host and
reduce the number of active host machines. It should use migration strategies to move the Virtual
Machines(VM) from the overloaded host to the lighter host to equalize the load throughout the whole
information center. Min-conflicts scheduling with Enhanced Eagle Aquila Optimization (MCS-EEAO)
approach is proposed to handle a Constraint Satisfaction Problem (CSP) in the fog sever. Dynamic Compare
and Balance Algorithm (DCABA) also reduces the number of host machines that need to be maintained
and the cost of fog services. In contrast to conventional server optimization schemes that only take into
account LB and the allocation of resources based on the consumption of CPU, RAM, and Bandwidth in
physical servers. High latency and safety issues are important challenges for fog computing The proposed
system is based on fog technology which offers safety control, data management, fast response and
processing time. It also reduces the service costs in the fog business while making efficient use of the
resources that are already accessible.
