Business

Computation offloading

Computer network

Mathematics

Nash equilibrium

Price of anarchy

Latency (audio)

Server

Operating system

Distributed computing

Mathematical optimization

Monetary policy

Enhanced Data Rates for GSM Evolution

Marketing

Economics

Microeconomics

Game theory

Price of stability

Vendor

Mobile edge computing

Potential game

Edge computing

Computer science

Monetary economics

Cloud computing

Telecommunications

IEEE Transactions on Parallel and Distributed Systems

Edge Computing provides mobile and Internet-of-Things (IoT) app vendors with a new distributed computing paradigm which allows an app vendor to deploy its app at hired edge servers distributed near app users at the edge of the cloud. This way, app users can be allocated to hired edge servers nearby to minimize network latency and energy consumption. A cost-effective edge user allocation (EUA) requires maximum app users to be served with minimum overall system cost. Finding a centralized optimal solution to this EUA problem is NP-hard. Thus, we propose EUAGame, a game-theoretic approach that formulates the EUA problem as a potential game. We analyze the game and show that it admits a Nash equilibrium. Then, we design a novel decentralized algorithm for finding a Nash equilibrium in the game as a solution to the EUA problem. The performance of this algorithm is theoretically analyzed and experimentally evaluated. The results show that the EUA problem can be solved effectively and efficiently.

A Game-Theoretical Approach for User Allocation in Edge Computing Environment