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Distributed Systems

Almost every computing system nowadays is distributed, ranging from multi-core laptops to Internet-scale services; understanding the principles of distributed computing is hence important for the design and engineering of modern computing systems.  Fundamental issues that arise in reliable and efficient distributed systems include developing adequate methods for modeling failures and synchrony assumptions, determining precise performance bounds on implementations of concurrent data structures, capturing the trade-off between consistency and efficiency, and demarcating the frontier of feasibility in distributed computing.

For example, popular Internet services and applications such as CNN.com, YouTube, Facebook, Skype, BitTorrent attract millions of users every day, and only by the effective load-balancing and collaboration of many thousand machines, an acceptable Quality-of-Service/Quality-of-Experience can be guaranteed. While distributed systems promise a good scalability as well as a high robustness, they pose challenging research problems, such as: How to design robust and scalable distributed architectures and services? How to coordinate access to a shared resource, e.g., by electing a leader? Or how to provide incentives for cooperation in an open, collaborative distributed system?

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Selected Publications

Online Function Tracking with Generalized Penalties
Zitatschlüssel BS-OFTWGP-10
Autor Bienkowski, Marcin and Schmid, Stefan
Buchtitel Proceedings of 12th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2010)
Seiten 359–370
Jahr 2010
ISBN 978-3-642-13730-3
ISSN 0302-9743
DOI http://dx.doi.org/10.1007/978-3-642-13731-0_34
Ort Bergen, Norway
Adresse Berlin / Heidelberg, Germany
Jahrgang 6139
Monat June
Verlag Springer
Serie Lecture Notes in Computer Science (LNCS)
Zusammenfassung We attend to the classic setting where an observer needs to inform a tracker about an arbitrary time varying function f:N_0–>Z. This is an optimization problem, where both wrong values at the tracker and sending updates entail a certain cost. We consider an online variant of this problem, i.e., at time t, the observer only knows f(t') for all t'=<t. In this paper, we generalize existing cost models (with an emphasis on concave and convex penalties) and present two online algorithms. Our analysis shows that these algorithms perform well in a large class of models, and are even optimal in some settings.
Link zur Publikation Download Bibtex Eintrag

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