Recursive SDN for Carrier Networks

Control planes for global carrier networks should be programmable (so that new functionality can be easily introduced) and scalable (so they can handle the numerical scale and geographic scope of these networks). Neither traditional control planes nor new SDN-based control planes meet both of these goals. In this paper, we propose a framework for recursive routing computations that combines the best of SDN (programmability) and traditional networks (scalability through hierarchy) to achieve these two desired properties. Through simulation on graphs of up to 10,000 nodes, we evaluate our design's ability to support a variety of routing and traffic engineering solutions, while incorporating a fast failure recovery mechanism

Open Source Software: From Open Science to New Marketing Models

-Open source Software; Intellectual Property; Licensing; Business Model.

Smart railroad maintenance engineering with stochastic model checking

RAMS (reliability, availability, maintenance and safety) requirements are of utmost important for safety-critical systems like railroad infrastructure and signaling systems. Fault tree analysis (FTA) is a widely applied industry standard for RAMS analysis and is often one of the techniques preferred by railways organizations. FTA yields system availability and reliability, and can be used for critical path analysis. It can however not yet deal with a pressing aspect of railroad engineering: maintenance. While railroad infrastructure providers are focusing more and more on managing cost/performance ratios, RAMS can be considered as the performance specification, and maintenance the main cost driver. Methods facilitating the management of this ratio are still very uncommon. This paper presents a powerful, flexible and transparent technique to incorporate maintenance aspects in fault tree analysis, based on stochastic model checking. The analysis and comparison of different maintenance strategies (such as age-based, clockbased and condition-dependent maintenance) and their impact on reliability and availability metrics are thus enabled. Thus, the trade off between cost and RAMS performance is facilitated. To keep the underlying state space small, two aggressive state space reduction techniques are employed namely: compositional aggregation and smart semantics. The approach presented is illustrated using several existing, large fault tree models in a case study from Movares, a major RAMS consultancy firm in the Netherlands

Compounding Effects of Climate Warming and Antibiotic Resistance.

Bacteria have evolved diverse mechanisms to survive environments with antibiotics. Temperature is both a key factor that affects the survival of bacteria in the presence of antibiotics and an environmental trait that is drastically increasing due to climate change. Therefore, it is timely and important to understand links between temperature changes and selection of antibiotic resistance. This review examines these links by synthesizing results from laboratories, hospitals, and environmental studies. First, we describe the transient physiological responses to temperature that alter cellular behavior and lead to antibiotic tolerance and persistence. Second, we focus on the link between thermal stress and the evolution and maintenance of antibiotic resistance mutations. Finally, we explore how local and global changes in temperature are associated with increases in antibiotic resistance and its spread. We suggest that a multidisciplinary, multiscale approach is critical to fully understand how temperature changes are contributing to the antibiotic crisis

Project scheduling under undertainty – survey and research potentials.

The vast majority of the research efforts in project scheduling assume complete information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule will be executed. However, in the real world, project activities are subject to considerable uncertainty, that is gradually resolved during project execution. In this survey we review the fundamental approaches for scheduling under uncertainty: reactive scheduling, stochastic project scheduling, stochastic GERT network scheduling, fuzzy project scheduling, robust (proactive) scheduling and sensitivity analysis. We discuss the potentials of these approaches for scheduling projects under uncertainty.Management; Project management; Robustness; Scheduling; Stability;

On cost-effective reuse of components in the design of complex reconfigurable systems

Design strategies that benefit from the reuse of system components can reduce costs while maintaining or increasing dependability—we use the term dependability to tie together reliability and availability. D3H2 (aDaptive Dependable Design for systems with Homogeneous and Heterogeneous redundancies) is a methodology that supports the design of complex systems with a focus on reconfiguration and component reuse. D3H2 systematizes the identification of heterogeneous redundancies and optimizes the design of fault detection and reconfiguration mechanisms, by enabling the analysis of design alternatives with respect to dependability and cost. In this paper, we extend D3H2 for application to repairable systems. The method is extended with analysis capabilities allowing dependability assessment of complex reconfigurable systems. Analysed scenarios include time-dependencies between failure events and the corresponding reconfiguration actions. We demonstrate how D3H2 can support decisions about fault detection and reconfiguration that seek to improve dependability while reducing costs via application to a realistic railway case study