Gathering a Euclidean Closed Chain of Robots in Linear Time and Improved Algorithms for Chain-Formation - Castenow, Jannik; Harbig, Jonas; Jung, Daniel; Knollmann, Till; Meyer auf der Heide, Friedhelm (Theoretical Computer Science)
Keywords: General Computer Science; Theoretical Computer Science

A Unifying Approach to Efficient (Near-)Gathering of Disoriented Robots with Limited Visibility - Castenow, Jannik; Harbig, Jonas; Jung, Daniel; Kling, Peter; Knollmann, Till; Meyer auf der Heide, Friedhelm (Proceedings of the 26th International Conference on Principles of Distributed Systems (OPODIS))

Online load balancing on uniform machines with limited migration - Maack, Marten (Operations Research Letters)
Keywords: Applied Mathematics; Industrial and Manufacturing Engineering; Management Science and Operations Research; Software

Unifying Gathering Protocols for Swarms of Mobile Robots - Castenow, Jannik; Harbig, Jonas; Meyer auf der Heide, Friedhelm (Lecture Notes in Computer Science)

Local Protocols for Contracting and Expanding Robot Formation Problems - Castenow, Jannik

Online Algorithms for Allocating Heterogeneous Resources - Knollmann, Till

On Cloud Assisted, Restricted, and Reosurce Constrained Scheduling - Pukrop, Simon

Server Cloud Scheduling - Maack, Marten; Meyer auf der Heide, Friedhelm; Pukrop, Simon (Algorithmica)
Abstract Consider 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.
Keywords: Applied Mathematics; Computer Science Applications; General Computer Science

Scheduling with Many Shared Resources - Deppert, Max A.; Jansen, Klaus; Maack, Marten; Pukrop, Simon; Rau, Malin (2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS))

A Discrete and Continuous Study of the Max-Chain-Formation Problem - Castenow, Jannik; Kling, Peter; Knollmann, Till; Meyer auf der Heide, Friedhelm (Information and Computation)
Keywords: Computational Theory and Mathematics; Computer Science Applications; Information Systems; Theoretical Computer Science

The k-Server with Preferences Problem - Castenow, Jannik; Feldkord, Björn; Knollmann, Till; Malatyali, Manuel; Meyer auf der Heide, Friedhelm (Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures)
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.
Keywords: K-Server Problem; Heterogeneity; Online Caching

Fair, Individually Rational and Cheap Adjustment - Polevoy, Gleb; Dziubiński, Marcin (Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence)
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.
Keywords: adjustment; strictly dominant; fairness; individually rational; transfer; tax; subsidy

Cardinality Constrained Scheduling in Online Models - Epstein, Leah; Lassota, Alexandra; Levin, Asaf; Maack, Marten; Rohwedder, Lars (39th International Symposium on Theoretical Aspects of Computer Science, STACS 2022, March 15-18, 2022, Marseille, France (Virtual Conference))

(In-)Approximability Results for Interval, Resource Restricted, and Low Rank Scheduling - Maack, Marten; Pukrop, Simon; Rasmussen, Anna Rodriguez (30th Annual European Symposium on Algorithms, ESA 2022, September 5-9, 2022, Berlin/Potsdam, Germany)

Mincut Sensitivity Data Structures for the Insertion of an Edge - Baswana, Surender; Gupta, Shiv; Knollmann, Till (Algorithmica)
Keywords: Applied Mathematics; Computer Science Applications; General Computer Science

Server Cloud Scheduling - Maack, Marten; Meyer auf der Heide, Friedhelm; Pukrop, Simon (Approximation and Online Algorithms)

A self-stabilizing Hashed Patricia Trie - Knollmann, Till; Scheideler, Christian (Information and Computation)
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.

