Due to enhancements in Internet of Things (IoT) technology, users can now control numerous IoT devices that are integrated for a system (e.g., smart building management system, smart factory, etc.) through mobile user equipment (UE). As the number of controllable IoT devices increases, the amount of data that needs to be processed has increased along with the energy consumption. Since many IoT devices and most UEs are battery operated, minimizing the energy consumption is very important. One solution is to have a multiaccess edge computing (MEC) system conduct the computation instead of the IoT devices and UEs to help save their energy. In this article, an energy-optimized offloading approach that uses MEC computing support to process cooperative tasks is investigated. An optimization problem model is developed to minimize the energy consumption of IoT devices and UEs that have service delay limits. The numerical results demonstrate that the proposed IoT and UE popularity-based energy optimization (IPEO) scheme provides a better performance compared to the conventional MEC offloading methods.
|Number of pages||13|
|Journal||IEEE Internet of Things Journal|
|Publication status||Published - 2022 Mar 1|
Bibliographical notePublisher Copyright:
© 2014 IEEE.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications