@inproceedings{19899,
abstract = {Most existing robot formation problems seek a target formation of a certain
minimal and, thus, efficient structure. Examples include the Gathering
and the Chain-Formation problem. In this work, we study formation problems that
try to reach a maximal structure, supporting for example an efficient
coverage in exploration scenarios. A recent example is the NASA Shapeshifter
project, which describes how the robots form a relay chain along which gathered
data from extraterrestrial cave explorations may be sent to a home base.
As a first step towards understanding such maximization tasks, we introduce
and study the Max-Chain-Formation problem, where $n$ robots are ordered along a
winding, potentially self-intersecting chain and must form a connected,
straight line of maximal length connecting its two endpoints. We propose and
analyze strategies in a discrete and in a continuous time model. In the
discrete case, we give a complete analysis if all robots are initially
collinear, showing that the worst-case time to reach an
$\varepsilon$-approximation is upper bounded by $\mathcal{O}(n^2 \cdot \log
(n/\varepsilon))$ and lower bounded by $\Omega(n^2 \cdot~\log
(1/\varepsilon))$. If one endpoint of the chain remains stationary, this result
can be extended to the non-collinear case. If both endpoints move, we identify
a family of instances whose runtime is unbounded. For the continuous model, we
give a strategy with an optimal runtime bound of $\Theta(n)$. Avoiding an
unbounded runtime similar to the discrete case relies crucially on a
counter-intuitive aspect of the strategy: slowing down the endpoints while all
other robots move at full speed. Surprisingly, we can show that a similar trick
does not work in the discrete model.},
author = {Castenow, Jannik and Kling, Peter and Knollmann, Till and Meyer auf der Heide, Friedhelm},
booktitle = {Stabilization, Safety, and Security of Distributed Systems - 22nd International Symposium, SSS 2020, Austin, Texas, USA, November 18-21, 2020, Proceedings},
editor = {Devismes , Stéphane and Mittal, Neeraj },
isbn = {978-3-030-64347-8},
pages = {65--80},
publisher = {Springer},
title = {{A Discrete and Continuous Study of the Max-Chain-Formation Problem – Slow Down to Speed Up}},
doi = {10.1007/978-3-030-64348-5_6},
volume = {12514},
year = {2020},
}
@inproceedings{12870,
author = {Feldkord, Björn and Knollmann, Till and Malatyali, Manuel and Meyer auf der Heide, Friedhelm},
booktitle = {Proceedings of the 17th Workshop on Approximation and Online Algorithms (WAOA)},
pages = {120 -- 137},
publisher = {Springer},
title = {{Managing Multiple Mobile Resources}},
doi = {10.1007/978-3-030-39479-0_9},
year = {2019},
}
@article{13873,
author = {Feldkord, Björn and Meyer auf der Heide, Friedhelm},
journal = {ACM Transactions on Parallel Computing (TOPC)},
number = {3},
title = {{The Mobile Server Problem}},
doi = {10.1145/3364204},
volume = {6},
year = {2019},
}
@unpublished{16341,
abstract = {We present a technique for rendering highly complex 3D scenes in real-time by
generating uniformly distributed points on the scene's visible surfaces. The
technique is applicable to a wide range of scene types, like scenes directly
based on complex and detailed CAD data consisting of billions of polygons (in
contrast to scenes handcrafted solely for visualization). This allows to
visualize such scenes smoothly even in VR on a HMD with good image quality,
while maintaining the necessary frame-rates. In contrast to other point based
rendering methods, we place points in an approximated blue noise distribution
only on visible surfaces and store them in a highly GPU efficient data
structure, allowing to progressively refine the number of rendered points to
maximize the image quality for a given target frame rate. Our evaluation shows
that scenes consisting of a high amount of polygons can be rendered with
interactive frame rates with good visual quality on standard hardware.},
author = {Brandt, Sascha and Jähn, Claudius and Fischer, Matthias and Meyer auf der Heide, Friedhelm},
booktitle = {arXiv:1904.08225},
title = {{Rendering of Complex Heterogenous Scenes using Progressive Blue Surfels}},
year = {2019},
}
@phdthesis{8080,
abstract = {This thesis investigates approximate pure Nash equilibria in different game-theoretic models. In such an outcome, no player can improve her objective by more than a given factor through a deviation to another strategy. In the first part, we investigate two variants of Congestion Games in which the existence of pure Nash equilibria is guaranteed through a potential function argument. However, the computation of such equilibria might be hard. We construct and analyze approximation algorithms that enable the computation of states with low approximation factors in polynomial time. To show their guarantees we use sub games among players, bound the potential function values of arbitrary states and exploit a connection between Shapley and proportional cost shares. Furthermore, we apply and analyze sampling techniques for the computation of approximate Shapley values in different