Gathering a Euclidean Closed Chain of Robots in Linear Time - Castenow, Jannik; Harbig, Jonas; Jung, Daniel; Knollmann, Till; Meyer auf der Heide, Friedhelm (Proceedings of the 17th International Symposium on Algorithms and Experiments for Wireless Sensor Networks (ALGOSENSORS))

A Meta-Review on Artiﬁcial Intelligence in Product Creation - Bernijazov, Ruslan; Dicks, Alexander; Dumitrescu, Roman; Foullois, Marc; Hanselle, Jonas Manuel; Hüllermeier, Eyke; Karakaya, Gökce; Ködding, Patrick; Lohweg, Volker; Malatyali, Manuel; Meyer auf der Heide, Friedhelm; Panzner, Melina; et al. (Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21))
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.
Keywords: Artificial Intelligence Product Creation Literature Review

Managing Multiple Mobile Resources - Feldkord, Björn; Knollmann, Till; Malatyali, Manuel; Meyer auf der Heide, Friedhelm (Theory of Computing Systems)

A Nearly Optimal Deterministic Online Algorithm for Non-Metric Facility Location - Bienkowski, Marcin; Feldkord, Björn; Schmidt, Pawel (Proceedings of the 38th Symposium on Theoretical Aspects of Computer Science (STACS))

A continuous strategy for collisionless gathering - Li, Shouwei; Markarian, Christine; Meyer auf der Heide, Friedhelm; Podlipyan, Pavel (Theoretical Computer Science)
Over the past decades, the Gathering problem, which asks to gather a group of robots in finite time given some restrictions, has been intensively studied. In this paper, we are given a group of n autonomous, dimensionless, deterministic, and anonymous robots, with bounded viewing range. Assuming a continuous time model, the goal is to gather these robots into one point in finite time. We introduce a simple convergence criterion that defines a new class of algorithms which perform gathering in O(nd) time, where d is the diameter of the initial robot configuration. We show that some gathering algorithms in the literature belong to this class and propose two new algorithms that belong to this class and have quadratic running time, namely, Go-To-The-Relative-Center algorithm (GTRC) and Safe-Go-To-The-Relative-Center algorithm (S-GTRC). We prove that the latter can perform gathering without collision by using a slightly more complex robot model: non oblivious, chiral, and luminous (i.e. robots have observable external memory, as in [8]). We also consider a variant of the Gathering problem, the Near-Gathering problem, in which robots must get close to each other without colliding. We show that S-GTRC solves the Near-Gathering problem in quadratic time and assumes a weaker robot model than the one assumed in the current state-of-the-art.
Keywords: Local algorithms; Distributed algorithms; Collisionless gathering; Mobile robots; Multiagent system

The impact of the Gabriel subgraph of the visibility graph on the gathering of mobile autonomous robots - Li, Shouwei; Meyer auf der Heide, Friedhelm; Podlipyan, Pavel (Theoretical Computer Science)
In this paper, we reconsider the well-known discrete, round-based Go-To-The-Center algorithm due to Ando, Suzuki, and Yamashita [2] for gathering n autonomous mobile robots with limited viewing range in the plane. Remarquably, this algorithm exploits the fact that during its execution, many collisions of robots occur. Such collisions are interpreted as a success because it is assumed that such collided robots behave the same from now on. This is acceptable under the assumption that each robot is represented by a single point. Otherwise, collisions should be avoided. In this paper, we consider a continuous Go-To-The-Center algorithm in which the robots continuously observe the positions of their neighbors and adapt their speed (assuming a speed limit) and direction. Our first results are time bounds of O(n2) for gathering in two dimensions Euclidean space, and Θ(n) for the one dimension. Our main contribution is the introduction and evaluation of a continuous algorithm which performs Go-To-The-Center considering only the neighbors of a robot with respect to the Gabriel subgraph of the visibility graph, i.e. Go-To-The-Gabriel-Center algorithm. We show that this modification still correctly executes gathering in one and two dimensions, with the same time bounds as above. Simulations exhibit a severe difference of the behavior of the Go-To-The-Center and the Go-To-The-Gabriel-Center algorithms: Whereas lots of collisions occur during a run of the Go-To-The-Center algorithm, typically only one, namely the final collision occurs during a run of the Go-To-The-Gabriel-Center algorithm. We can prove this “collisionless property” of the Go-To-The-Gabriel-Center algorithm for one dimension. In two-dimensional Euclidean space, we conjecture that the “collisionless property” holds for almost every initial configuration. We support our conjecture with measurements obtained from the simulation where robots execute both continuous Go-To-The-Center and Go-To-The-Gabriel-Center algorithms.
Keywords: Local algorithms; Distributed algorithms; Collisionless gathering; Mobile robots; Multiagent system

