DISCO: Distributed computation offloading framework for fog computing networks

Fog computing networks have been widely integrated in IoT-based systems to improve the quality of services (QoS) such as low response service delay through efficient offloading algorithms. However, designing an solution is still facing many challenges including complicated heterogeneity fog devices and complex computation tasks. In addition, need for a scalable distributed algorithm with computational complexity can be unachievable by global optimization approaches centralized information management dense networks. these regards, this paper proposes framework (DISCO) splittable tasks using matching theory. Through extensive simulation analysis, proposed show potential advantages reducing average significantly compared some related works.