State of the art and research challenges in the area of autonomous control for a reliable internet of services
The explosive growth of the Internet has fundamentally changed the global society. The emergence of concepts like service-oriented architecture (SOA), Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS), Network as a Service (NaaS) and Cloud Computing in general has catalyzed the migration from the information-oriented Internet into an Internet of Services (IoS). This has opened up virtually unbounded possibilities for the creation of new and innovative services that facilitate business processes and improve the quality of life. However, this also calls for new approaches to ensuring quality and reliability of these services. The goal of this book chapter is to first analyze the state-of-the-art in the area of autonomous control for a reliable IoS and then to identify the main research challenges within it. A general background and high-level description of the current state of knowledge is presented. Then, for each of the three subareas, namely the autonomous management and real-time control, methods and tools for monitoring and service prediction, and smart pricing and competition in multi-domain systems, a brief general introduction and background are presented, and a list of key research challenges is formulated.
|, , , , ,|
|Microsoft Research, Cambridge, UK|
|I. Ganchev (Ivan) , R.D. van der Mei (Rob) , J.L. van den Berg (Hans)|
|Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence|
|Organisation||Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands|
van der Mei, R.D, van den Berg, J.L, Ganchev, I, Tutschku, K, Leitner, P, Lassila, P, … Key, P. (2018). State of the art and research challenges in the area of autonomous control for a reliable internet of services. In I Ganchev, R.D van der Mei, & J.L van den Berg (Eds.), Autonomous Control for a Reliable Internet of Services. Methods, Models, Approaches, Techniques, Algorithms, and Tools (pp. 1–22). doi:10.1007/978-3-319-90415-3_1