Decentralized Computation Offloading Game For Mobile Cloud Computing
arXiv:1404.3200 · doi:10.1109/TPDS.2014.2316834
Abstract
Mobile cloud computing is envisioned as a promising approach to augment computation capabilities of mobile devices for emerging resource-hungry mobile applications. In this paper, we propose a game theoretic approach for achieving efficient computation offloading for mobile cloud computing. We formulate the decentralized computation offloading decision making problem among mobile device users as a decentralized computation offloading game. We analyze the structural property of the game and show that the game always admits a Nash equilibrium. We then design a decentralized computation offloading mechanism that can achieve a Nash equilibrium of the game and quantify its efficiency ratio over the centralized optimal solution. Numerical results demonstrate that the proposed mechanism can achieve efficient computation offloading performance and scale well as the system size increases.
The paper has been accepted by IEEE Transactions on Parallel and Distributed Systems (TPDS) Vol. 26, No. 4, pp. 974 - 983, March 2015
Cited by in corpus (12)
- Dynamic Computation Offloading for Mobile-Edge Computing with Energy Harvesting Devices
- Joint Optimization of Radio and Computational Resources for Multicell Mobile-Edge Computing
- Resource Management in Fog/Edge Computing: A Survey
- Joint Energy Minimization and Resource Allocation in C-RAN with Mobile Cloud
- Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends
- Resource Sharing of a Computing Access Point for Multi-user Mobile Cloud Offloading with Delay Constraints
- A Review on Computational Intelligence Techniques in Cloud and Edge Computing
- Multi-user Multi-task Offloading and Resource Allocation in Mobile Cloud Systems
- A Comprehensive Survey of Potential Game Approaches to Wireless Networks
- Delay Sensitive Task Offloading in the 802.11p Based Vehicular Fog Computing Systems
- Power Minimization Based Joint Task Scheduling and Resource Allocation in Downlink C-RAN
- Hybrid Online-Offline Learning for Task Offloading in Mobile Edge Computing Systems