Intelligent management for next generation communication systems - communication systems policies for delivering fresh information

Many Internet of Things (IoT) applications require information to be received and decision-making made in a timely manner. The Age-of-Information (AoI) metric has been proposed to measure and evaluate the freshness of information. Afterwards, a new metric was proposed, named Peak AoI (PA), which represents the worst-case AoI. PA is defined as the maximum time elapsed since the preceding piece of information was generated. The PA metric has a simpler formation and is a more utilisable metric. Consequently, it has gained attention in the literature with various approaches to model it and also to optimise network functions to minimise it. This thesis answers the following question ‘How can we deliver fresh information?’. To answer this question, several gaps in the current body of knowledge had to be filled. The first gap was ‘A method for evaluating the information freshness empirically using experiments’. Hence, an experimental model is proposed, and validated to evaluate the freshness of information. Using the empirical method, the second research gap, i.e., the limitation of the policies proposed in the literature, was examined and proved to be inefficient in some of the real-world scenarios. Thus, the next research gap had been formed, that is a policy to deliver fresh information in real-world applications, hence, the author proposed a policy to deliver fresh information and tested it in several real-world scenarios. Afterwards, it was noticed that to deliver fresh information it is necessary to decrease the throughput, hence, it a naval policy to deliver freshness information without compromising the throughput was proposed. The accuracy of queuing models used in the literature was also investigated