Multi-Objective Optimization-Oriented Resource Allocation in the Fog Environment

Fog computing is a decentralized computer system where data, processing, storage, as well applications are located anywhere between the cloud and data source. takes closer to users, decreasing latency allows deployment of new delay-sensitive appliances. An important feature fog-cloud network process decision-making on assigning resources execute tasks application. This paper aims propose resource allocation strategy for fog that determines effective under consideration objectives includes constraints like credibility score, concurrency, price affordability task time computation. Moreover, score determined based execution efficiency, Service response rate, access reliability Reboot rate. Thereby, optimal handled by Hybrid Monarch-Dragon Algorithm (HM-DA) hybrids concept Dragonfly (DA) Monarch Butterfly Optimization (MBO) algorithm.