@article{33947, author = {{Castenow, Jannik and Harbig, Jonas and Jung, Daniel and Knollmann, Till and Meyer auf der Heide, Friedhelm}}, issn = {{0304-3975}}, journal = {{Theoretical Computer Science}}, keywords = {{General Computer Science, Theoretical Computer Science}}, pages = {{261--291}}, publisher = {{Elsevier BV}}, title = {{{Gathering a Euclidean Closed Chain of Robots in Linear Time and Improved Algorithms for Chain-Formation}}}, doi = {{10.1016/j.tcs.2022.10.031}}, volume = {{939}}, year = {{2023}}, } @inproceedings{34008, author = {{Castenow, Jannik and Harbig, Jonas and Jung, Daniel and Kling, Peter and Knollmann, Till and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 26th International Conference on Principles of Distributed Systems (OPODIS) }}, editor = {{Hillel, Eshcar and Palmieri, Roberto and Riviére, Etienne}}, isbn = {{978-3-95977-265-5}}, issn = {{1868-8969}}, location = {{Brussels}}, pages = {{15:1–15:25}}, publisher = {{Schloss Dagstuhl – Leibniz Zentrum für Informatik}}, title = {{{A Unifying Approach to Efficient (Near-)Gathering of Disoriented Robots with Limited Visibility }}}, doi = {{10.4230/LIPIcs.OPODIS.2022.15}}, volume = {{253}}, year = {{2023}}, } @article{44077, author = {{Maack, Marten}}, issn = {{0167-6377}}, journal = {{Operations Research Letters}}, keywords = {{Applied Mathematics, Industrial and Manufacturing Engineering, Management Science and Operations Research, Software}}, number = {{3}}, pages = {{220--225}}, publisher = {{Elsevier BV}}, title = {{{Online load balancing on uniform machines with limited migration}}}, doi = {{10.1016/j.orl.2023.02.013}}, volume = {{51}}, year = {{2023}}, } @inbook{44769, author = {{Castenow, Jannik and Harbig, Jonas and Meyer auf der Heide, Friedhelm}}, booktitle = {{Lecture Notes in Computer Science}}, isbn = {{9783031304477}}, issn = {{0302-9743}}, publisher = {{Springer International Publishing}}, title = {{{Unifying Gathering Protocols for Swarms of Mobile Robots}}}, doi = {{10.1007/978-3-031-30448-4_1}}, year = {{2023}}, } @phdthesis{45580, author = {{Castenow, Jannik}}, title = {{{Local Protocols for Contracting and Expanding Robot Formation Problems}}}, doi = {{10.17619/UNIPB/1-1750}}, year = {{2023}}, } @phdthesis{45579, author = {{Knollmann, Till}}, title = {{{Online Algorithms for Allocating Heterogeneous Resources}}}, doi = {{10.17619/UNIPB/1-1751}}, year = {{2023}}, } @phdthesis{45781, author = {{Pukrop, Simon}}, title = {{{On Cloud Assisted, Restricted, and Reosurce Constrained Scheduling}}}, doi = {{10.17619/UNIPB/1-1768 }}, year = {{2023}}, } @article{50458, abstract = {{AbstractConsider a set of jobs connected to a directed acyclic task graph with a fixed source and sink. The edges of this graph model precedence constraints and the jobs have to be scheduled with respect to those. We introduce the server cloud scheduling problem, in which the jobs have to be processed either on a single local machine or on one of infinitely many cloud machines. For each job, processing times both on the server and in the cloud are given. Furthermore, for each edge in the task graph, a communication delay is included in the input and has to be taken into account if one of the two jobs is scheduled on the server and the other in the cloud. The server processes jobs sequentially, whereas the cloud can serve as many as needed in parallel, but induces costs. We consider both makespan and cost minimization. The main results are an FPTAS for the makespan objective for graphs with a constant source and sink dividing cut and strong hardness for the case with unit processing times and delays.}}, author = {{Maack, Marten and Meyer auf der Heide, Friedhelm and Pukrop, Simon}}, issn = {{0178-4617}}, journal = {{Algorithmica}}, keywords = {{Applied Mathematics, Computer Science Applications, General Computer Science}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Server Cloud Scheduling}}}, doi = {{10.1007/s00453-023-01189-x}}, year = {{2023}}, } @inproceedings{50460, author = {{Deppert, Max A. and Jansen, Klaus and Maack, Marten and Pukrop, Simon and Rau, Malin}}, booktitle = {{2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS)}}, publisher = {{IEEE}}, title = {{{Scheduling with Many Shared Resources}}}, doi = {{10.1109/ipdps54959.2023.00049}}, year = {{2023}}, } @article{29843, author = {{Castenow, Jannik and Kling, Peter and Knollmann, Till and Meyer auf der Heide, Friedhelm}}, issn = {{0890-5401}}, journal = {{Information and Computation}}, keywords = {{Computational Theory and Mathematics, Computer Science Applications, Information Systems, Theoretical Computer Science}}, publisher = {{Elsevier BV}}, title = {{{A Discrete and Continuous Study of the Max-Chain-Formation Problem}}}, doi = {{10.1016/j.ic.2022.104877}}, year = {{2022}}, } @inproceedings{31847, abstract = {{The famous $k$-Server Problem covers plenty of resource allocation