@inproceedings{209,
abstract = {{We study a new class of games which generalizes congestion games and its bottleneck variant. We introduce congestion games with mixed objectives to model network scenarios in which players seek to optimize for latency and bandwidths alike. We characterize the existence of pure Nash equilibria (PNE) and the convergence of improvement dynamics. For games that do not possess PNE we give bounds on the approximation ratio of approximate pure Nash equilibria.}},
author = {{Feldotto, Matthias and Leder, Lennart and Skopalik, Alexander}},
booktitle = {{Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA)}},
pages = {{655----669}},
title = {{{Congestion Games with Mixed Objectives}}},
doi = {{10.1007/978-3-319-48749-6_47}},
year = {{2016}},
}
@misc{5406,
author = {{Bülling, Jonas}},
title = {{{Parallelisierung von Algorithmen zur IR-Luftbildanalyse von Laubholzmischbeständen zur Verifizierung der Ausbreitung von Eichenkomplexschäden}}},
year = {{2016}},
}
@misc{5407,
author = {{Koepe, Jörn}},
publisher = {{Universität Paderborn}},
title = {{{Price-Based Allocation Games}}},
year = {{2016}},
}
@misc{688,
author = {{Kutzias, Damian}},
publisher = {{Universität Paderborn}},
title = {{{Friendship Processes in Network Creation Games}}},
year = {{2016}},
}
@misc{689,
author = {{Schaefer, Johannes Sebastian}},
publisher = {{Universität Paderborn}},
title = {{{Routing Algorithms on Delayed Networks for Disaster Management Support}}},
year = {{2016}},
}
@unpublished{16450,
abstract = {{In this paper, we solve the local gathering problem of a swarm of $n$
indistinguishable, point-shaped robots on a two dimensional grid in
asymptotically optimal time $\mathcal{O}(n)$ in the fully synchronous
$\mathcal{FSYNC}$ time model. Given an arbitrarily distributed (yet connected)
swarm of robots, the gathering problem on the grid is to locate all robots
within a $2\times 2$-sized area that is not known beforehand. Two robots are
connected if they are vertical or horizontal neighbors on the grid. The
locality constraint means that no global control, no compass, no global
communication and only local vision is available; hence, a robot can only see
its grid neighbors up to a constant $L_1$-distance, which also limits its
movements. A robot can move to one of its eight neighboring grid cells and if
two or more robots move to the same location they are \emph{merged} to be only
one robot. The locality constraint is the significant challenging issue here,
since robot movements must not harm the (only globally checkable) swarm
connectivity. For solving the gathering problem, we provide a synchronous
algorithm -- executed by every robot -- which ensures that robots merge without
breaking the swarm connectivity. In our model, robots can obtain a special
state, which marks such a robot to be performing specific connectivity
preserving movements in order to allow later merge operations of the swarm.
Compared to the grid, for gathering in the Euclidean plane for the same robot
and time model the best known upper bound is $\mathcal{O}(n^2)$.}},
author = {{Cord-Landwehr, Andreas and Fischer, Matthias and Jung, Daniel and Meyer auf der Heide, Friedhelm}},
booktitle = {{arXiv:1602.03303}},
title = {{{Asymptotically Optimal Gathering on a Grid}}},
year = {{2016}},
}
@inproceedings{169,
abstract = {{We apply methods of genetic programming to a general problem from software engineering, namely example-based generation of specifications. In particular, we focus on model transformation by example. The definition and implementation of model transformations is a task frequently carried out by domain experts, hence, a (semi-)automatic approach is desirable. This application is challenging because the underlying search space has rich semantics, is high-dimensional, and unstructured. Hence, a computationally brute-force approach would be unscalable and potentially infeasible. To address that problem, we develop a sophisticated approach of designing complex mutation operators. We define ‘patterns’ for constructing mutation operators and report a successful case study. Furthermore, the code of the evolved model transformation is required to have high maintainability and extensibility, that is, the code should be easily readable by domain experts. We report an evaluation of this approach in a software engineering case study.}},
author = {{Kühne, Thomas and Hamann, Heiko and Arifulina, Svetlana and Engels, Gregor}},
booktitle = {{Proceedings of the 19th European Conference on Genetic Programming (EuroGP 2016)}},
pages = {{278----293}},
title = {{{Patterns for Constructing Mutation Operators: Limiting the Search Space in a Software Engineering Application}}},
doi = {{10.1007/978-3-319-30668-1_18}},
year = {{2016}},
}
@misc{1082,
author = {{Handirk, Tobias}},
publisher = {{Universität Paderborn}},
title = {{{Über die Rolle von Informationen in Verkehrsnetzwerken}}},
year = {{2016}},
}
@phdthesis{154,
author = {{Cord-Landwehr, Andreas}},
isbn = {{978-3-942647-72-4}},
publisher = {{Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn}},
title = {{{Selfish Network Creation - On Variants of Network Creation Games}}},
volume = {{353}},
year = {{2016}},
}
@inproceedings{157,
