Development of a framework for adaptive productivity management for edge computing based IoT applications

Data collected from IoT devices can be encrypted and analysed by computer resources at the network edge in your nearby cloud to alleviate congestion load infrastructure, whilst different applications indeed run clouds reduce time among both users such as mobile user devices) clouds. Taking into account geographical temporal characteristics of working loads each application, allocation across for application influences application’s response time. While it decrease latency allocating users’ requests local cloud, delay unpleasant if an associated virtual machine is overextended a cloudlet. In order overcome this problem, we are developing application-known workload assignment scheme minimise times deciding destination types amount computing assigned application. This approach takes consideration delays compute delay, more likely less loaded. meantime, system adjusts various on basis its therefore reduces computational all requests. Comprehensive simulations have confirmed efficiency control strategy.