Load Balancing by Min-conflicts scheduling with Enhanced Eagle Aquila Optimization for Fog Computing Environment

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.