abstract = {{Consider a scheduling problem in which a set of jobs with interjob communication, canonically represented by a weighted tree, needs to be scheduled on m parallel processors interconnected by a shared communication channel. In each time step, we may allow any processed job to use a certain capacity of the channel in order to satisfy (parts of) its communication demands to adjacent jobs processed in parallel. The goal is to find a schedule that minimizes the makespan and in which communication demands of all jobs are satisfied.We show that this problem is NP-hard in the strong sense even if the number of processors and the maximum degree of the underlying tree is constant.Consequently, we design and analyze simple approximation algorithms with asymptotic approximation ratio 2-2/m in case of paths and a ratio of 5/2 in case of arbitrary trees.}},
author = {{König, Jürgen and Mäcker, Alexander and Meyer auf der Heide, Friedhelm and Riechers, Sören}},
booktitle = {{Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA)}},
pages = {{563----577}},
title = {{{Scheduling with Interjob Communication on Parallel Processors}}},
doi = {{10.1007/978-3-319-48749-6_41}},
year = {{2016}},
}
@article{159,
abstract = {{Abstract—Max-min fairness (MMF) is a widely known approachto a fair allocation of bandwidth to each of the usersin a network. This allocation can be computed by uniformlyraising the bandwidths of all users without violating capacityconstraints. We consider an extension of these allocations byraising the bandwidth with arbitrary and not necessarily uniformtime-depending velocities (allocation rates). These allocationsare used in a game-theoretic context for routing choices, whichwe formalize in progressive filling games (PFGs). We present avariety of results for equilibria in PFGs. We show that these gamespossess pure Nash and strong equilibria. While computation ingeneral is NP-hard, there are polynomial-time algorithms forprominent classes of Max-Min-Fair Games (MMFG), includingthe case when all users have the same source-destination pair.We characterize prices of anarchy and stability for pure Nashand strong equilibria in PFGs and MMFGs when players havedifferent or the same source-destination pairs. In addition, weshow that when a designer can adjust allocation rates, it is possibleto design games with optimal strong equilibria. Some initial resultson polynomial-time algorithms in this direction are also derived.}},
author = {{Harks, Tobias and Höfer, Martin and Schewior, Kevin and Skopalik, Alexander}},
journal = {{IEEE/ACM Transactions on Networking}},
number = {{4}},
pages = {{2553 -- 2562}},
publisher = {{IEEE}},
title = {{{Routing Games With Progressive Filling}}},
doi = {{10.1109/TNET.2015.2468571}},
year = {{2016}},
}
@inproceedings{149,
abstract = {{In this paper we consider a strategic variant of the online facility location problem. Given is a graph in which each node serves two roles: it is a strategic client stating requests as well as a potential location for a facility. In each time step one client states a request which induces private costs equal to the distance to the closest facility. Before serving, the clients may collectively decide to open new facilities, sharing the corresponding price. Instead of optimizing the global costs, each client acts selfishly. The prices of new facilities vary between nodes and also change over time, but are always bounded by some fixed value α. Both the requests as well as the facility prices are given by an online sequence and are not known in advance.We characterize the optimal strategies of the clients and analyze their overall performance in comparison to a centralized offline solution. If all players optimize their own competitiveness, the global performance of the system is O(√α⋅α) times worse than the offline optimum. A restriction to a natural subclass of strategies improves this result to O(α). We also show that for fixed facility costs, we can find strategies such that this bound further improves to O(√α).}},
author = {{Drees, Maximilian and Feldkord, Björn and Skopalik, Alexander}},
booktitle = {{Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA)}},
pages = {{593----607}},
title = {{{Strategic Online Facility Location}}},
doi = {{10.1007/978-3-319-48749-6_43}},
year = {{2016}},
}
@proceedings{163,
editor = {{Dressler, Falko and Meyer auf der Heide, Friedhelm}},
location = {{Paderborn, Germany}},
publisher = {{ACM}},
title = {{{Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc)}}},
doi = {{10.1145/2942358}},
year = {{2016}},
}
@inproceedings{16351,
abstract = {{Defining, measuring, and comparing the quality and efficiency of rendering algorithms in computer graphics is a demanding challenge: quality measures are often application specific and efficiency is strongly influenced by properties of the rendered scene and the used hardware. We survey the currently employed evaluation methods for AQ1 the development process of rendering algorithms. Then, we present our PADrend framework, which supports systematic and flexible development, evaluation, adaptation, and comparison of rendering algorithms, and provides a comfortable and easy-to-use platform for developers of rendering algorithms. The system includes a new evaluation method to improve the objectivity of experimental evaluations of rendering algorithms.
