Seagull optimization algorithm based multi-objective VM placement in edge-cloud data centers

Edge-Cloud Datacenters (ECDCs) have been massively exploited by the owners of technology and industrial centers to satisfy user demand. At same time, amount energy used these data is considerable. To address this challenge, Virtual Machine (VM) placement ECDCs plays an important role; therefore, assigning VM properly physical machines (PM) can significantly decrease consumption. The applied technique simultaneously must consider additional objectives involving traffic power usage network elements, which makes it a challenging problem. This paper proposes multi-objective approach in edge-cloud centers, uses Seagull optimization optimize together. In strategy, among PMs reduced concentrating communications VMs on reduce transferred through PMs’ consumption consolidating fewer PMs, consumes less energy. We evaluate with simulations CloudSim test two different topologies, VL2 (Virtual Layer 2) three-tier, validate that proposed effectively ECDCs. experimental results show our method 5.5% while reducing 70% components 80%.