A Self-Stabilizing Hashed Patricia Trie - Knollmann, Till; Scheideler, Christian (Proceedings of the 20th International Symposium on Stabilization, Safety, and Security of Distributed Systems (SSS))
While a lot of 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. Considering crashing peers in peer-to-peer networks, it should not be taken for granted that a distributed data structure remains intact. In this work, 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 a wide area of applications including string matching problems 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 $\mathcal{O}(\log |x|)$ hash table read accesses. We show how to maintain the structure in a self-stabilizing way. Our protocol assures low overhead in a legal state and a total (asymptotically optimal) memory demand of $Θ(d)$ bits, where $d$ is the number of bits needed for storing all keys.
Keywords: Self-Stabilizing; Prefix Search; Distributed Data Structure

Competitive Routing in Hybrid Communication Networks - Jung, Daniel; Kolb, Christina; Scheideler, Christian; Sundermeier, Jannik (Proceedings of the 14th International Symposium on Algorithms and Experiments for Wireless Networks (ALGOSENSORS))
Routing is a challenging problem for wireless ad hoc networks, especially when the nodes are mobile and spread so widely that in most cases multiple hops are needed to route a message from one node to another. In fact, it is known that any online routing protocol has a poor performance in the worst case, in a sense that there is a distribution of nodes resulting in bad routing paths for that protocol, even if the nodes know their geographic positions and the geographic position of the destination of a message is known. The reason for that is that radio holes in the ad hoc network may require messages to take long detours in order to get to a destination, which are hard to find in an online fashion. In this paper, we assume that the wireless ad hoc network can make limited use of long-range links provided by a global communication infrastructure like a cellular infrastructure or a satellite in order to compute an abstraction of the wireless ad hoc network that allows the messages to be sent along near-shortest paths in the ad hoc network. We present distributed algorithms that compute an abstraction of the ad hoc network in $\mathcal{O}\left(\log ^2 n\right)$ time using long-range links, which results in $c$-competitive routing paths between any two nodes of the ad hoc network for some constant $c$ if the convex hulls of the radio holes do not intersect. We also show that the storage needed for the abstraction just depends on the number and size of the radio holes in the wireless ad hoc network and is independent on the total number of nodes, and this information just has to be known to a few nodes for the routing to work.
Keywords: greedy routing; ad hoc networks; convex hulls; c-competitiveness

Brief Announcement: Competitive Routing in Hybrid Communication Networks - Jung, Daniel; Kolb, Christina; Scheideler, Christian; Sundermeier, Jannik (Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures (SPAA))

Brief Announcement: Communication in Systems of Home Based Mobile Agents - Meyer auf der Heide, Friedhelm; Schaefer, Johannes Sebastian (Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA '18)

A Peer-to-Peer based Cloud Storage supporting orthogonal Range Queries of arbitrary Dimension - Benter, Markus; Knollmann, Till; Meyer auf der Heide, Friedhelm; Setzer, Alexander; Sundermeier, Jannik (Proceedings of the 4th International Symposium on Algorithmic Aspects of Cloud Computing (ALGOCLOUD))
We present a peer-to-peer network that supports the efficient processing of orthogonal range queries $R=\bigtimes_{i=1}^{d}[a_i,\,b_i]$ in a $d$-dimensional point space.\\ The network is the same for each dimension, namely a distance halving network like the one introduced by Naor and Wieder (ACM TALG'07). We show how to execute such range queries using $\mathcal{O}\left(2^{d'}d\,\log m + d\,|R|\right)$ hops (and the same number of messages) in total. Here $[m]^d$ is the ground set, $|R|$ is the size and $d'$ the dimension of the queried range. Furthermore, if the peers form a distributed network, the query can be answered in $\mathcal{O}\left(d\,\log m + d\,\sum_{i=1}^{d}(b_i-a_i+1)\right)$ communication rounds. Our algorithms are based on a mapping of the Hilbert Curve through $[m]^d$ to the peers.
Keywords: Distributed Storage; Multi-Dimensional Range Queries; Peer-to-Peer; Hilbert Curve

Mobile Facility Leasing - Geromel, Marcel

Online Algorithmen für das k-Page Migration Problem - Kolpaczki, Patrick Irenäus

Congestion games with mixed objectives - Feldotto, Matthias; Leder, Lennart; Skopalik, Alexander (Journal of Combinatorial Optimization)
We study a new class of games which generalizes congestion games andits bottleneck variant. We introduce congestion games with mixed objectives to modelnetwork scenarios in which players seek to optimize for latency and bandwidths alike.We characterize the (non-)existence of pure Nash equilibria (PNE), the convergenceof improvement dynamics, the quality of equilibria and show the complexity of thedecision problem. For games that do not possess PNE we give bounds on the approx-imation ratio of approximate pure Nash equilibria.

Pure Nash Equilibria in Robust Congestion Games via Potential Functions - Kemper, Arne

Scenario-driven Strategy Analysis in a n-player Composition Game Model - Nachtigall, Marcel

Learning deterministic bandit behaviour form compositions - Kempf, Jérôme

Local Strategies for Swarm Formations on a Grid - Jung, Daniel
My dissertation deals with the Gathering problem for swarms of n point-shaped robots on a grid, in which all robots of the swarm are supposed to gather at a previously undefined point. Special attention is paid to the strong limitation of robot capabilities. These include in particular the lack of global control, a global compass, global visibility and (global) communication skills. Furthermore, all robots are identical. The robots are given only local abilities. This includes a constant range of vision. The robots all work completely synchronously. In this work we present and analyze three different Gathering strategies in different robot models. We formally prove correctness and total running time: Chapter 4 focuses on minimizing the available robot capabilities. The underlying strategy completes the gathering in O(n^2) time. For the following Chapters 5 and 6, the aim is to optimize the total running time under using only local robot capabilities: We additionally allow a constant-sized memory and a constant number of locally visible statuses (lights, flags). For the strategies of both chapters we show an asymptotically optimal running time of O(n). Unlike in Chapters 4 and 5, we additionally restrict connectivity and vision to an initially given chain connectivity in Chapter 6, where two chain neighbors must have a distance of 1 from each other. A robot can only see and interact with a constant number of its direct chain neighbors.

