Abstract
This work proposes a dynamic numerology scheme assignment framework to provision mobile-edge computing (MEC) for massive Internet of Things (IoT) networks via unmanned aerial vehicles (UAVs). IoT devices (IoTDs) usually lack computational power; thus, they offload their computational tasks to MEC servers. To enhance their battery lives, an optimal assignment of a numerology scheme to each IoTD is imperative; it also enhances the system spectral efficiency. In this work, we bring MEC services closer to a massive IoT network by deploying a UAV-MEC and allocate communication resources of the sub-6-GHz band dependent on the numerology schemes to each IoTD. We formulate a multiobjective optimization problem (MOOP) with two countering objectives to maximize the uplink spectral efficiency while minimizing the IoTDs' energy consumption. We solve a series of sequential subproblems, which are convex approximations of the MOOP and propose a novel algorithm to allocate computational resources, assign numerology schemes, and communication resources for each of the IoTDs. Our extensive simulation results validate the proposed aims herein.
Original language | English (US) |
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Pages (from-to) | 23860-23868 |
Number of pages | 9 |
Journal | IEEE Internet of Things Journal |
Volume | 9 |
Issue number | 23 |
DOIs | |
State | Published - Dec 1 2022 |
All Science Journal Classification (ASJC) codes
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications
Keywords
- Energy consumption
- Internet of Things
- mobile-edge computing (MEC)
- numerology
- spectral efficiency
- unmanned aerial vehicle (UAV)