Mission scheduler for a rail guided vehicle system

A transport system with automatic guided vehicles AGVs, is a fully automatic system that provides logistics services in industrial environments such as warehouses and production plants. These systems have reached such a degree of maturity as to allow, in their daily use, the application of heuristic algorithms for the optimization of the various operations they perform. For instance, find the shortest paths between working stations and storage area, assign movements and strategic positions for idle vehicles, operate efficient and long-life battery management and more. A relevant interesting algorithm, presented and developed in this thesis, concerns the sorting of products in the shipping phase, which affects the scheduling tasks assigned to the autonomous vehicles. The scheduler has the aims of determining which operations have more strict constraints and more priority over others. Studies and practice have shown that the adoption of a valid scheduler implies considerable improvements in the system performance, consequently it is advisable to dedicate time and effort to the research for the right one. The following algorithms obtained a successful outcome and they have been implemented for the production of a modern automated warehouse located in the city of Cesena, Italy. The paper is divided into four chapters, with a further one dedicated to conclusions

Integrating Blockchain and Fog Computing Technologies for Efficient Privacy-preserving Systems

This PhD dissertation concludes a three-year long research journey on the integration of Fog Computing and Blockchain technologies. The main aim of such integration is to address the challenges of each of these technologies, by integrating it with the other. Blockchain technology (BC) is a distributed ledger technology in the form of a distributed transactional database, secured by cryptography, and governed by a consensus mechanism. It was initially proposed for decentralized cryptocurrency applications with practically proven high robustness. Fog Computing (FC) is a geographically distributed computing architecture, in which various heterogeneous devices at the edge of network are ubiquitously connected to collaboratively provide elastic computation services. FC provides enhanced services closer to end-users in terms of time, energy, and network load. The integration of FC with BC can result in more efficient services, in terms of latency and privacy, mostly required by Internet of Things systems

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse