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Computation Offloading and User-Clustering Game in Multi-Channel Cellular Networks for Mobile Edge Computing.
Yan-Yun Huang1, Pi-Chung Wang1
1Department of Computer Science and Engineering, National Chung Hsing University, Taichung 402, Taiwan.
This study introduces a distributed algorithm for mobile edge computing that optimizes device clustering and computation offloading. The novel approach enhances transmission efficiency, reducing energy consumption and improving application responsiveness for mobile devices.
Area of Science:
- Computer Science
- Electrical Engineering
- Telecommunications
Background:
- Mobile devices utilize mobile edge computing (MEC) for enhanced energy efficiency and responsiveness via computation offloading.
- Device transmissions in MEC can cause interference, degrading upload rates and increasing transmission delays.
- Existing clustering methods lack distributed algorithms for optimizing both clustering and computation offloading.
Purpose of the Study:
- To develop a distributed algorithm for optimizing computation offloading in mobile edge computing.
- To minimize mobile device energy consumption by adaptively clustering devices and improving transmission efficiency.
- To address the challenge of interference and transmission delay in dense mobile device environments.
Main Methods:
- Formulated the distributed optimization problem of clustering and computation offloading as a potential game.
- Constructed the potential game and demonstrated the existence of a Nash equilibrium.
- Proposed a novel distributed algorithm for adaptive clustering and computation offloading based on game theory.
Main Results:
- Simulations confirmed the proposed algorithm's effectiveness in improving offloading efficiency for mobile devices in MEC.
- The algorithm successfully enhanced transmission efficiency, leading to reduced energy consumption.
- Simultaneous improvements in mobile device energy efficiency and application responsiveness were observed.
Conclusions:
- The developed distributed algorithm offers an effective solution for optimizing computation offloading in mobile edge computing.
- Adaptive clustering and game-theoretic approaches can mitigate interference and enhance transmission efficiency.
- The findings contribute to more energy-efficient and responsive mobile edge computing systems.