A Dynamic Distributed Data Structure for Top-k and k-Select Queries - Feldkord, Björn; Malatyali, Manuel; Meyer auf der Heide, Friedhelm (Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications)

Pure Nash equilibria in restricted budget games - Drees, Maximilian; Feldotto, Matthias; Riechers, Sören; Skopalik, Alexander (Journal of Combinatorial Optimization)
In budget games, players compete over resources with finite budgets. For every resource, a player has a specific demand and as a strategy, he chooses a subset of resources. If the total demand on a resource does not exceed its budget, the utility of each player who chose that resource equals his demand. Otherwise, the budget is shared proportionally. In the general case, pure Nash equilibria (NE) do not exist for such games. In this paper, we consider the natural classes of singleton and matroid budget games with additional constraints and show that for each, pure NE can be guaranteed. In addition, we introduce a lexicographical potential function to prove that every matroid budget game has an approximate pure NE which depends on the largest ratio between the different demands of each individual player.

Parallel fixed parameter tractable problems - Li, Shouwei

Leasing with Uncertainty - Markarian, Christine (International Conference on Operations Research (OR))

Scheduling Access to Shared Space in Multi-robot Systems - Khaluf, Yara; Markarian, Christine; Simoens, Pieter; Reina, Andreagiovanni (International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2017))
Through this study, we introduce the idea of applying scheduling techniques to allocate spatial resources that are shared among multiple robots moving in a static environment and having temporal constraints on the arrival time to destinations. To illustrate this idea, we present an exemplified algorithm that plans and assigns a motion path to each robot. The considered problem is particularly challenging because: (i) the robots share the same environment and thus the planner must take into account overlapping paths which cannot happen at the same time; (ii) there are time deadlines thus the planner must deal with temporal constraints; (iii) new requests arrive without a priori knowledge thus the planner must be able to add new paths online and adjust old plans; (iv) the robot motion is subject to noise thus the planner must be reactive to adapt to online changes. We showcase the functioning of the proposed algorithm through a set of agent-based simulations.

Congestion Games with Complementarities - Feldotto, Matthias; Leder, Lennart; Skopalik, Alexander (Proceedings of the 10th International Conference on Algorithms and Complexity (CIAC))
We study a model of selfish resource allocation that seeks to incorporate dependencies among resources as they exist in in modern networked environments. Our model is inspired by utility functions with constant elasticity of substitution (CES) which is a well-studied model in economics. We consider congestion games with different aggregation functions. In particular, we study $L_p$ norms and analyze the existence and complexity of (approximate) pure Nash equilibria. Additionally, we give an almost tight characterization based on monotonicity properties to describe the set of aggregation functions that guarantee the existence of pure Nash equilibria.

Computing Approximate Pure Nash Equilibria in Shapley Value Weighted Congestion Games - Feldotto, Matthias; Gairing, Martin; Kotsialou, Grammateia; Skopalik, Alexander (Proceedings of the 13th International Conference on Web and Internet Economics (WINE))
We study the computation of approximate pure Nash equilibria in Shapley value (SV) weighted congestion games, introduced in [19]. This class of games considers weighted congestion games in which Shapley values are used as an alternative (to proportional shares) for distributing the total cost of each resource among its users. We focus on the interesting subclass of such games with polynomial resource cost functions and present an algorithm that computes approximate pure Nash equilibria with a polynomial number of strategy updates. Since computing a single strategy update is hard, we apply sampling techniques which allow us to achieve polynomial running time. The algorithm builds on the algorithmic ideas of [7], however, to the best of our knowledge, this is the first algorithmic result on computation of approximate equilibria using other than proportional shares as player costs in this setting. We present a novel relation that approximates the Shapley value of a player by her proportional share and vice versa. As side results, we upper bound the approximate price of anarchy of such games and significantly improve the best known factor for computing approximate pure Nash equilibria in weighted congestion games of [7].

Filtering Undesirable Flows in Networks - Polevoy, Gleb; Trajanovski, Stojan; Grosso, Paola; de Laat, Cees (Combinatorial Optimization and Applications: 11th International Conference, COCOA 2017, Shanghai, China, December 16-18, 2017, Proceedings, Part I)
Keywords: flow; filter; MMSA; set cover; approximation; local ratio algorithm

Reciprocation Effort Games - Polevoy, Gleb; de Weerdt, M.M. (Proceedings of the 29th Benelux Conference on Artificial Intelligence)
Keywords: interaction; reciprocation; contribute; shared effort; curbing; convergence; threshold; Nash equilibrium; social welfare; efficiency; price of anarchy; price of stability

Competition between Cooperative Projects - Polevoy, Gleb; de Weerdt, M.M. (Proceedings of the 29th Benelux Conference on Artificial Intelligence)
Keywords: agents; projects; contribute; shared effort game; competition; quota; threshold; Nash equilibrium; social welfare; efficiency; price of anarchy; price of stability

Gathering Anonymous, Oblivious Robots on a Grid - Fischer, Matthias; Jung, Daniel; Meyer auf der Heide, Friedhelm (arXiv:1702.03400)
We consider a swarm of $n$ autonomous mobile robots, distributed on a 2-dimensional grid. A basic task for such a swarm is the gathering process: All robots have to gather at one (not predefined) place. A common local model for extremely simple robots is the following: The robots do not have a common compass, only have a constant viewing radius, are autonomous and indistinguishable, can move at most a constant distance in each step, cannot communicate, are oblivious and do not have flags or states. The only gathering algorithm under this robot model, with known runtime bounds, needs $\mathcal{O}(n^2)$ rounds and works in the Euclidean plane. The underlying time model for the algorithm is the fully synchronous $\mathcal{FSYNC}$ model. On the other side, in the case of the 2-dimensional grid, the only known gathering algorithms for the same time and a similar local model additionally require a constant memory, states and "flags" to communicate these states to neighbors in viewing range. They gather in time $\mathcal{O}(n)$. In this paper we contribute the (to the best of our knowledge) first gathering algorithm on the grid that works under the same simple local model as the above mentioned Euclidean plane strategy, i.e., without memory (oblivious), "flags" and states. We prove its correctness and an $\mathcal{O}(n^2)$ time bound in the fully synchronous $\mathcal{FSYNC}$ time model. This time bound matches the time bound of the best known algorithm for the Euclidean plane mentioned above. We say gathering is done if all robots are located within a $2× 2$ square, because in $\mathcal{FSYNC}$ such configurations cannot be solved.

