This thesis investigates several aspects of Multi-Tiered Storage (MTS), Extended Petri Nets (EPNs), and novel rule-based scheduling for data transfers, all aimed at enhancing the efficiency of processing database applications in computing systems equipped with multi-tiered persistent storage devices. It presents specialised algorithms designed to generate optimal data transfer strategies.
Moreover, the work explores the essential role of MTS in effectively managing organisations’ extensive volume of data. It offers comprehensive insights into Petri Nets, detailing their components and operational principles. Additionally, the thesis introduces a novel data processing framework called the EPN, which extends the original Petri Nets. It introduces algorithms that leverage EPN to articulate data flows between storage tiers, facilitating the creation of optimal data transfer strategies
