Energy consumption

Monetary policy

Ecology

Biology

Computation offloading

Microeconomics

Server

Telecommunications

Economics

Scalability

Computer science

Mathematical optimization

Potential game

Distributed computing

Adaptability

Computer network

Database

Mathematics

Monetary economics

Enhanced Data Rates for GSM Evolution

Nash equilibrium

Price of anarchy

Mobile edge computing

Game theory

Edge computing

Price of stability

IEEE Internet of Things Journal

The emerging mobile-edge computing paradigm provides opportunities for the resource-hungry mobile devices (MDs) to migrate computation. In order to satisfy the requirements of MDs in terms of latency and energy consumption, recent researches proposed diverse computation offloading schemes. However, they either fail to consider the potential computing resources at the edge, or ignore the selfish behavior of users and the dynamic resource adaptability. To this end, we study the computation offloading problem and take into consideration the dynamic available resource of idle devices and the selfish behavior of users. Furthermore, we propose a game theoretic offloading method by regarding the computation offloading process as a resource contention game, which minimizes the individual task execution cost and the system overhead. Utilizing the potential game, we prove the existence of Nash equilibrium (NE), and give a lightweight algorithm to help the game reach a NE, wherein each user can find an optimal offloading strategy based on three contention principles. Additionally, we conduct analysis of computational complexity and the Price of Anarchy (PoA), and deploy three baseline methods to compare with our proposed scheme. Numerical results illustrate that our scheme can provide high-quality services to users, and also demonstrate the effectiveness, scalability and dynamic resource adaptability of our proposed algorithm in a multiuser network.

D2D-Enabled Mobile-Edge Computation Offloading for Multiuser IoT Network