@inbook{13939, author = {{Kling, Peter and Meyer auf der Heide, Friedhelm}}, booktitle = {{Distributed Computing by Mobile Entities, Current Research in Moving and Computing}}, pages = {{317--334}}, publisher = {{Springer}}, title = {{{Continuous Protocols for Swarm Robotics}}}, doi = {{10.1007/978-3-030-11072-7\_13}}, volume = {{11340}}, year = {{2019}}, } @inproceedings{13942, author = {{Markarian, Christine and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 8th International Conference on Operations Research and Enterprise Systems}}, pages = {{315--321}}, publisher = {{SciTePress}}, title = {{{Online Algorithms for Leasing Vertex Cover and Leasing Non-metric Facility Location}}}, doi = {{10.5220/0007369503150321}}, year = {{2019}}, } @article{13946, author = {{Abu-Khzam, Faisal N. and Li, Shouwei and Markarian, Christine and Meyer auf der Heide, Friedhelm and Podlipyan, Pavel}}, journal = {{Theoretical Computer Science}}, pages = {{2--12}}, title = {{{Efficient parallel algorithms for parameterized problems}}}, doi = {{10.1016/j.tcs.2018.11.006}}, volume = {{786}}, year = {{2019}}, } @inproceedings{14539, author = {{Castenow, Jannik and Kolb, Christina and Scheideler, Christian}}, booktitle = {{Proceedings of the 26th International Colloquium on Structural Information and Communication Complexity (SIROCCO)}}, location = {{L'Aquila, Italy}}, pages = {{345--348}}, title = {{{A Bounding Box Overlay for Competitive Routing in Hybrid Communication Networks}}}, doi = {{10.1007/978-3-030-24922-9\_26}}, 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}}, } @misc{10344, author = {{Pukrop, Simon}}, publisher = {{Universität Paderborn}}, title = {{{Scheduling Algorithms for Multi-Operation Jobs with Setups on a Single Machine}}}, year = {{2019}}, } @inproceedings{2484, abstract = {{We study the classic bin packing problem in a fully-dynamic setting, where new items can arrive and old items may depart. We want algorithms with low asymptotic competitive ratio while repacking items sparingly between updates. Formally, each item i has a movement cost c_i >= 0, and we want to use alpha * OPT bins and incur a movement cost gamma * c_i, either in the worst case, or in an amortized sense, for alpha, gamma as small as possible. We call gamma the recourse of the algorithm. This is motivated by cloud storage applications, where fully-dynamic bin packing models the problem of data backup to minimize the number of disks used, as well as communication incurred in moving file backups between disks. Since the set of files changes over time, we could recompute a solution periodically from scratch, but this would give a high number of disk rewrites, incurring a high energy cost and possible wear and tear of the disks. In this work, we present optimal tradeoffs between number of bins used and number of items repacked, as well as natural extensions of the latter measure.}}, author = {{Feldkord, Björn and Feldotto, Matthias and Gupta, Anupam and Guruganesh, Guru and Kumar, Amit and Riechers, Sören and Wajc, David}}, booktitle = {{45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)}}, editor = {{Chatzigiannakis, Ioannis and Kaklamanis, Christos and Marx, Dániel and Sannella, Donald}}, isbn = {{978-3-95977-076-7}}, issn = {{1868-8969}}, location = {{Prag}}, pages = {{51:1--51:24}}, publisher = {{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik}}, title = {{{Fully-Dynamic Bin Packing with Little Repacking}}}, doi = {{10.4230/LIPIcs.ICALP.2018.51}}, volume = {{107}}, year = {{2018}}, } @inproceedings{2485, author = {{Feldkord, Björn and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 30th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA)}}, location = {{Wien}}, pages = {{373 -- 381 }}, publisher = {{ACM}}, title = {{{Online Facility Location with Mobile Facilities}}}, doi = {{10.1145/3210377.3210389}}, year = {{2018}}, } @misc{25121, abstract = {{We consider a group of $n$ autonomous mobile robots of which $m$ are stationary thus cannot move. Robots are represented by points in the Euclidean plane. They have no memory, do not communicate or share a common coordinate system and they move solely based on the positioning of other robots within their limited viewing range of 1. The goal is to gather the robots inside of the convex hull of all stationary robots. A variant of this problem, the general gathering problem, has been studied in various different time models. In this work, we consider a continuous time model, where robots continuously observe their neighbors, compute the next target of movement and move with a speed limit of 1 at any time. Regarding the robots' local strategy, we only study contracting algorithms in which every robot that is positioned on the border of the convex hull of all robots moves into this hull. We present a time bound of $\mathcal{O}(nd)$ for any general contracting algorithms in a configuration with only a single stationary robot. For configurations with more stationary robots, we prove that robots converge against the convex hull of all stationary robots and that no upper bound on the runtime exists. For the specific contracting algorithms Go-To-The-Left, Go-On-Bisector and Go-To-The-Middle, we provide linear time bounds.}}, author = {{Liedtke, David Jan}}, title = {{{Influence of Stationary Robots on Continuous Robot Formation Problems}}}, year = {{2018}}, } @unpublished{19978, abstract = {{We introduce the \emph{Online Connected Dominating Set Leasing} problem (OCDSL) in which we are given an undirected connected graph $G = (V, E)$, a set $\mathcal{L}$ of lease types each characterized by a duration and cost, and a sequence of subsets of $V$ arriving over time. A node can be leased using lease type $l$ for cost $c_l$ and remains active for time $d_l$. The adversary gives in each step $t$ a subset of nodes that need to be dominated by a connected subgraph consisting of nodes active at time $t$. The goal is to minimize the total leasing costs. OCDSL contains the \emph{Parking Permit Problem}~\cite{PPP} as a special subcase and generalizes the classical offline \emph{Connected Dominating Set} problem~\cite{Guha1998}. It has an $\Omega(\log ^2 n + \log |\mathcal{L}|)$ randomized lower bound resulting from lower bounds for the \emph{Parking Permit Problem} and the \emph{Online Set Cover} problem~\cite{Alon:2003:OSC:780542.780558,Korman}, where $|\mathcal{L}|$ is the number of available lease types and $n$ is the number of nodes in the input graph. We give a randomized $\mathcal{O}(\log ^2 n + \log |\mathcal{L}| \log n)$-competitive algorithm for OCDSL. We also give a deterministic algorithm for a variant of OCDSL in which the dominating subgraph need not be connected, the \emph{Online Dominating Set Leasing} problem. The latter is based on a simple primal-dual approach and has an $\mathcal{O}(|\mathcal{L}| \cdot \Delta)$-competitive ratio, where $\Delta$ is the maximum degree of the input graph.}}, author = {{Markarian, Christine}}, booktitle = {{arXiv:1805.02994}}, title = {{{Online Connected Dominating Set Leasing}}}, year = {{2018}}, }