Software has never been as important as today – and its impact on life, work and society is growing at an impressive rate. We are in the flow of a software-induced transformation of nearly all aspects of our way of life and work. The dependence on software has become almost total. Malfunctions and unavailability may threaten vital areas of our society, life and work at any time.
The two massive challenges of software are one hand the complexity of the software and on the other hand the disruptive environment.
Complexity of the software is a result of the size, the continuously growing functionality, the more complicated technology and the growing networking. The unfortunate consequence is that complexity leads to many problems in design, development, evolution and operation of software-systems, especially of large software-systems.
All software-systems live in an environment. Many of today’s environments can be disruptive and cause severe problems for the systems and their users. Examples of disruptions are attacks, failures of partner systems or networks, faults in communications or malicious activities.
Traditionally, both growing complexity and disruptions from the environment have been tackled by better and better software engineering. The development and operating processes are constantly being improved and more powerful engineering tools are introduced. For defending against disruptions, predictive methods – such as risk analysis or fault trees – are used. All this techniques are based on the ingenuity, experience and skills of the engineers!
However, the growing complexity and the increasing intensity of possible disruptions from the environment make it more and more questionable, if people are really able to successfully cope with this raising challenge in the future. Already, serious research suggests that this is not the case anymore and that we need assistance from the software-systems themselves!
Here enters “autonomic computing” – A promising branch of software science which enables software-systems with self-configuring, self-healing, self-optimization and self-protection capabilities. Autonomic computing systems are able to re-organize, optimize, defend and adapt themselves with no real-time human intervention. Autonomic computing relies on many branches of science – especially computer science, artificial intelligence, control theory, machine learning, multi-agent systems and more.
Autonomic computing is an active research field which currently transfers many of its results into software engineering and many applications. This Hauptseminar offered the opportunity to learn about the fascinating technology “autonomic computing” and to do some personal research guided by a professor and assisted by the seminar peers.:Introduction 5
1 What Knowledge Does a Taxi Need? – Overview of Rule Based, Model Based and
Reinforcement Learning Systems for Autonomic Computing (Anja Reusch) 11
2 Chancen und Risiken von Virtual Assistent Systemen (Felix Hanspach) 23
3 Evolution einer Microservice Architektur zu Autonomic Computing (Ilja Bauer) 37
4 Mögliche Einflüsse von autonomen Informationsdiensten auf ihre Nutzer (Jan Engelmohr) 49
5 The Benefits of Resolving the Trust Issues between Autonomic Computing Systems
and their Users (Marc Kandler) 61
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:29925 |
| Date | 09 January 2017 |
| Creators | Furrer, Frank J., Püschel, Georg |
| Publisher | Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:workingPaper, info:eu-repo/semantics/workingPaper, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | urn:nbn:de:bsz:14-qucosa-79344, qucosa:24841 |
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