scenarios, and several variations have been studied extensively for decades. However, to the best of our knowledge, no research has considered the problem if the servers are not identical and requests can express which specific servers should serve them. Therefore, we present a new model generalizing the $k$-Server Problem by *preferences* of the requests and proceed to study it in a uniform metric space for deterministic online algorithms (the special case of paging). In our model, requests can either demand to be answered by any server (*general requests*) or by a specific one (*specific requests*). If only general requests appear, the instance is one of the original $k$-Server Problem, and a lower bound for the competitive ratio of $k$ applies. If only specific requests appear, a solution with a competitive ratio of $1$ becomes trivial since there is no freedom regarding the servers' movements. Perhaps counter-intuitively, we show that if both kinds of requests appear, the lower bound raises to $2k-1$. We study deterministic online algorithms in uniform metrics and present two algorithms. The first one has an adaptive competitive ratio dependent on the frequency of specific requests. It achieves a worst-case competitive ratio of $3k-2$ while it is optimal when only general or only specific requests appear (competitive ratio of $k$ and $1$, respectively). The second has a fixed close-to-optimal worst-case competitive ratio of $2k+14$. For the first algorithm, we show a lower bound of $3k-2$, while the second algorithm has a lower bound of $2k-1$ when only general requests appear. The two algorithms differ in only one behavioral rule for each server that significantly influences the competitive ratio. Each server acting according to the rule allows approaching the worst-case lower bound, while it implies an increased lower bound for $k$-Server instances. In other words, there is a trade-off between performing well against instances of the $k$-Server Problem and instances containing specific requests. We also show that no deterministic online algorithm can be optimal for both kinds of instances simultaneously.}}, author = {{Castenow, Jannik and Feldkord, Björn and Knollmann, Till and Malatyali, Manuel and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures}}, isbn = {{9781450391467}}, keywords = {{K-Server Problem, Heterogeneity, Online Caching}}, pages = {{345--356}}, publisher = {{Association for Computing Machinery}}, title = {{{The k-Server with Preferences Problem}}}, doi = {{10.1145/3490148.3538595}}, year = {{2022}}, } @inproceedings{34040, abstract = {{Consider the practical goal of making a desired action profile played, when the planner can only change the payoffs, bound by stringent constraints. Applications include motivating people to choose the closest school, the closest subway station, or to coordinate on a communication protocol or an investment strategy. Employing subsidies and tolls, we adjust the game so that choosing this predefined action profile becomes strictly dominant. Inspired mainly by the work of Monderer and Tennenholtz, where the promised subsidies do not materialise in the not played profiles, we provide a fair and individually rational game adjustment, such that the total outside investments sum up to zero at any profile, thereby facilitating easy and frequent usage of our adjustment without bearing costs, even if some players behave unexpectedly. The resultant action profile itself needs no adjustment. Importantly, we also prove that our adjustment minimises the general transfer among all such adjustments, counting the total subsidising and taxation.}}, author = {{Polevoy, Gleb and Dziubiński, Marcin}}, booktitle = {{Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence}}, editor = {{De Raedt, Luc}}, keywords = {{adjustment, strictly dominant, fairness, individually rational, transfer, tax, subsidy}}, location = {{Vienna}}, publisher = {{International Joint Conferences on Artificial Intelligence Organization}}, title = {{{Fair, Individually Rational and Cheap Adjustment}}}, doi = {{10.24963/ijcai.2022/64}}, year = {{2022}}, } @inproceedings{33085, author = {{Epstein, Leah and Lassota, Alexandra and Levin, Asaf and Maack, Marten and Rohwedder, Lars}}, booktitle = {{39th International Symposium on Theoretical Aspects of Computer Science, STACS 2022, March 15-18, 2022, Marseille, France (Virtual Conference)}}, editor = {{Berenbrink, Petra and Monmege, Benjamin}}, pages = {{28:1–28:15}}, publisher = {{Schloss Dagstuhl - Leibniz-Zentrum für Informatik}}, title = {{{Cardinality Constrained Scheduling in Online Models}}}, doi = {{10.4230/LIPIcs.STACS.2022.28}}, volume = {{219}}, year = {{2022}}, } @inproceedings{33491, author = {{Maack, Marten and Pukrop, Simon and Rasmussen, Anna Rodriguez}}, booktitle = {{30th Annual European Symposium on Algorithms, ESA 2022, September 