settings. In the second part, we concentrate on the existence of approximate pure Nash equilibria in games in which no pure Nash equilibria exist in general. In the model of Coevolving Opinion Formation Games, we bound the approximation guarantees for natural states nearly independent of the specific definition of the players' neighborhoods by applying a concept of virtual costs. For the special case of only one influential neighbor, we even show lower approximation factors for a natural strategy. Then, we investigate a two-sided Facility Location Game among facilities and clients on a line with an objective function consisting of distance and load. We show tight bounds on the approximation factor for settings with three facilities and infinitely many clients. For the general scenario with an arbitrary number of facilities, we bound the approximation factor for two promising candidates, namely facilities that are uniformly distributed and which are paired.},
author = {Feldotto, Matthias},
title = {{Approximate Pure Nash Equilibria in Congestion, Opinion Formation and Facility Location Games}},
doi = {10.17619/UNIPB/1-588},
year = {2019},
}
@inproceedings{10281,
abstract = {Competing firms tend to select similar locations for their stores. This phenomenon, called the principle of minimum differentiation, was captured by Hotelling with a landmark model of spatial competition but is still the object of an ongoing scientific debate. Although consistently observed in practice, many more realistic variants of Hotelling's model fail to support minimum differentiation or do not have pure equilibria at all. In particular, it was recently proven for a generalized model which incorporates negative network externalities and which contains Hotelling's model and classical selfish load balancing as special cases, that the unique equilibria do not adhere to minimum differentiation. Furthermore, it was shown that for a significant parameter range pure equilibria do not exist. We derive a sharp contrast to these previous results by investigating Hotelling's model with negative network externalities from an entirely new angle: approximate pure subgame perfect equilibria. This approach allows us to prove analytically and via agent-based simulations that approximate equilibria having good approximation guarantees and that adhere to minimum differentiation exist for the full parameter range of the model. Moreover, we show that the obtained approximate equilibria have high social welfare.},
author = {Feldotto, Matthias and Lenzner, Pascal and Molitor, Louise and Skopalik, Alexander},
booktitle = {Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems},
location = {Montreal QC, Canada},
pages = {1949----1951},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
title = {{ From Hotelling to Load Balancing: Approximation and the Principle of Minimum Differentiation}},
year = {2019},
}
@article{13937,
author = {Meyer auf der Heide, Friedhelm},
journal = {Mathematische Semesterberichte},
number = {2},
pages = {259--260},
title = {{Paul Curzon, Peter W. McOwan: Computational Thinking; Die Welt des algorithmischen Denkens – in Spielen, Zaubertricks und Rätseln}},
doi = {10.1007/s00591-019-00249-0},
volume = {66},
year = {2019},
}
@phdthesis{18975,
author = {Malatyali, Manuel},
title = {{Big Data: Sublinear Algorithms for Distributed Data Streams}},
doi = {10.17619/UNIPB/1-766},
year = {2019},
}
@misc{10344,
author = {Pukrop, Simon},
publisher = {Universität Paderborn},
title = {{Scheduling Algorithms for Multi-Operation Jobs with Setups on a Single Machine}},
year = {2019},
}
@inproceedings{17667,
abstract = {Resolving distributed attacks benefits from collaboration between networks. We present three approaches for the same multi-domain defensive action that can be applied in such an alliance: 1) Counteract Everywhere, 2) Minimize Countermeasures, and 3) Minimize Propagation. First, we provide a formula to compute efficiency of a defense; then we use this formula to compute the efficiency of the approaches under various circumstances. Finally, we discuss how task execution order and timing influence defense efficiency. Our results show that the Minimize Propagation approach is the most efficient method when defending against the chosen attack.},
author = {Koning, Ralph and Polevoy, Gleb and Meijer, Lydia and de Laat, Cees and Grosso, Paola},
booktitle = {2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)},
issn = {null},
keyword = {computer network security, multinetwork environments, multidomain defensive action, task execution order, timing influence defense efficiency, distributed attacks, collaborative security defence approach, minimize propagation approach, minimize countermeasure approach, counteract everywhere approach, Conferences, Cloud computing, Computer crime, Edge computing, Security, Defense Approaches, Multi-Domain Defense, Collaborative Defense, Defense Algorithms, Computer Networks},
pages = {113--123},
title = {{Approaches for Collaborative Security Defences in Multi Network Environments}},
doi = {10.1109/CSCloud/EdgeCom.2019.000-9},
year = {2019},
}