The Max-Line-Formation Problem – And New Insights for Gathering and Chain-Formation - Castenow, Jannik; Götte, Thorsten; Knollmann, Till; Meyer auf der Heide, Friedhelm (Proceedings of the 23rd International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS 2021)

Full Version -- Server Cloud Scheduling - Maack, Marten; Meyer auf der Heide, Friedhelm; Pukrop, Simon (arXiv:2108.02109)
Consider 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 many cloud machines. Both the source and the sink have to be scheduled on the local machine. 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, the other in the cloud. The server can process 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 with respect for the makespan objective for a fairly general case and strong hardness for the case with unit processing times and delays.

Combining Mobility, Heterogeneity, and Leasing Approaches for Online Resource Allocation - Berger, Thilo Frederik

Online k-Facility Reallocation using k-Server Algorithms - Pranger, Sebastian

A Discrete and Continuous Study of the Max-Chain-Formation Problem – Slow Down to Speed Up - Castenow, Jannik; Kling, Peter; Knollmann, Till; Meyer auf der Heide, Friedhelm (Stabilization, Safety, and Security of Distributed Systems - 22nd International Symposium, SSS 2020, Austin, Texas, USA, November 18-21, 2020, Proceedings)
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.

Mincut Sensitivity Data Structures for the Insertion of an Edge - Baswana, Surender; Gupta, Shiv; Knollmann, Till (28th Annual European Symposium on Algorithms (ESA 2020))
Let G = (V,E) be an undirected graph on n vertices with non-negative capacities on its edges. The mincut sensitivity problem for the insertion of an edge is defined as follows. Build a compact data structure for G and a given set S ⊆ V of vertices that, on receiving any edge (x,y) ∈ S×S of positive capacity as query input, can efficiently report the set of all pairs from S× S whose mincut value increases upon insertion of the edge (x,y) to G. The only result that exists for this problem is for a single pair of vertices (Picard and Queyranne, Mathematical Programming Study, 13 (1980), 8-16). We present the following results for the single source and the all-pairs versions of this problem. 1) Single source: Given any designated source vertex s, there exists a data structure of size 𝒪(|S|) that can output all those vertices from S whose mincut value to s increases upon insertion of any given edge. The time taken by the data structure to answer any query is 𝒪(|S|). 2) All-pairs: There exists an 𝒪(|S|²) size data structure that can output all those pairs of vertices from S× S whose mincut value gets increased upon insertion of any given edge. The time taken by the data structure to answer any query is 𝒪(k), where k is the number of pairs of vertices whose mincut increases. For both these versions, we also address the problem of reporting the values of the mincuts upon insertion of any given edge. To derive our results, we use interesting insights into the nearest and the farthest mincuts for a pair of vertices. In addition, a crucial result, that we establish and use in our data structures, is that there exists a directed acyclic graph of 𝒪(n) size that compactly stores the farthest mincuts from all vertices of V to a designated vertex s in the graph. We believe that this result is of independent interest, especially, because it also complements a previously existing result by Hariharan et al. (STOC 2007) that the nearest mincuts from all vertices of V to s is a laminar family, and hence, can be stored compactly in a tree of 𝒪(n) size.
Keywords: Mincut; Sensitivity; Data Structure

Brief Announcement: Gathering in Linear Time: A Closed Chain of Disoriented & Luminous Robots with Limited Visibility - Castenow, Jannik; Harbig, Jonas; Jung, Daniel; Knollmann, Till; Meyer auf der Heide, Friedhelm (Stabilization, Safety, and Security of Distributed Systems - 22nd International Symposium, SSS 2020, Austin, Texas, USA, November 18-21, 2020, Proceedings)

