A Dynamic Cost Model to Minimize Energy Consumption and Processing Time for IoT Tasks in a Mobile Edge Computing Environment.

The rapid growth of IoT devices and applications with data-intensive processing has led to energy consumption and latency concerns. These applications tend to offload task processing to remote Data Centers in the Cloud, distant from end-users, increasing communication latency and energy costs. In such a context, this work proposes a dynamic cost model to minimize energy consumption and total elapsed time for IoT devices in Mobile Edge Computing environments. The solution presents a Time and Energy Minimization Scheduler (TEMS) that executes the cost model, validated through simulation, which resulted in a reduction in energy consumption by up to 51.61% and in task completion time by up to 86.65%.