A Hybrid Load Balancing Optimization For Cloud Iot Edge Application

Abstract

Cloud computing and Storage services are traditionally utilized for making and provisioning Virtual Machines (VMs) to have bunch and stream processing applications. This method offer sight control of the foundation where the product is running, yet comes at significant expense of upkeep, as each machine must be provisioned separately. With regards to adaptability and optimization, there is a strong need for careful capacity planning and manual intervention even with automated tools. To alleviate these issues, there current trend is to use containers instead of VMs as the minimal computation unit in the cloud. The Sense Things Internet will as simple as a person with a heart monitor installed on a smartphone or a car with coherent detectors alerting the driver to an imminent threat. Under the umbrella of IoT falls any human build or general object that can be represented as an IP address and that can transmit data over a network. Effectively all programs enhance each other until the relationship is mutual. The IoT is the network, since the cloud is the central hub for computing.This paper describes the proposed methodology to organize the optimization technique to achieve the load balancing and cloud edge to IOT connectivity. We employ a hybrid cloud-edge optimization technique to minimize the load and improves the computation efficiency. Allotment of the application to that same desktop server including its client should move to some specified portion that are optimized through the service manager.