Non-Clairvoyant Scheduling to Minimize Max Flow Time on a Machine with Setup Times - Mäcker, Alexander; Malatyali, Manuel; Meyer auf der Heide, Friedhelm; Riechers, Sören (Proceedings of the 15th Workshop on Approximation and Online Algorithms (WAOA))
Consider a problem in which $n$ jobs that are classified into $k$ types arrive over time at their release times and are to be scheduled on a single machine so as to minimize the maximum flow time.The machine requires a setup taking $s$ time units whenever it switches from processing jobs of one type to jobs of a different type.We consider the problem as an online problem where each job is only known to the scheduler as soon as it arrives and where the processing time of a job only becomes known upon its completion (non-clairvoyance).We are interested in the potential of simple ``greedy-like'' algorithms.We analyze a modification of the FIFO strategy and show its competitiveness to be $Θ(\sqrt{n})$, which is optimal for the considered class of algorithms.For $k=2$ types it achieves a constant competitiveness.Our main insight is obtained by an analysis of the smoothed competitiveness.If processing times $p_j$ are independently perturbed to $\hat p_j = (1+X_j)p_j$, we obtain a competitiveness of $O(σ^{-2} \log^2 n)$ when $X_j$ is drawn from a uniform or a (truncated) normal distribution with standard deviation $σ$.The result proves that bad instances are fragile and ``practically'' one might expect a much better performance than given by the $Ω(\sqrt{n})$-bound.

Modular-Width: An Auxiliary Parameter for Parameterized Parallel Complexity - Abu-Khzam, Faisal N.; Li, Shouwei; Markarian, Christine; Meyer auf der Heide, Friedhelm; Podlipyan, Pavel (Proceedings of the 11th International Workshop on Frontiers in Algorithmics (FAW))
Many graph problems such as maximum cut, chromatic number, hamiltonian cycle, and edge dominating set are known to be fixed-parameter tractable (FPT) when parameterized by the treewidth of the input graphs, but become W-hard with respect to the clique-width parameter. Recently, Gajarský et al. proposed a new parameter called modular-width using the notion of modular decomposition of graphs. They showed that the chromatic number problem and the partitioning into paths problem, and hence hamiltonian path and hamiltonian cycle, are FPT when parameterized by this parameter. In this paper, we study modular-width in parameterized parallel complexity and show that the weighted maximum clique problem and the maximum matching problem are fixed-parameter parallel-tractable (FPPT) when parameterized by this parameter.

Sharing is Caring: Multiprocessor Scheduling with a Sharable Resource - Kling, Peter; Mäcker, Alexander; Riechers, Sören; Skopalik, Alexander (Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA))
We consider a scheduling problem on $m$ identical processors sharing an arbitrarily divisible resource. In addition to assigning jobs to processors, the scheduler must distribute the resource among the processors (e.g., for three processors in shares of 20%, 15%, and 65%) and adjust this distribution over time. Each job $j$ comes with a size $p_j \in \mathbb{R}$ and a resource requirement $r_j > 0$. Jobs do not benefit when receiving a share larger than $r_j$ of the resource. But providing them with a fraction of the resource requirement causes a linear decrease in the processing efficiency. We seek a (non-preemptive) job and resource assignment minimizing the makespan.Our main result is an efficient approximation algorithm which achieves an approximation ratio of $2 + 1/(m-2)$. It can be improved to an (asymptotic) ratio of $1 + 1/(m-1)$ if all jobs have unit size. Our algorithms also imply new results for a well-known bin packing problem with splittable items and a restricted number of allowed item parts per bin.Based upon the above solution, we also derive an approximation algorithm with similar guarantees for a setting in which we introduce so-called tasks each containing several jobs and where we are interested in the average completion time of tasks (a task is completed when all its jobs are completed).

Price Fluctuations in Online Leasing - Feldkord, Björn; Markarian, Christine; Meyer auf der Heide, Friedhelm (Proceedings of the 11th Annual International Conference on Combinatorial Optimization and Applications (COCOA))

Local Algorithms for the Continuous Gathering Problem - Podlipyan, Pavel

Scheduling with Scarce Resources - Riechers, Sören

Cost-efficient Scheduling on Machines from the Cloud - Mäcker, Alexander; Malatyali, Manuel; Meyer auf der Heide, Friedhelm; Riechers, Sören (Journal of Combinatorial Optimization)

From User Demand to Software Service: Using Machine Learning to Automate the Requirements Specification Process - van Rooijen, Lorijn; Bäumer, Frederik Simon; Platenius, Marie Christin; Geierhos, Michaela; Hamann, Heiko; Engels, Gregor (2017 IEEE 25th International Requirements Engineering Conference Workshops (REW))
Bridging the gap between informal, imprecise, and vague user requirements descriptions and precise formalized specifications is the main task of requirements engineering. Techniques such as interviews or story telling are used when requirements engineers try to identify a user's needs. The requirements specification process is typically done in a dialogue between users, domain experts, and requirements engineers. In our research, we aim at automating the specification of requirements. The idea is to distinguish between untrained users and trained users, and to exploit domain knowledge learned from previous runs of our system. We let untrained users provide unstructured natural language descriptions, while we allow trained users to provide examples of behavioral descriptions. In both cases, our goal is to synthesize formal requirements models similar to statecharts. From requirements specification processes with trained users, behavioral ontologies are learned which are later used to support the requirements specification process for untrained users. Our research method is original in combining natural language processing and search-based techniques for the synthesis of requirements specifications. Our work is embedded in a larger project that aims at automating the whole software development and deployment process in envisioned future software service markets.
Keywords: Software; Unified modeling language; Requirements engineering; Ontologies; Search problems; Natural languages

