Double-Matching Resource Allocation Strategy in Fog Computing Networks Based on Cost Efficiency

Fog computing is an advanced technique to decrease latency and network congestion, and provide economical gains for Internet of Things (IoT) networks. In this paper, we investigate the computing resource allocation problem in three-layer fog computing networks. We first formulated the resource allocation problem as a double two-sided matching optimization problem. Then, we propose a double-matching strategy for the resource allocation problem in fog computing networks based on cost efficiency, which is derived by analysing the utility and cost in fog computing networks. The proposed double-matching strategy is an extension of the deferred acceptance algorithm from two-side matching to three-side matching. Numerical results show that high cost efficiency performance can be achieved by adopting the proposed strategy. Furthermore, by using the proposed strategy, the three participants in the fog computing networks could achieve stable results that each participant cannot change its paired partner unilaterally for more cost efficiency.