Incentive Propagation Mechanism of Computation Offloading in Fog-enabled D2D Networks
Yang Liu, Hongbin Zhu, Haifeng Wang, Hua Lin Qian, Yang Yang · 2018
Fog computing is a promising technology to provide economical and low latency data services, where devices can offload their intensive computation tasks to other devices which have idle computation resources. However, devices can only execute task offloading within their neighbors in conventional computation offloading schemes, which are not efficient for the whole network. We propose an incentive propagation mechanism (IPM) in fog-enabled device-to-device (D2D) networks, which incentivizes devices to not only truthfully report their charge price on the computation task, but also further propagate the task information to other devices. The proposed algorithm achieves more efficient computation offloading of the entire fog network. Simulation results validate its effectiveness.