Internet of Things (IoT) is emerging as part ofthe infrastructures for advancing a large variety of applicationsinvolving connection of many intelligent devices, leadingto smart communities. Due to the severe limitation on thecomputing resources of IoT devices, it is common to offloadtasks of various applications requiring substantial computingresources to computing systems with sufficient computingresources, such as servers, cloud systems, and/or data centersfor processing. However, the offloading method suffers fromthe difficulties of high latency and network congestion in theIoT infrastructures. Recently edge computing has emergedto reduce the negative impacts of these difficulties. Yet, edgecomputing has its drawbacks, such as the limited computingresources of some edge computing devices and the unbalancedload among these devices. In order to effectively explorethe potential of edge computing to support IoT applications,it is necessary to have efficient task management in edgecomputing networks. In this paper, an approach is presented toperiodically distributing incoming tasks in the edge computingnetwork so that the number of tasks, which can be processedin the edge computing network, is increased, and the qualityof-service (QoS) requirements of the tasks completed in theedge computing network are satisfied. Simulation results arepresented to show the improvement of using this approach onthe increase of the number of tasks to be completed in the edgecomputing network.