The Mobile Server Problem - Feldkord, Björn; Meyer auf der Heide, Friedhelm (Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA))
We introduce the mobile server problem, inspired by current trends to move computational tasks from cloud structures to multiple devices close to the end user. An example for this are embedded systems in autonomous cars that communicate in order to coordinate their actions. Our model is a variant of the classical Page Migration Problem. Moreformally, we consider a mobile server holding a data page.The server can move in the Euclidean space (of arbitrary dimension). In every round, requests for data items from the page pop up at arbitrary points in the space. The requests are served, each at a cost of the distance from the requesting point and the server, and the mobile server may move, at a cost D times the distance traveled for some constant D . We assume a maximum distance m the server is allowed to move per round. We show that no online algorithm can achieve a competitive ratio independent of the length of the input sequence in this setting. Hence we augment the maximum movement distance of the online algorithms to ( 1 + δ) times the maximum distance of the offline solution. We provide a deterministic algorithm which is simple to describe and works for multiple variants of our problem. The algorithm achieves almost tight competitive ratios independent of the length of the input sequence.

Pure Nash Equilibria in Restricted Budget Games - Drees, Maximilian; Feldotto, Matthias; Riechers, Sören; Skopalik, Alexander (Proceedings of the 23rd International Computing and Combinatorics Conference (COCOON))
In budget games, players compete over resources with finite budgets. For every resource, a player has a specific demand and as a strategy, he chooses a subset of resources. If the total demand on a resource does not exceed its budget, the utility of each player who chose that resource equals his demand. Otherwise, the budget is shared proportionally. In the general case, pure Nash equilibria (NE) do not exist for such games. In this paper, we consider the natural classes of singleton and matroid budget games with additional constraints and show that for each, pure NE can be guaranteed. In addition, we introduce a lexicographical potential function to prove that every matroid budget game has an approximate pure NE which depends on the largest ratio between the different demands of each individual player.

On-The-Fly Konstruktion zusammenhängender Straßennetze aus gegebenen Einzelteilen - Nowack, Joshua

Wissenschaftsforum Intelligente Technische Systeme (WInTeSys) - Gausemeier, Jürgen; Bodden, Eric; Dressler, Falko; Dumitrescu, Roman; Meyer auf der Heide, Friedhelm; Scheytt, Christoph; Trächtler, Ansgar

Monitoring of Domain-Related Problems in Distributed Data Streams - Bemmann, Pascal; Biermeier, Felix; Bürmann, Jan; Kemper, Arne; Knollmann, Till; Knorr, Steffen; Kothe, Nils; Mäcker, Alexander; Malatyali, Manuel; Meyer auf der Heide, Friedhelm; Riechers, Sören; Schaefer, Johannes Sebastian; et al. (Structural Information and Communication Complexity)

Sortieren dynamischer Daten - Nachtigall, Simon

Robuste Optimierung in Congestion Games - Pukrop, Simon

Complexity of Signalling in Routing Games under Uncertainty - Bürmann, Jan

Bounding the Inefficiency of Equilibria in Congestion Games under Taxation - Vijayalakshmi, Vipin Ravindran

Making Gamification Easy for the Professor: Decoupling Game and Content with the StudyNow Mobile App - Feldotto, Matthias; John, Thomas; Kundisch, Dennis; Hemsen, Paul; Klingsieck, Katrin; Skopalik, Alexander (Proceedings of the 12th International Conference on Design Science Research in Information Systems and Technology (DESRIST))
Many university students struggle with motivational problems, and gamification has the potential to address these problems. However, gamification is hardly used in education, because current approaches to gamification require instructors to engage in the time-consuming preparation of their course contents for use in quizzes, mini-games and the like. Drawing on research on limited attention and present bias, we propose a "lean" approach to gamification, which relies on gamifying learning activities (rather than learning contents) and increasing their salience. In this paper, we present the app StudyNow that implements such a lean gamification approach. With this app, we aim to enable more students and instructors to benefit from the advantages of gamification.

Towards a Lean Approach for Gamifying Education - John, Thomas; Feldotto, Matthias; Hemsen, Paul; Klingsieck, Katrin; Kundisch, Dennis; Langendorf, Mike (Proceedings of the 25th European Conference on Information Systems (ECIS))
Many university students struggle with motivational problems, and gamification has the potential to address these problems. However, using gamification currently is rather tedious and time-consuming for instructors because current approaches to gamification require instructors to engage in the time-consuming preparation of course contents (e.g., for quizzes or mini-games). In reply to this issue, we propose a “lean” approach to gamification, which relies on gamifying learning activities rather than learning contents. The learning activities that are gamified in the lean approach can typically be drawn from existing course syllabi (e.g., attend certain lectures, hand in assignments, read book chapters and articles). Hence, compared to existing approaches, lean gamification substantially lowers the time requirements posed on instructors for gamifying a given course. Drawing on research on limited attention and the present bias, we provide the theoretical foundation for the lean gamification approach. In addition, we present a mobile application that implements lean gamification and outline a mixed-methods study that is currently under way for evaluating whether lean gamification does indeed have the potential to increase students’ motivation. We thereby hope to allow more students and instructors to benefit from the advantages of gamification.

