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

2020; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-030-65310-1_8

1611-3349

João Luiz Grave Gross, Kassiano J. Matteussi, Julio César Santos dos Anjos, Cláudio Fernando Resin Geyer,

Cloud Computing and Resource Management

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%.