The Online Multi-Commodity Facility Location Problem - Castenow, Jannik; Feldkord, Björn; Knollmann, Till; Malatyali, Manuel; Meyer auf der Heide, Friedhelm (Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures)
We consider a natural extension to the metric uncapacitated Facility Location Problem (FLP) in which requests ask for different commodities out of a finite set \( S \) of commodities. Ravi and Sinha (SODA 2004) introduced the model as the Multi-Commodity Facility Location Problem (MFLP) and considered it an offline optimization problem. The model itself is similar to the FLP: i.e., requests are located at points of a finite metric space and the task of an algorithm is to construct facilities and assign requests to facilities while minimizing the construction cost and the sum over all assignment distances. In addition, requests and facilities are heterogeneous; they request or offer multiple commodities out of $S$. A request has to be connected to a set of facilities jointly offering the commodities demanded by it. In comparison to the FLP, an algorithm has to decide not only if and where to place facilities, but also which commodities to offer at each. To the best of our knowledge we are the first to study the problem in its online variant in which requests, their positions and their commodities are not known beforehand but revealed over time. We present results regarding the competitive ratio. On the one hand, we show that heterogeneity influences the competitive ratio by developing a lower bound on the competitive ratio for any randomized online algorithm of \( Ω ( \sqrt{|S|} + \frac{\log n}{\log \log n} ) \) that already holds for simple line metrics. Here, \( n \) is the number of requests. On the other side, we establish a deterministic \( \mathcal{O}(\sqrt{|S|} · \log n) \)-competitive algorithm and a randomized \( \mathcal{O}(\sqrt{|S|} · \frac{\log n}{\log \log n} ) \)-competitive algorithm. Further, we show that when considering a more special class of cost functions for the construction cost of a facility, the competitive ratio decreases given by our deterministic algorithm depending on the function.
Keywords: Online Multi-Commodity Facility Location; Competitive Ratio; Online Optimization; Facility Location Problem

Brief Announcement: A Discrete and Continuous Study of the Max-Chain-Formation Problem: Slow Down to Speed up - Castenow, Jannik; Kling, Peter; Knollmann, Till; Meyer auf der Heide, Friedhelm (Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures)

Local Gathering of Mobile Robots in Three Dimensions - Braun, Michael; Castenow, Jannik; Meyer auf der Heide, Friedhelm (Proceedings of the 27th Conference on Structural Information and Communication Complexity (SIROCCO))
In this work, we initiate the research about the Gathering problem for robots with limited viewing range in the three-dimensional Euclidean space. In the Gathering problem, a set of initially scattered robots is required to gather at the same position. The robots' capabilities are very restricted -- they do not agree on any coordinate system or compass, have a limited viewing range, have no memory of the past and cannot communicate. We study the problem in two different time models, in FSYNC (fully synchronized discrete rounds) and the continuous time model. For FSYNC, we introduce the 3D-Go-To-The-Center-strategy and prove a runtime of $Θ(n^2)$ that matches the currently best runtime bound for the same model in the Euclidean plane [SPAA'11]. Our main result is the generalization of contracting strategies (continuous time) from [Algosensors'17] to three dimensions. In contracting strategies, every robot that is located on the global convex hull of all robots' positions moves with full speed towards the inside of the convex hull. We prove a runtime bound of $O(Δ · n^{3/2})$ for any three-dimensional contracting strategy, where $Δ$ denotes the diameter of the initial configuration. This comes up to a factor of $\sqrt{n}$ close to the lower bound of $Ω (Δ · n)$ which is already true in two dimensions. In general, it might be hard for robots with limited viewing range to decide whether they are located on the global convex hull and which movement maintains the connectivity of the swarm, rendering the design of concrete contracting strategies a challenging task. We prove that the continuous variant of 3D-Go-To-The-Center is contracting and keeps the swarm connected. Moreover, we give a simple design criterion for three-dimensional contracting strategies that maintains the connectivity of the swarm and introduce an exemplary strategy based on this criterion.

Mobile Resource Allocation - Feldkord, Björn

Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets - Wever, Marcel Dominik; van Rooijen, Lorijn; Hamann, Heiko (Evolutionary Computation)
In software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users to specify a desired software system on their own. With our approach, users are only asked to provide exemplary behavioral descriptions. The problem of synthesizing a requirements specification from examples can partially be reduced to the problem of grammatical inference, to which we apply an active coevolutionary learning approach. However, this approach would usually require many feedback queries to be sent to the user. In this work, we extend and generalize our active learning approach to receive knowledge from multiple oracles, also known as proactive learning. The ‘user oracle’ represents input received from the user and the ‘knowledge oracle’ represents available, formalized domain knowledge. We call our two-oracle approach the ‘first apply knowledge then query’ (FAKT/Q) algorithm. We compare FAKT/Q to the active learning approach and provide an extensive benchmark evaluation. As result we find that the number of required user queries is reduced and the inference process is sped up significantly. Finally, with so-called On-The-Fly Markets, we present a motivation and an application of our approach where such knowledge is available.