Continuous Speed Scaling with Variability: A Simple and Direct Approach - Antoniadis, Antonios; Kling, Peter; Ott, Sebastian; Riechers, Sören (Theoretical Computer Science)
We consider an extension of the dynamic speed scaling scheduling model introduced by Yao et al.: A set of jobs, each with a release time, deadline, and workload, has to be scheduled on a single, speed-scalable processor. Both the maximum allowed speed of the processor and the energy costs may vary continuously over time. The objective is to find a feasible schedule that minimizes the total energy costs. Theoretical algorithm design for speed scaling problems often tends to discretize problems, as our tools in the discrete realm are often better developed or understood. Using the above speed scaling variant with variable, continuous maximal processor speeds and energy prices as an example, we demonstrate that a more direct approach via tools from variational calculus can not only lead to a very concise and elegant formulation and analysis, but also avoids the “explosion of variables/constraints” that often comes with discretizing. Using well-known tools from calculus of variations, we derive combinatorial optimality characteristics for our continuous problem and provide a quite concise and simple correctness proof.

Automatic Derivation of Geometric Properties of Components From 3D Polygon Models - Brandt, Sascha; Fischer, Matthias; Gerges, Maria; Jähn, Claudius; Berssenbrügge, Jan (Volume 1: 37th Computers and Information in Engineering Conference)
To detect errors or find potential for improvement during the CAD-supported development of a complex technical system like modern industrial machines, the system’s virtual prototype can be examined in virtual reality (VR) in the context of virtual design reviews. Besides exploring the static shape of the examined system, observing the machines’ mechanics (e.g., motor-driven mechanisms) and transport routes for the material transport (e.g., via conveyor belts or chains, or rail-based transport systems) can play an equally important role in such a review. In practice it is often the case, that the relevant information about transport routes, or kinematic properties is either not consequently modeled in the CAD data or is lost during conversion processes. To significantly reduce the manual effort and costs for creating animations of the machines complex behavior with such limited input data for a design review, we present a set of algorithms to automatically determine geometrical properties of machine parts based only on their triangulated surfaces. The algorithms allow to detect the course of transport systems, the orientation of objects in 3d space, rotation axes of cylindrical objects and holes, the number of tooth of gears, as well as the tooth spacing of toothed racks. We implemented the algorithms in the VR system PADrend and applied them to animate virtual prototypes of real machines.

Automatische Ableitung der Transportwege von Transportsystemen aus dem 3D-Polygonmodell - Brandt, Sascha; Fischer, Matthias (Wissenschaftsforum Intelligente Technische Systeme (WInTeSys) 2017)
In der CAD-unterstützten Entwicklung von technischen Systemen (Maschinen, Anlagen etc.) werden virtuelle Prototypen im Rahmen eines virtuellen Design-Reviews mit Hilfe eines VR-Systems gesamtheitlich betrachtet, um frühzeitig Fehler und Verbesserungsbedarf zu erkennen. Ein wichtiger Untersuchungsgegenstand ist dabei die Analyse von Transportwegen für den Materialtransport mittels Fließbändern, Förderketten oder schienenbasierten Transportsystemen. Diese Transportwege werden im VR-System animiert. Problematisch dabei ist, dass derartige Transportsysteme im zugrundeliegenden CAD-Modell in der Praxis oft nicht modelliert und nur exemplarisch angedeutet werden, da diese für die Konstruktion nicht relevant sind (z.B. der Fördergurt eines Förderbandes, oder die Kette einer Förderkette), oder die Informationen über den Verlauf bei der Konvertierung der Daten in das VR-System verloren gehen. Bei der Animation dieser Transportsysteme in einem VR-System muss der Transportweg also aufwändig, manuell nachgearbeitet werden. Das Ziel dieser Arbeit ist die Reduzierung des notwendigen manuellen Nachbearbeitungsaufwandes für das Design-Review durch eine automatische Berechnung der Animationspfade entlang eines Transportsystems. Es wird ein Algorithmus vorgestellt, der es ermöglicht mit nur geringem zeitlichem Benutzeraufwand den Animationspfad aus den reinen polygonalen dreidimensionalen Daten eines Transportsystems automatisch zu rekonstruieren.

Gathering Anonymous, Oblivious Robots on a Grid - Fischer, Matthias; Jung, Daniel; Meyer auf der Heide, Friedhelm (Algorithms for Sensor Systems - 13th International Symposium on Algorithms and Experiments for Wireless Sensor Networks, ALGOSENSORS)

A Communication-Efficient Distributed Data Structure for Top-k and k-Select Queries - Biermeier, Felix; Feldkord, Björn; Malatyali, Manuel; Meyer auf der Heide, Friedhelm (Proceedings of the 15th Workshop on Approximation and Online Algorithms (WAOA))

A Continuous Strategy for Collisionless Gathering - Podlipyan, Pavel; Li, Shouwei; Markarian, Christine; Meyer auf der Heide, Friedhelm (Proceedings of the 13th International Symposium on Algorithms and Experiments for Wireless Networks (ALGOSENSORS))

An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap - Wahby, Mostafa; Hofstadler, Daniel Nicolas; Heinrich, Mary Katherine; Zahadat, Payam; Hamann, Heiko (Proc. of the 10th International Conference on Self-Adaptive and Self-Organizing Systems)
The self-organizing bio-hybrid collaboration ofrobots and natural plants allows for a variety of interestingapplications. As an example we investigate how robots can beused to control the growth and motion of a natural plant, using LEDs to provide stimuli. We follow an evolutionaryrobotics approach where task performance is determined bymonitoring the plant's reaction. First, we do initial plantexperiments with simple, predetermined controllers. Then weuse image sampling data as a model of the dynamics ofthe plant tip xy position. Second, we use this approach toevolve robot controllers in simulation. The task is to makethe plant approach three predetermined, distinct points in anxy-plane. Finally, we test the evolved controllers in real plantexperiments and find that we cross the reality gap successfully. We shortly describe how we have extended from plant tipto many points on the plant, for a model of the plant stemdynamics. Future work will extend to two-axes image samplingfor a 3-d approach.

