Litcius/Paper detail

Computation Offloading in Multi-Cell Networks With Collaborative Edge-Cloud Computing: A Game Theoretic Approach

Liantao Wu, Peng Sun, Zhibo Wang, Yanjun Li, Yang Yang

2023IEEE Transactions on Mobile Computing48 citationsDOI

Abstract

With the widespread application of 5G and the Internet of things (IoT), edge computing and cloud computing have been collaboratively utilized for task offloading and processing. However, though the massive devices (e.g., smartphones) are organized into multi-cells, most of the existing works do not explore the computation offloading for edge-cloud computing under inter-cell interference. Thus, the offloading decisions may be inappropriate as the transmission rate is overestimated. To address this issue, we propose COMEC, a novel Computation Offloading scheme in Multi-cell networks with Edge-Cloud collaboration, which could minimize the total cost in terms of delay and energy consumption. Specifically, we first formulate COMEC as an optimization problem taking into account inter-cell interference. Then, considering the offloading decisions of all users are coupled, a non-cooperative game is formulated to minimize the total cost of each user in a distributed manner. We prove that this game is a general (ordinal) potential game and possesses a pure strategy Nash equilibrium (NE). Based on the finite improvement property of the potential game, we develop the corresponding computation offloading algorithm to achieve the NE. Finally, simulation results show that the proposed scheme can achieve superior performance in overall system cost compared with other baselines.

Topics & Concepts

Computation offloadingComputer scienceCloud computingPotential gameDistributed computingNash equilibriumEdge computingMobile edge computingEnhanced Data Rates for GSM EvolutionGame theoryComputationComputer networkMathematical optimizationAlgorithmArtificial intelligenceMicroeconomicsMathematicsEconomicsOperating systemIoT and Edge/Fog ComputingMolecular Communication and NanonetworksPrivacy-Preserving Technologies in Data