An Investigation of Task Offloading Latency in Edge-Cloud Environment Using Machine Learning Techniques

The volume of information produced by Internet of Things (IoT) gadgets has significantly expanded along with how many of these gadgets are connected to the Internet. Now a day’s Edge-Cloud computing has a major roll to store the data. Edge computing is close proximity to the network's edge enables quick data processing and supporting user request. Therefore, we present an Edge-Cloud system design that enables scheduling IoT application offloading operations reducing a massive volume of data being transmitted in the network.