Self-Organized Construction with Continuous Building Material: Higher Flexibility Based on Braided Structures - Heinrich, Mary Katherine; Wahby, Mostafa; Divband Soorati, Mohammad; Hofstadler, Daniel Nicolas; Zahadat, Payam; Ayres, Phil; Stoy, Kasper; Hamann, Heiko (Proc. of the 1st International Workshop on Self-Organising Construction (SOCO))

Hybrid Societies: Challenges and Perspectives in the Design of Collective Behavior in Self-organizing Systems - Hamann, Heiko; Khaluf, Yara; Botev, Jean; Divband Soorati, Mohammad; Ferrante, Eliseo; Kosak, Oliver; Montanier, Jean-Marc; Mostaghim, Sanaz; Redpath, Richard; Timmis, Jon; Veenstra, Frank; Wahby, Mostafa; et al. (Frontiers in Robotics and AI)

Robot Self-Assembly as Adaptive Growth Process: Collective Selection of Seed Position and Self-Organizing Tree-Structures - Hamann, Heiko; Divband Soorati, Mohammad (IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016))

Collective Decision with 100 Kilobots: Speed vs Accuracy in Binary Discrimination Problems - Dorigo, Marco; Hamann, Heiko; Valentini, Gabriele; Ferrante, Eliseo (Journal of Autonomous Agents and Multi-Agent Systems)

Existence and Properties of Pure Nash Equilibria in Budget Games - Drees, Maximilian

Population Coding: A New Design Paradigm for Embodied Distributed Systems - Hamann, Heiko; Valentini, Gabriele; Dorigo, Marco (10th Int. Conf. on Swarm Intelligence, ANTS 2016)

Robot Gardens: An Augmented Reality Prototype for Plant-Robot Biohybrid Systems - von Mammen, Sebastian; Hamann, Heiko; Heider, Michael (ACM Symposium on Virtual Reality Software and Technology (VRST))

Inspiration-Triggered Search: Towards Higher Complexities by Mimicking Creative Processes - Rybář, Milan; Hamann, Heiko (Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2016))

On the Definition of Self-organizing Systems: Relevance of Positive/Negative Feedback and Fluctuations - Khaluf, Yara; Hamann, Heiko (ANTS 2016)

Collective Perception of Environmental Features in a Robot Swarm - Valentini, Gabriele; Brambilla, Davide; Hamann, Heiko; Dorigo, Marco (10th Int. Conf. on Swarm Intelligence, ANTS 2016)

Congestion Games with Mixed Objectives - Leder, Lennart

Churn- and DoS-resistant Overlay Networks Based on Network Reconfiguration - Drees, Maximilian; Gmyr, Robert; Scheideler, Christian (Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA))
We present three robust overlay networks: First, we present a network that organizes the nodes into an expander and is resistant to even massive adversarial churn. Second, we develop a network based on the hypercube that maintains connectivity under adversarial DoS-attacks. For the DoS-attacks we use the notion of a Omega(log log n)-late adversary which only has access to topological information that is at least Omega(log log n) rounds old. Finally, we develop a network that combines both churn- and DoS-resistance. The networks gain their robustness through constant network reconfiguration, i.e., the topology of the networks changes constantly. Our reconguration algorithms are based on node sampling primitives for expanders and hypercubes that allow each node to sample a logarithmic number of nodes uniformly at random in O(log log n) communication rounds. These primitives are specific to overlay networks and their optimal runtime represents an exponential improvement over known techniques. Our results have a wide range of applications, for example in the area of scalable and robust peer-to-peer systems.

The Game of Reciprocation Habits - Polevoy, Gleb; de Weerdt, M.M.; Jonker, C.M. (Proceedings of the 2016 European Conference on Artificial Intelligence)
Keywords: agents; action; repeated reciprocation; fixed; floating; network; Nash equilibrium; social welfare; price of anarchy; price of stability; convex combination

The Convergence of Reciprocation - Polevoy, Gleb; de Weerdt, Mathijs; Jonker, Catholijn (Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems)
Keywords: agent's influence; behavior; convergence; perron-frobenius; reciprocal interaction; repeated reciprocation

On the Parameterized Parallel Complexity and the Vertex Cover Problem - Abu-Khzam, Faisal N.; Li, Shouwei; Markarian, Christine; Meyer auf der Heide, Friedhelm; Podlipyan, Pavel (Proceedings of the 10th International Conference on Combinatorial Optimization and Applications (COCOA))
Efficiently parallelizable parameterized problems have been classified as being either in the class FPP (fixed-parameter parallelizable) or the class PNC (parameterized analog of NC), which contains FPP as a subclass. In this paper, we propose a more restrictive class of parallelizable parameterized problems called fixed-parameter parallel-tractable (FPPT). For a problem to be in FPPT, it should possess an efficient parallel algorithm not only from a theoretical standpoint but in practice as well. The primary distinction between FPPT and FPP is the parallel processor utilization, which is bounded by a polynomial function in the case of FPPT. We initiate the study of FPPT with the well-known k-vertex cover problem. In particular, we present a parallel algorithm that outperforms the best known parallel algorithm for this problem: using O(m) instead of O(n2) parallel processors, the running time improves from 4logn+O(kk) to O(k⋅log3n), where m is the number of edges, n is the number of vertices of the input graph, and k is an upper bound of the size of the sought vertex cover. We also note that a few P-complete problems fall into FPPT including the monotone circuit value problem (MCV) when the underlying graphs are bounded by a constant Euler genus.

Introduction to the Special Issue on SPAA 2014 (Transactions on Parallel Computing (TOPC))

Cost-efficient Scheduling on Machines from the Cloud - Mäcker, Alexander; Malatyali, Manuel; Meyer auf der Heide, Friedhelm; Riechers, Sören (Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA))
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 $β$ 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 $β$. While for $β series = LNCS

Congestion Games with Mixed Objectives - Feldotto, Matthias; Leder, Lennart; Skopalik, Alexander (Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA))
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.

