A smart campus provides students who are geographically scattered with online tools to get access to learning resources and laboratories. Although these remote laboratories have the potential and capabilities to implement different learning experiments, most of them are configured in a static fashion, being able to serve only one experiment for a given period of time. This lack of adaptability and flexibility causes long waiting queues of students in certain overloaded remote laboratories, while others are underused. To overcome this limitation, a smart campus can incorporate new techniques and paradigms such as Network function virtualization (NFV) and Software-defined networking (SDN), which are rapidly modifying current cloud services and applications to provide autonomous and adaptive solutions. In this context, the main contribution of this paper is an SDN/NFV-based architecture with autonomic capabilities to adapt to the remote laboratories configuration according to the end-user demand. The proposed architecture will be able to optimize computing resources to ensure the users' quality of service in a smart campus with remote laboratories. A use case with a remote laboratory, based on the control of a servo motor, shows how our solution can dynamically change the lab service under specific circumstances. Finally, experiments using diverse configurations and service descriptions show the performance and suitability of the proposal.
- remote laboratories
- Smart campus