As an extension of the cloud, a fog computing environment facilitates the deployment of Internet of Things (IoT) applications by shifting the computing, storage and networking services closer to the IoT devices, thus satisfying the delay and response time requirements. This paper aims to improve the overall task execution efficiency of IoT applications by appropriately selecting customized real-time tasks for execution at the fog layer. Specifically, we propose a fuzzy logic based task scheduling algorithm to divide the tasks between the fog and cloud layers in a fog-cloud computing framework. The algorithm selects appropriate processing units to execute the submitted tasks in the fog layer with heterogeneous resources, by exploiting the task requirements (e.g., computation, storage, bandwidth) and their constraints (e.g., deadline, data size). Simulation experiments demonstrate the efficacy of the proposed algorithm and its superior performance as compared to other existing algorithms in terms of success ratio of the tasks, makespan, average turnaround time, and delay rate.