7 research outputs found
To Adapt or Not to Adapt: A Quantification Technique for Measuring an Expected Degree of Self-Adaptation
Self-adaptation and self-organization (SASO) have been introduced to the management
of technical systems as an attempt to improve robustness and administrability. In particular, both
mechanisms adapt the system’s structure and behavior in response to dynamics of the environment
and internal or external disturbances. By now, adaptivity has been considered to be fully desirable.
This position paper argues that too much adaptation conflicts with goals such as stability and user
acceptance. Consequently, a kind of situation-dependent degree of adaptation is desired, which
defines the amount and severity of tolerated adaptations in certain situations. As a first step into this
direction, this position paper presents a quantification approach for measuring the current adaptation
behavior based on generative, probabilistic models. The behavior of this method is analyzed in
terms of three application scenarios: urban traffic control, the swidden farming model, and data
communication protocols. Furthermore, we define a research roadmap in terms of six challenges for
an overall measurement framework for SASO systems
Modelling and Design of Resilient Networks under Challenges
Communication networks, in particular the Internet, face a variety of challenges that can disrupt our daily lives resulting in the loss of human lives and significant financial costs in the worst cases. We define challenges as external events that trigger faults that eventually result in service failures. Understanding these challenges accordingly is essential for improvement of the current networks and for designing Future Internet architectures. This dissertation presents a taxonomy of challenges that can help evaluate design choices for the current and Future Internet. Graph models to analyse critical infrastructures are examined and a multilevel graph model is developed to study interdependencies between different networks. Furthermore, graph-theoretic heuristic optimisation algorithms are developed. These heuristic algorithms add links to increase the resilience of networks in the least costly manner and they are computationally less expensive than an exhaustive search algorithm. The performance of networks under random failures, targeted attacks, and correlated area-based challenges are evaluated by the challenge simulation module that we developed. The GpENI Future Internet testbed is used to conduct experiments to evaluate the performance of the heuristic algorithms developed