5-9, 2022, Berlin/Potsdam, Germany}}, editor = {{Chechik, Shiri and Navarro, Gonzalo and Rotenberg, Eva and Herman, Grzegorz}}, pages = {{77:1–77:13}}, publisher = {{Schloss Dagstuhl - Leibniz-Zentrum für Informatik}}, title = {{{(In-)Approximability Results for Interval, Resource Restricted, and Low Rank Scheduling}}}, doi = {{10.4230/LIPIcs.ESA.2022.77}}, volume = {{244}}, year = {{2022}}, } @article{31479, author = {{Baswana, Surender and Gupta, Shiv and Knollmann, Till}}, issn = {{0178-4617}}, journal = {{Algorithmica}}, keywords = {{Applied Mathematics, Computer Science Applications, General Computer Science}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Mincut Sensitivity Data Structures for the Insertion of an Edge}}}, doi = {{10.1007/s00453-022-00978-0}}, year = {{2022}}, } @inbook{29872, author = {{Maack, Marten and Meyer auf der Heide, Friedhelm and Pukrop, Simon}}, booktitle = {{Approximation and Online Algorithms}}, isbn = {{9783030927011}}, issn = {{0302-9743}}, publisher = {{Springer International Publishing}}, title = {{{Server Cloud Scheduling}}}, doi = {{10.1007/978-3-030-92702-8_10}}, year = {{2022}}, } @article{21096, abstract = {{While many research in distributed computing has covered solutions for self-stabilizing computing and topologies, there is far less work on self-stabilization for distributed data structures. However, when peers in peer-to-peer networks crash, a distributed data structure may not remain intact. We present a self-stabilizing protocol for a distributed data structure called the Hashed Patricia Trie (Kniesburges and Scheideler WALCOM'11) that enables efficient prefix search on a set of keys. The data structure has many applications while offering low overhead and efficient operations when embedded on top of a Distributed Hash Table. Especially, longest prefix matching for x can be done in O(log |x|) hash table read accesses. We show how to maintain the structure in a self-stabilizing way, while assuring a low overhead in a legal state and an asymptotically optimal memory demand of O(d) bits, where d is the number of bits needed for storing all keys.}}, author = {{Knollmann, Till and Scheideler, Christian}}, issn = {{0890-5401}}, journal = {{Information and Computation}}, title = {{{A self-stabilizing Hashed Patricia Trie}}}, doi = {{10.1016/j.ic.2021.104697}}, year = {{2022}}, } @inproceedings{23730, author = {{Castenow, Jannik and Harbig, Jonas and Jung, Daniel and Knollmann, Till and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 17th International Symposium on Algorithms and Experiments for Wireless Sensor Networks (ALGOSENSORS)}}, editor = {{Gasieniec, Leszek and Klasing, Ralf and Radzik, Tomasz}}, location = {{Lissabon}}, pages = {{29 -- 44}}, publisher = {{Springer}}, title = {{{Gathering a Euclidean Closed Chain of Robots in Linear Time}}}, doi = {{10.1007/978-3-030-89240-1_3}}, volume = {{12961}}, year = {{2021}}, } @inproceedings{23779, abstract = {{Produktentstehung (PE) bezieht sich auf den Prozess der Planung und Entwicklung eines Produkts sowie der damit verbundenen Dienstleistungen von der ersten Idee bis zur Herstellung und zum Vertrieb. Während dieses Prozesses gibt es zahlreiche Aufgaben, die von menschlichem Fachwissen abhängen und typischerweise von erfahrenen Experten übernommen werden. Da sich das Feld der Künstlichen Intelligenz (KI) immer weiterentwickelt und seinen Weg in den Fertigungssektor findet, gibt es viele Möglichkeiten für eine Anwendung von KI, um bei der Lösung der oben genannten Aufgaben zu helfen. In diesem Paper geben wir einen umfassenden Überblick über den aktuellen Stand der Technik des Einsatzes von KI in der PE. Im Detail analysieren wir 40 bestehende Surveys zu KI in der PE und 94 Case Studies, um herauszufinden, welche Bereiche der PE von der aktuellen Forschung in diesem Bereich vorrangig adressiert werden, wie ausgereift die diskutierten KI-Methoden sind und inwieweit datenzentrierte Ansätze in der aktuellen Forschung genutzt werden.}}, author = {{Bernijazov, Ruslan and Dicks, Alexander and Dumitrescu, Roman and Foullois, Marc and Hanselle, Jonas Manuel and Hüllermeier, Eyke and Karakaya, Gökce and Ködding, Patrick and Lohweg, Volker and Malatyali, Manuel and Meyer auf der Heide, Friedhelm and Panzner, Melina and Soltenborn, Christian}}, booktitle = {{Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21)}}, keywords = {{Artificial Intelligence Product Creation Literature Review}}, location = {{Montreal, Kanada}}, title = {{{A Meta-Review on Artificial Intelligence in Product Creation}}}, year = {{2021}}, } @article{20683, author = {{Feldkord, Björn and Knollmann, Till and Malatyali, Manuel and Meyer auf der Heide, Friedhelm}}, journal = {{Theory of Computing Systems}}, pages = {{943–984}}, title = {{{Managing Multiple Mobile Resources}}}, doi = {{10.1007/s00224-020-10023-8}}, volume = {{65}}, year = {{2021}}, }