Accepted Tutorials

In the following is the list of accepted tutorials to ICSOC 2022. The list is provided in no specific order.

Location-aware Cloud Service Brokering in Multi-cloud Environment

Organizers: 

  • Hui Ma. Victoria University of Wellington, Wellington, New Zealand
  • Sven Hartmann. Clausthal University of Technology, Clausthal-Zellerfeld, Germany
  • Gang Chen. Victoria University of Wellington, Wellington, New Zealand
  • Tao Shi. Qingdao Agricultural University, Qingdao, China

Information: 

  • More and more enterprises are increasingly gaining technical and economic benefits from the global cloud marketplace. A multi-cloud environment makes it possible to orchestrate the access and management of multiple cloud resources at the global scale. Cloud service brokers can be regarded as the intermediate to discover, integrate, aggregate, customize, and optimize cloud services, e.g. Infrastructure as a Service (IaaS), from different cloud providers. However, the existing cloud brokering schemes rarely consider the optimization techniques of deploying cloud services with respect to various criteria, such as cost and performance. In this tutorial, we present some of our works using AI based approaches to the multi-cloud service brokering problem, i.e. selecting and leasing virtual machines (VMs) for cloud users with minimal cost and network latency. Experimental studies using real-world datasets show that our approaches with problem-tailored solution representation, efficient performance measurement, and smart solution initialization strategies can significantly outperform many existing approaches proposed in the literature.

More info here.

Distributed Computing Continuum Systems and AI – Opportunities and Research Challenges

Organizers:

  • Victor Casamayor Pujol. Distributed Systems Group at TU Wien
  • Praveen Kumar Donta. Distributed Systems Group at TU Wien
  • Andrea Morichetta. Distributed Systems Group at TU Wien
  • Ilir Murturi. Distributed Systems Group at TU Wien
  • Schahram Dustdar. Distributed Systems Group at TU Wien

Information:

  • In this tutorial we will discuss the opportunities and open research challenges of distributed computing continuum systems (IoT, Edge, Fog, and Cloud) and the utilization of AI techniques for this field. We will discuss multiple methods and techniques and select a few to present in more detail.
  • Introduction & Basics (~30min):
    • What are Distributed Continuum Computing Systems (DCCS) + Motivation + System’s candidate representations and definitions.
    • What is Edge Intelligence and how it relates to DCCS + Motivation + AI interpretation (what is AI from our perspective and for the needs of DCCS) and learning opportunities (what can be learnt).
    • Transversal example – Ideally we could always follow the same.
    • Introduction and overview on candidate technologies/concepts (we need a logical order to present them).
  • General (or not AI specific) techniques/concepts for DCCS (~1h):
    • DeepSLO
    • FEP
    • Markov Blanket
    • Operational Equilibrium
    • Elastic Strategies
    • Semantic Communication
    • Self-Reference
  • Learning/AI techniques for DCCS (~1h):
    • Deep Reinforcement Learning
    • Global Workspace Theory
    • Graph Knowledge representation
    • Active inference
    • Distributed learning
    • Causal inference
    • Generative models
    • Frontiers of AI in DCCS
  • Conclusions (~30min):
    • Wrap-up of techniques/concepts, what are they relations (and maybe a taxonomy relating challenges of the DCCS/AI and the mapping to the techniques) – Get back to the example (in case it has not been follow for each technique/concept)
    • Research roadmap (what are our priorities and why)

More info here.

Testing of RESTful Web APIs

Organizers:

  • Juan Carlos Alonso Valenzuela. University of Seville, Spain
  • Alberto Martín López. Schaffhausen Institute of Technology (SIT) and
    the Università della Svizzera Italiana (USI)

Information:

  • Introduction. REST APIs, OpenAPI Specification, RESTful API testing.
  • Manual testing. Overview of popular tools in industry.
    • REST Assured. Popular JUnit library for system-level testing of REST APIs.
    • Postman. Reference platform for API lifecycle management (dev, test, deploy, etc.)
  • Automated testing. Overview of powerful research tools.
    • RESTler. Black-box fuzzing, developed by Microsoft.
    • EvoMaster. White-box testing with evolutionary algorithms.
    • RESTest. Black-box testing with varied customizable strategies.
      • Test data generators and test case generators.
      • Test oracle generation (with Juan Carlos Alonso).
  • Continuous online testing with RESTest.
    • Intro. The RESTest testing ecosystem.
    • Demo. Testing commercial APIs with bots.
    • Results. Hundreds of bugs in commercial APIs.
  • Conclusion. Recap, additional resources, research opportunities.

More info here.