The Internet of Things has revolutionized the lifestyle in all aspects. Considering the huge number of connected objects and the plethora of real-time services, edge computing approaches have emerged. Resource allocation is one of the most important challenges in the Internet of Things. Here edge computing allows the use of resources at the edge network, hence, filling the gap between cloud and end-devices. The network resource allocation should meet users' expectations and provide optimal use of resources. Today, most of the systems are moving toward a self-x concept, such as self-organizing. As a result, these systems must be aware of users' preferences and the current state of the IoT ecosystem in order to adapt themselves to the conditions. In this context, we benefit from the employment of semantic technologies as these enhance the current systems with information modeling and reasoning capabilities which effectively support the allocation of IoT network resources.