## 3 Smart Campus/University Communications Architectures  
Several authors have previously proposed different smart campus architectures, but it can be stated that, in general, they can be classified as Service-Oriented Architecture (SOA)  
Figure 1: Main fields and technologies of a smart campus. architectures [32; 33] that revolve around two main paradigms (IoT and cloud computing [34]), which are usually helped by Big Data when processing and analyzing the collected information. An example of smart campus architecture based on cloud computing is presented in [35], where the authors deployed a smart campus platform in three months by using Commercial Off-The-Shelf (COTS) hardware and Microsoft Azure cloud services. With respect to IoT, its use has been proposed for easing the deployment of architectures that allow for implementing learning, access control, or resource water management applications [10; 36]. Some researchers have also proposed alternative paradigms for creating smart campuses. For instance, the authors of [37] propose an opportunistic communications architecture that allows for sharing data through infrastructure-less services. The main novelty behind the proposed architecture is the concept of Floating Content node, which is a computing device that produces data that can be shared among users located in nearby areas. Similar architectures have been proposed, but they have been focused on improving certain aspects like security [38]. Some of the latest smart campus architectures have suggested the use of the different types of the edge computing paradigm (e.g., mobile edge computing or fog computing), which have already been successfully applied to other smart fields [39]. The main advantage of edge computing is its ability to offload part of the processing tasks from the cloud, delegating such tasks to the so-called edge devices, which are physically located close to the IoT nodes. Thanks to this approach, the amount of communications transactions with the cloud and latency response are reduced, while also being able to provide location-aware services [40; 41]. For example, the authors of [42] make use of edge computing devices to improve their smart campus architecture. Such devices are focused on delivering services related to content caching and bandwidth allocation. A similar approach is presented in [43], where the researchers provide smart campus services through edge computing devices embedded into street lights. In the case of the work detailed in [44], the authors propose a smart campus platform called WiCloud that is based in mobile edge computing, which allows for accessing the platform servers through mobile phone base stations or wireless access points. Finally, it is worth mentioning the smart campus system presented in [45], which makes use of fog computing nodes to enhance user experience. To clarify the previously mentioned architectures, Figure 2 illustrates their evolution. In this figure, at the top, the traditional cloud-based architecture is depicted, which is composed by two main layers:  
* Node layer: it consists of multiple IoT nodes and computing devices, whose data are collected through IoT gateways and routers in order to send them to the cloud where they are stored. * Cloud layer: it is essentially a central server or a group of servers where the main processing tasks are carried out. In addition, the cloud allows for interacting with third parties, it presents the stored data to remote users and enables interconnecting the multiple IoT networks that may be scattered through different physical locations. The architecture depicted at the bottom of Figure 2 on the left represents a fog computing architecture. In this case, besides the node layer and the cloud, there is a third layer (the fog layer), which is made of fog devices. Such devices provide different local fog services to the IoT nodes and are also able to exchange data among them to collaborate in certain tasks.