Parallelisierung von Algorithmen zur IR-Luftbildanalyse von Laubholzmischbeständen zur Verifizierung der Ausbreitung von Eichenkomplexschäden - Bülling, Jonas

Price-Based Allocation Games - Koepe, Jörn

Friendship Processes in Network Creation Games - Kutzias, Damian

Routing Algorithms on Delayed Networks for Disaster Management Support - Schaefer, Johannes Sebastian

Asymptotically Optimal Gathering on a Grid - Cord-Landwehr, Andreas; Fischer, Matthias; Jung, Daniel; Meyer auf der Heide, Friedhelm (arXiv:1602.03303)
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 $2× 2$-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 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 $\mathcal{O}(n^2)$.

Patterns for Constructing Mutation Operators: Limiting the Search Space in a Software Engineering Application - Kühne, Thomas; Hamann, Heiko; Arifulina, Svetlana; Engels, Gregor (Proceedings of the 19th European Conference on Genetic Programming (EuroGP 2016))
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.

Über die Rolle von Informationen in Verkehrsnetzwerken - Handirk, Tobias

Selfish Network Creation - On Variants of Network Creation Games - Cord-Landwehr, Andreas

Scheduling with Interjob Communication on Parallel Processors - König, Jürgen; Mäcker, Alexander; Meyer auf der Heide, Friedhelm; Riechers, Sören (Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA))
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.

Routing Games With Progressive Filling - Harks, Tobias; Höfer, Martin; Schewior, Kevin; Skopalik, Alexander (IEEE/ACM Transactions on Networking)
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.

Strategic Online Facility Location - Drees, Maximilian; Feldkord, Björn; Skopalik, Alexander (Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA))
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).

Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc)

Algorithm Engineering Aspects of Real-Time Rendering Algorithms - Fischer, Matthias; Jähn, Claudius; Meyer auf der Heide, Friedhelm; Petring, Ralf (Algorithm Engineering)
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.

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 (Algorithms for Sensor Systems, Proceedings of the 12th International Symposium on Algorithms and Experiments for Wireless Sensor Networks (ALGOSENSORS))

Asymptotically Optimal Gathering on a Grid - Cord-Landwehr, Andreas; Fischer, Matthias; Jung, Daniel; Meyer auf der Heide, Friedhelm (Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA))
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).

Gathering a Closed Chain of Robots on a Grid - Abshoff, Sebastian; Cord-Landwehr, Andreas; Fischer, Matthias; Jung, Daniel; Meyer auf der Heide, Friedhelm (Proceedings of the 30th International Parallel and Distributed Processing Symposium (IPDPS))
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.

On Competitive Algorithms for Approximations of Top-k-Position Monitoring of Distributed Streams - Macker, Alexander; Malatyali, Manuel; Meyer auf der Heide, Friedhelm (2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS))

Cost-efficient Scheduling on Machines from the Cloud - Mäcker, Alexander; Malatyali, Manuel; Meyer auf der Heide, Friedhelm; Riechers, Sören (arXiv:1609.01184)
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 $β$ 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 $β$. While for $β < s$ no finite competitiveness is possible, our main result is an $O(\frac{c}{ε} + \frac{1}{ε^3})$-competitive online algorithm for $β = (1+ε)s$ with $\frac{1}{s} ≤ ε ≤ 1$, 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 $Ω(\frac{c}{ε})$.

Towards the price of leasing online - Abshoff, Sebastian; Kling, Peter; Markarian, Christine; Meyer auf der Heide, Friedhelm; Pietrzyk, Peter (Journal of Combinatorial Optimization)
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).

The Monotone Circuit Value Problem with Bounded Genus Is in NC - Abu-Khzam, Faisal N.; Li, Shouwei; Markarian, Christine; Meyer auf der Heide, Friedhelm; Podlipyan, Pavel (Proceedings of the 22nd International Conference on Computing and Combinatorics (COCOON))
We present an efficient parallel algorithm for the general Monotone Circuit Value Problem (MCVP) with n gates and an underlying graph of bounded genus k. Our algorithm generalizes a recent result by Limaye et al. who showed that MCVP with toroidal embedding (genus 1) is in NC when the input contains a toroidal embedding of the circuit. In addition to extending this result from genus 1 to any bounded genus k, and unlike the work reported by Limaye et al., we do not require a precomputed embedding to be given. Most importantly, our results imply that given a P-complete problem, it is possible to find an algorithm that makes the problem fall into NC by fixing one or more parameters. Hence, we deduce the interesting analogy: Fixed Parameter Parallelizable (FPP) is with respect to P-complete what Fixed Parameter Tractable (FPT) is with respect to NP-complete. Similar work that uses treewidth as parameter was also presented by Elberfeld et al. in [6].

Systematic evaluation of peer-to-peer systems using PeerfactSim.KOM - Feldotto, Matthias; Graffi, Kalman (Concurrency and Computation: Practice and Experience)
Comparative evaluations of peer-to-peer protocols through simulations are a viable approach to judge the performance and costs of the individual protocols in large-scale networks. In order to support this work, we present the peer-to-peer system simulator PeerfactSim.KOM, which we extended over the last years. PeerfactSim.KOM comes with an extensive layer model to support various facets and protocols of peer-to-peer networking. In this article, we describe PeerfactSim.KOM and show how it can be used for detailed measurements of large-scale peer-to-peer networks. We enhanced PeerfactSim.KOM with a fine-grained analyzer concept, with exhaustive automated measurements and gnuplot generators as well as a coordination control to evaluate sets of experiment setups in parallel. Thus, by configuring all experiments and protocols only once and starting the simulator, all desired measurements are performed, analyzed, evaluated, and combined, resulting in a holistic environment for the comparative evaluation of peer-to-peer systems. An immediate comparison of different configurations and overlays under different aspects is possible directly after the execution without any manual post-processing.

