Internet-of-Things (IoT) is a networking architecture where promising, intelligent services are designed via leveraging information from multiple heterogeneous sources of data within the network. However, the availability of such information in a timely manner requires processing and communication of raw data collected from these sources. Therefore, the economic feasibility of IoT-enabled networks relies on the efficient allocation of both computational and communication resources within the network. Since fog computing and 5G cellular networks approach this problem independently, there is a need for joint resource-provisioning of both communication and computational resources in the networks. As the solution to this problem, we propose a novel three-dimensional matching based resource provisioning algorithm that minimizes average service latency in the presence of various resource constraints, task deadlines and non-identical preferences at IoT devices, fog access points (FAPs) and small-cell access points (SAPs) in 5G networks. We prove the stability and termination of the proposed algorithm and also demonstrate that our proposed algorithm outperforms other state-of-the-art algorithms through both, simulation and real-world experiments on the laboratory test-bed.