A Bounding Box Overlay for Competitive Routing in Hybrid Communication Networks - Castenow, Jannik; Kolb, Christina; Scheideler, Christian (Proceedings of the 21st International Conference on Distributed Computing and Networking (ICDCN))

Gathering Anonymous, Oblivious Robots on a Grid - Castenow, Jannik; Fischer, Matthias; Harbig, Jonas; Jung, Daniel; Meyer auf der Heide, Friedhelm (Theoretical Computer Science)

Approximating Weighted Completion Time for Order Scheduling with Setup Times - Pukrop, Simon; Mäcker, Alexander; Meyer auf der Heide, Friedhelm (Proceedings of the 46th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM))

A Case for a New IT Ecosystem: On-The-Fly Computing - Karl, Holger; Kundisch, Dennis; Meyer auf der Heide, Friedhelm; Wehrheim, Heike (Business & Information Systems Engineering)

Fault Tolerant and Fully Dynamic DFS in Undirected Graphs: Simple Yet Efficient - Baswana, Surender; Gupta, Shiv; Tulsyan, Ayush (44th International Symposium on Mathematical Foundations of Computer Science (MFCS 2019))

Approaches for Collaborative Security Defences in Multi Network Environments - Koning, Ralph; Polevoy, Gleb; Meijer, Lydia; de Laat, Cees; Grosso, Paola (2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom))
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.
Keywords: 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

Big Data: Sublinear Algorithms for Distributed Data Streams - Malatyali, Manuel

Approximate Pure Nash Equilibria in Congestion, Opinion Formation and Facility Location Games - Feldotto, Matthias
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.

Scheduling on (Un-)Related Machines with Setup Times - Jansen, Klaus; Maack, Marten; Mäcker, Alexander (Proceedings of the 33rd IEEE International Parallel and Distributed Processing Symposium (IPDPS))

Multi-unit Bilateral Trade - Lazos, Philip; Goldberg, Paul; Skopalik, Alexander; Gerstgrasser, Matthias; de Keijzer, Bart (Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI))
We characterise the set of dominant strategy incentive compatible (DSIC), strongly budget balanced (SBB), and ex-post individually rational (IR) mechanisms for the multi-unit bilateral trade setting. In such a setting there is a single buyer and a single seller who holds a finite number k of identical items. The mechanism has to decide how many units of the item are transferred from the seller to the buyer and how much money is transferred from the buyer to the seller. We consider two classes of valuation functions for the buyer and seller: Valuations that are increasing in the number of units in possession, and the more specific class of valuations that are increasing and submodular. Furthermore, we present some approximation results about the performance of certain such mechanisms, in terms of social welfare: For increasing submodular valuation functions, we show the existence of a deterministic 2-approximation mechanism and a randomised e/(1-e) approximation mechanism, matching the best known bounds for the single-item setting.

Managing Multiple Mobile Resources - Feldkord, Björn; Knollmann, Till; Malatyali, Manuel; Meyer auf der Heide, Friedhelm (Proceedings of the 17th Workshop on Approximation and Online Algorithms (WAOA))

On Scheduling with Setup Times - Mäcker, Alexander

Rendering of Complex Heterogenous Scenes using Progressive Blue Surfels - Brandt, Sascha; Jähn, Claudius; Fischer, Matthias; Meyer auf der Heide, Friedhelm (arXiv:1904.08225)
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.

The Mobile Server Problem - Feldkord, Björn; Meyer auf der Heide, Friedhelm (ACM Transactions on Parallel Computing (TOPC))

Paul Curzon, Peter W. McOwan: Computational Thinking; Die Welt des algorithmischen Denkens – in Spielen, Zaubertricks und Rätseln - Meyer auf der Heide, Friedhelm (Mathematische Semesterberichte)