Solving the aggregated bandits problem - Pfannschmidt, Karlson

On the Tradeoff between Hardware Protection and Optimization Success: A Case Study in Onboard Evolutionary Robotics for Autonomous Parallel Parking - Wahby, Mostafa; Hamann, Heiko (Applications of Evolutionary Computation (EvoApplications 2015))

Flora Robotica - Mixed Societies of Symbiotic Robot-Plant Bio-Hybrids - Hamann, Heiko; Wahby, Mostafa; Schmickl, Thomas; Zahadat, Payam; Hofstadler, Daniel; Stoy, Kasper; Risi, Sebastian; Faina, Andres; Veenstra, Frank; Kernbach, Serge; Kuksin, Igor; Kernbach, Olga; et al. (Proceedings of the 2015 IEEE Symposium on Artificial Life (IEEE ALIFE'15))
Besides the life-as-it-could-be driver of artificial life research there is also the concept of extending natural life by creating hybrids or mixed societies that are built from natural and artificial components. In this paper we motivate and present the research program of the project flora robotica. Our objective is to develop and to investigate closely linked symbiotic relationships between robots and natural plants and to explore the potentials of a plant-robot society able to produce architectural artifacts and living spaces. These robot-plant bio-hybrids create synergies that allow for new functions of plants and robots. They also create novel design opportunities for an architecture that fuses the design and construction phase. The bio-hybrid is an example of mixed societies between 'hard' artificial and 'wet' natural life, which enables an interaction between natural and artificial ecologies. They form an embodied, self-organizing, and distributed cognitive system which is supposed to grow and develop over long periods of time resulting in the creation of meaningful architectural structures. A key idea is to assign equal roles to robots and plants in order to create a highly integrated, symbiotic system. Besides the gain of knowledge, this project has the objective to create a bio-hybrid system with a defined function and application -- growing architectural artifacts.

Lessons from Speciation Dynamics: How to Generate Selective Pressure Towards Diversity - Hamann, Heiko (Artificial Life)
Recent approaches in evolutionary robotics (ER) propose to generate behavioral diversity in order to evolve desired behaviors more easily. These approaches require the definition of a behavioral distance, which often includes task-specific features and hence a priori knowledge. Alternative methods, which do not explicitly force selective pressure towards diversity (SPTD) but still generate it, are known from the field of artificial life, such as in artificial ecologies (AEs). In this study, we investigate how SPTD is generated without task-specific behavioral features or other forms of a priori knowledge and detect how methods of generating SPTD can be transferred from the domain of AE to ER. A promising finding is that in both types of systems, in systems from ER that generate behavioral diversity and also in the investigated speciation model, selective pressure is generated towards unpopulated regions of search space. In a simple case study we investigate the practical implications of these findings and point to options for transferring the idea of self-organizing SPTD in AEs to the domain of ER.

Revisiting BEECLUST: Aggregation of Swarm Robots with Adaptiveness to Different Light Settings - Wahby, Mostafa; Weinhold, Alexander; Hamann, Heiko (Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS))
Aggregation is a crucial task in swarm robotics to ensure cooperation. We investigate the task of aggregation on an area specified indirectly by certain environmental features, here it is a light distribution. We extend the original BEECLUST algorithm, that implements an aggregation behavior, to an adaptive variant that automatically adapts to any light conditions. We compare these two control algorithms in a number of swarm robot experiments with different light conditions. The improved, adaptive variant is found to be significantly better in the tested setup.

Evolution of Controllers for Robot-Plant Bio-Hybdrids: A Simple Case Study Using a Model of Plant Growth and Motion - Wahby, Mostafa; Divband Soorati, Mohammad; von Mammen, Sebastian; Hamann, Heiko (Proceedings. 25. Computational Intelligence Workshop)

The Effect of Fitness Function Design on Performance in Evolutionary Robotics: The Influence of a Priori Knowledge - Hamann, Heiko; Divband Soorati, Mohammad (Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015))
Fitness function design is known to be a critical feature of the evolutionary-robotics approach. Potentially, the complexity of evolving a successful controller for a given task can be reduced by integrating a priori knowledge into the fitness function which complicates the comparability of studies in evolutionary robotics. Still, there are only few publications that study the actual effects of different fitness functions on the robot's performance. In this paper, we follow the fitness function classification of Nelson et al. (2009) and investigate a selection of four classes of fitness functions that require different degrees of a priori knowledge. The robot controllers are evolved in simulation using NEAT and we investigate different tasks including obstacle avoidance and (periodic) goal homing. The best evolved controllers were then post-evaluated by examining their potential for adaptation, determining their convergence rates, and using cross-comparisons based on the different fitness function classes. The results confirm that the integration of more a priori knowledge can simplify a task and show that more attention should be paid to fitness function classes when comparing different studies.

Evolving Collective Behaviors With Diverse But Predictable Sensor States - Hamann, Heiko; Schmickl, Thomas; Zahadat, Payam (13th European Conference on Artificial Life (ECAL 2015))

Probabilistic Modeling of Swarming Systems - Hamann, Heiko; Correll, Nikolaus; Kacprzyk, Janusz; Pedrycz, Witold (Springer Handbook of Computational Intelligence)

Dependability in Swarm Robotics: Error Detection and Correction - Ding, Hongli; Hamann, Heiko (First International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM 2015))

Potential of Heterogeneity in Collective Behaviors: A Case Study on Heterogeneous Swarms - Hamann, Heiko; Schmickl, Thomas; Kengyel, Daniela; Zahadat, Payam; Radspieler, Gerald; Wotawa, Franz (Principles and Practice of Multi-Agent Systems (PRIMA 2015))

Time-variant feedback processes in collective decision-making systems: influence and effect of dynamic neighborhood sizes - Valentini, Gabriele; Hamann, Heiko (Swarm Intelligence)