}},
author = {{Fischer, Matthias and Jähn, Claudius and Meyer auf der Heide, Friedhelm and Petring, Ralf}},
booktitle = {{Algorithm Engineering}},
editor = {{Kliemann, Lasse and Sanders, Peter}},
pages = {{226--244}},
publisher = {{Springer}},
title = {{{Algorithm Engineering Aspects of Real-Time Rendering Algorithms}}},
doi = {{10.1007/978-3-319-49487-6_7 }},
volume = {{9220}},
year = {{2016}},
}
@inproceedings{16358,
author = {{Li, Shouwei and Meyer auf der Heide, Friedhelm and Podlipyan, Pavel}},
booktitle = {{Algorithms for Sensor Systems, Proceedings of the 12th International Symposium on Algorithms and Experiments for Wireless Sensor Networks (ALGOSENSORS)}},
publisher = {{Springer}},
title = {{{The impact of the Gabriel subgraph of the visibility graph on the gathering of mobile autonomous robots}}},
doi = {{10.1007/978-3-319-53058-1_5 }},
year = {{2016}},
}
@inproceedings{16359,
abstract = {{In this paper, we solve the local gathering problem of a swarm of n indistinguishable, point-shaped robots on a two dimensional grid in asymptotically optimal time O(n) in the fully synchronous FSYNC time model. Given an arbitrarily distributed (yet connected) swarm of robots, the gathering problem on the grid is to locate all robots within a 2x2- sized area that is not known beforehand. Two robots are connected if they are vertical or horizontal neighbors on the grid. The locality constraint means that no global control, no compass, no global communication and only local vision is available; hence, a robot can only see its grid neighbors up to a constant L1-distance, which also limits its movements. A robot can move to one of its eight neighboring grid cells and if two or more robots move to the same location they are merged to be only one robot. The locality constraint is the significant challenging issue here, since robot move- ments must not harm the (only globally checkable) swarm connectivity. For solving the gathering problem, we provide a synchronous algorithm { executed by every robot { which ensures that robots merge without breaking the swarm con- nectivity. In our model, robots can obtain a special state, which marks such a robot to be performing specific connec- tivity preserving movements in order to allow later merge operations of the swarm. Compared to the grid, for gath- ering in the Euclidean plane for the same robot and time model the best known upper bound is O(n^2).}},
author = {{Cord-Landwehr, Andreas and Fischer, Matthias and Jung, Daniel and Meyer auf der Heide, Friedhelm}},
booktitle = {{Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA)}},
pages = {{301--312}},
publisher = {{ACM}},
title = {{{Asymptotically Optimal Gathering on a Grid}}},
doi = {{10.1145/2935764.2935789}},
year = {{2016}},
}
@inproceedings{16360,
abstract = {{We consider the following variant of the two dimensional gathering problem for swarms of robots: Given a swarm of n indistinguishable, point shaped robots on a two dimensional grid. Initially, the robots form a closed chain on the grid and must keep this connectivity during the whole process of their gathering. Connectivity means, that neighboring robots of the chain need to be positioned at the same or neighboring points of the grid. In our model, gathering means to keep shortening the chain until the robots are located inside a 2*2 subgrid. Our model is completely local (no global control, no global coordinates, no compass, no global communication or vision, ...). Each robot can only see its next constant number of left and right neighbors on the chain. This fixed constant is called the viewing path length. All its operations and detections are restricted to this constant number of robots. Other robots, even if located at neighboring or the same grid point cannot be detected. Only based on the relative positions of its detectable chain neighbors, a robot can decide to obtain a certain state. Based on this state and their local knowledge, the robots do local modifications to the chain by moving to neighboring grid points without breaking the chain. These modifications are performed without the knowledge whether they lead to a global progress or not. We assume the fully synchronous FSYNC model. For this problem, we present a gathering algorithm which needs linear time. This result generalizes a result, where an open chain with specified distinguishable (and fixed) endpoints is considered. }},
author = {{Abshoff, Sebastian and Cord-Landwehr, Andreas and Fischer, Matthias and Jung, Daniel and Meyer auf der Heide, Friedhelm}},
booktitle = {{Proceedings of the 30th International Parallel and Distributed Processing Symposium (IPDPS)}},
pages = {{689--699}},
publisher = {{IEEE}},
title = {{{Gathering a Closed Chain of Robots on a Grid}}},
doi = {{10.1109/IPDPS.2016.51}},
year = {{2016}},
}
@inproceedings{16364,
author = {{Macker, Alexander and Malatyali, Manuel and Meyer auf der Heide, Friedhelm}},
booktitle = {{2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS)}},
isbn = {{9781509021406}},
title = {{{On Competitive Algorithms for Approximations of Top-k-Position Monitoring of Distributed Streams}}},
doi = {{10.1109/ipdps.2016.91}},
year = {{2016}},
}
@unpublished{16396,
abstract = {{We consider a scheduling problem where machines need to be rented from the
cloud in order to process jobs. There are two types of machines available which
can be rented for machine-type dependent prices and for arbitrary durations.
