Schahram Dustdar – författare

This book constitutes the refereed proceedings of the 32nd International Conference on Advanced Information Systems Engineering, CAiSE 2020, held in Grenoble, France, in June 2020.*

The 33 full papers presented in this volume were carefully reviewed and selected from 185 submissions. The book also contains one invited talk in full paper length.

The papers were organized in topical sections named: distributed applications; AI and big data in IS; process mining and analysis; requirements and modeling; and information systems engineering.

Abstracts on the CAiSE 2020 tutorials can be found in the back matter of the volume.

*The conference was held virtually due to the COVID-19 pandemic.

The 9 full and 2 short papers were carefully reviewed and selected from 23 submissions. The papers mainly focus on IoT and cyber-physical systems, advanced application areas, cloud and edge, and service-based applications.

*The conference was held virtually due to the COVID-19 pandemic.

This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms.

The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks alongedge computing platforms. Chapter 5 introduces AI/ML pipelines to efficiently process generated data on the edge. Chapter 6 introduces ways to implement AI/ML systems on the edge and ways to deal with their training and inferencing procedures considering the limited resources available at the edge-nodes. Chapter 7 motivates the creation of a new orchestrator independent object model to descriptive objects (nodes, applications, etc.) and requirements (SLAs) for underlying edge platforms.

To provide hands-on experience to students and step-by-step improve their technical capabilities, seven sets of Tutorials-and-Labs (TaLs) are also designed. Codes and Instructions for each TaL is provided on the book website, and accompanied by videos to facilitate their learning process.

This book constitutes the refereed proceedings of the 18th Symposium and Summer School on Service-Oriented Computing, SummerSOC 2024, held in Crete, Greece, during June 24–29, 2024.

The 8 revised full papers and 1 short paper presented in these proceedings were carefully reviewed and selected from 24 submissions. They cover the following topics: modeling the digital world; quantum computing; data platforms.