Katinka Wolter Livres

As modern society relies on the fault-free operation of complex computing systems, system fault-tolerance has become an indispensable requirement. Therefore, we need mechanisms that guarantee correct service in cases where system components fail, be they software or hardware elements. Redundancy patterns are commonly used, for either redundancy in space or redundancy in time. Wolter’s book details methods of redundancy in time that need to be issued at the right moment. In particular, she addresses the so-called „timeout selection problem“, i. e., the question of choosing the right time for different fault-tolerance mechanisms like restart, rejuvenation and checkpointing. Restart indicates the pure system restart, rejuvenation denotes the restart of the operating environment of a task, and checkpointing includes saving the system state periodically and reinitializing the system at the most recent checkpoint upon failure of the system. Her presentation includes a brief introduction to the methods, their detailed stochastic description, and also aspects of their efficient implementation in real-world systems. The book is targeted at researchers and graduate students in system dependability, stochastic modeling and software reliability. Readers will find here an up-to-date overview of the key theoretical results, making this the only comprehensive text on stochastic models for restart-related problems.

The resilience of computing systems encompasses dependability, fault tolerance, and security, defining their ability to function effectively amidst disturbances and recover from service degradation. These attributes are crucial in a world reliant on the reliable and secure operation of large-scale distributed systems. The editors have organized 20 chapters from leading researchers into seven parts: an introduction, modeling techniques, model-driven prediction, measurement and metrics, testing techniques, case studies, and conclusions. Central to the volume are 12 technical papers framed by real-world examples and case studies that illustrate the necessity of the presented methods. While the technical chapters can be read independently, readers will gain more from the case studies if they are paired with the related techniques. Topics covered include modeling, benchmarking, testing, performance evaluation, and dependability, targeting academic and industrial researchers, as well as graduate students and lecturers in related fields. This volume offers a comprehensive overview of the state of the art in a field of growing practical importance.

This comprehensive work delves into various optimization problems in service provisioning systems, exploring Markov chains and their implications on steady-state probabilities, particularly regarding reward-based measures and equilibrium distributions. It discusses compositionality for Markov reward chains with rapid transitions and presents closed-form absorption time bounds alongside a canonical representation of order 3 phase-type distributions. The text also covers process algebras and state machines, introducing SPAMR, an extension of PAMR with stochastic time, and highlights advancements in SPDL model checking through property-driven state space generation. Additionally, it evaluates finite state machines with stochastic time and timeouts, investigates peer-to-peer (P2P) systems, and assesses P2P search algorithms for trust path discovery. The work emphasizes building online performance models for grid middleware, particularly through a case study on the Globus Toolkit, and proposes a performance measuring framework for grid market middleware. It further explores queueing theory applications, including a fixed-point algorithm for closed queueing networks and automated architectural feedback generation from software performance analysis. The text also examines optimal dynamic server allocation in systems with on/off sources, workload characterization of benchmarks, and resource sharing in performance models. Lastly, it