Fog computing is a promising architectural to alleviate increasingly intensive transmission over the network. In addition to the data transmission capability, a fog node (FN) also has spare resources of data storage and computing. In this paper, we study the computation offloading scenario that takes advantage of fog architecture and utilizes the FN resources. A social welfare maximization problem is formulated to distribute the data among FNs based on the trade-off between the considered computational cost and communication cost. A distributed adaptation algorithm is developed based on a Jacobi-Proximal alternating direction method of multipliers (ADMM) algorithm. The computational burden for solving the optimization problem is fully distributed to FNs, software defined network (SDN) controller, where local variables of FNs are updated in parallel. Performance of the proposed algorithm is validated with simulation results.
Distributed Computation Offloading in Resource Limited Fog Computing
2019-09-01
488754 byte
Conference paper
Electronic Resource
English