However, a machine-type dependent setup time is required before a machine is
available for processing. Jobs arrive online over time, have machine-type
dependent sizes and have individual deadlines. The objective is to rent
machines and schedule jobs so as to meet all deadlines while minimizing the
rental cost.
Since we observe the slack of jobs to have a fundamental influence on the
competitiveness, we study the model when instances are parameterized by their
(minimum) slack. An instance is called to have a slack of $\beta$ if, for all
jobs, the difference between the job's release time and the latest point in
time at which it needs to be started is at least $\beta$. While for $\beta < s$
no finite competitiveness is possible, our main result is an
$O(\frac{c}{\varepsilon} + \frac{1}{\varepsilon^3})$-competitive online
algorithm for $\beta = (1+\varepsilon)s$ with $\frac{1}{s} \leq \varepsilon
\leq 1$, where $s$ and $c$ denotes the largest setup time and the cost ratio of
the machine-types, respectively. It is complemented by a lower bound of
$\Omega(\frac{c}{\varepsilon})$.}},
author = {{Mäcker, Alexander and Malatyali, Manuel and Meyer auf der Heide, Friedhelm and Riechers, Sören}},
booktitle = {{arXiv:1609.01184}},
title = {{{Cost-efficient Scheduling on Machines from the Cloud}}},
year = {{2016}},
}
@article{139,
abstract = {{We consider online optimization problems in which certain goods have to be acquired in order to provide a service or infrastructure. Classically, decisions for such problems are considered as final: one buys the goods. However, in many real world applications, there is a shift away from the idea of buying goods. Instead, leasing is often a more flexible and lucrative business model. Research has realized this shift and recently initiated the theoretical study of leasing models (Anthony and Gupta in Proceedings of the integer programming and combinatorial optimization: 12th International IPCO Conference, Ithaca, NY, USA, June 25–27, 2007; Meyerson in Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2005), 23–25 Oct 2005, Pittsburgh, PA, USA, 2005; Nagarajan and Williamson in Discret Optim 10(4):361–370, 2013) We extend this line of work and suggest a more systematic study of leasing aspects for a class of online optimization problems. We provide two major technical results. We introduce the leasing variant of online set multicover and give an O(log(mK)logn)-competitive algorithm (with n, m, and K being the number of elements, sets, and leases, respectively). Our results also imply improvements for the non-leasing variant of online set cover. Moreover, we extend results for the leasing variant of online facility location. Nagarajan and Williamson (Discret Optim 10(4):361–370, 2013) gave an O(Klogn)-competitive algorithm for this problem (with n and K being the number of clients and leases, respectively). We remove the dependency on n (and, thereby, on time). In general, this leads to a bound of O(lmaxloglmax) (with the maximal lease length lmax). For many natural problem instances, the bound improves to O(K2).}},
author = {{Abshoff, Sebastian and Kling, Peter and Markarian, Christine and Meyer auf der Heide, Friedhelm and Pietrzyk, Peter }},
journal = {{Journal of Combinatorial Optimization}},
number = {{4}},
pages = {{ 1197----1216}},
publisher = {{Springer}},
title = {{{Towards the price of leasing online}}},
doi = {{10.1007/s10878-015-9915-5}},
year = {{2016}},
}