TY - THES AB - Web computing is a variant of parallel computing where the idle times of PCs donated by worldwide distributed users are employed to execute parallel programs. In this thesis we consider a web computing variant with two important properties: First, we support the execution of coupled, massively parallel algorithms (rather than distributed data processing). And second, we organize the system in peer-to-peer fashion. We present the Paderborn University BSP-based Web Computing (PUB-Web) library, which supports the execution of parallel programs in the bulk-synchronous style (BSP) in such a web computing setting. In this thesis, we focus on important technical and algorithmic aspects, in particular: In order to schedule processes with respect to the currently available computing power, which continually changes in an unpredictable fashion, we need intelligent load balancing algorithms and -- as a basic precondition -- the technical ability to migrate threads at runtime. To achieve the latter in a way suitable for production use, compatible with recent Java versions, available for all important platforms, and easy-to-use for developers, we develop the PadMig thread migration and checkpointing library. In order to tackle the distributed load balancing problem, we present an algorithm based on Distributed Heterogeneous Hash-Tables. In order to judge the quality of the schedules produced, we perform extensive experiments to compare several variants of the DHHT-based load balancer with the well- established Work Stealing algorithm, using realistic input data obtained by profiling the utilization of several hundred PCs for a period of several months. Beside the available computing power, we finally also consider the network bandwidth as a secondary criterion for load balancing. For this purpose, we cluster the PUB-Web network according to bandwidth, employing a novel, fault-tolerant, adaptive, and scaling distributed clustering algorithm called DiDiC. In order to judge the quality of the clusterings produces by DiDiC, we experimentally compare it to the well-established MCL algorithm using a simulator. AU - Gehweiler, Joachim ID - 18976 SN - 978-3-942647-17-5 TI - Peer-to-Peer Based Parallel Web Computing VL - 298 ER - TY - CONF AU - Briest, Patrick AU - Raupach, Christoph ID - 19026 SN - 9781450307437 T2 - Proceedings of the 23rd ACM symposium on Parallelism in algorithms and architectures - SPAA '11 TI - The car sharing problem ER - TY - THES AU - Effert, Sascha ID - 19040 TI - Verfahren zur redundanten Datenplatzierung in skalierbaren Speichersystemen ER - TY - JOUR AB - This paper deals with the design of efficiently computable incentive-compatible mechanisms for combinatorial optimization problems with single-minded agents each possibly having multiple private parameters. We focus on approximation algorithms for NP-hard mechanism design problems. These algorithms need to satisfy certain monotonicity properties to ensure truthfulness. Since most of the known approximation techniques do not fulfill these properties, we study alternative techniques. Our first contribution is a quite general method to transform a pseudopolynomial algorithm into a monotone fully polynomial time approximation scheme (FPTAS). This can be applied to various problems like, e.g., knapsack, constrained shortest path, or job scheduling with deadlines. For example, the monotone FPTAS for the knapsack problem gives a very efficient, truthful mechanism for single-minded multiunit auctions. The best previous result for such auctions was a 2-appro-xi-ma-tion. In addition, we present a monotone PTAS for the generalized assignment problem with any constant number of private parameters per agent. The most efficient way to solve packing integer programs (PIPs) is linear programming–based randomized rounding, which also is in general not monotone. We show that primal-dual greedy algorithms achieve almost the same approximation ratios for PIPs as randomized rounding. The advantage is that these algorithms are inherently monotone. This way, we can significantly improve the approximation ratios of truthful mechanisms for various fundamental mechanism design problems like single-minded combinatorial auctions (CAs), unsplittable flow routing, and multicast routing. Our primal-dual approximation algorithms can also be used for the winner determination in CAs with general bidders specifying their bids through an oracle. AU - Briest, Patrick AU - Krysta, Piotr AU - Vöcking, Berthold ID - 23739 JF - SIAM Journal on Computing SN - 0097-5397 TI - Approximation Techniques for Utilitarian Mechanism Design ER - TY - JOUR AB - We investigate nonparametric multiproduct pricing problems, in which we want to find revenue maximizing prices for products $\mathcal{P}$ based on a set of customer samples $\mathcal{C}$. We mostly focus on the unit-demand case, in which products constitute strict substitutes and each customer aims to purchase a single product. In this setting a customer sample consists of a number of nonzero values for different products and possibly an additional product ranking. Once prices are fixed, each customer chooses to buy one of the products she can afford based on some predefined selection rule. We distinguish between the min-buying, max-buying, and rank-buying models. Some of our results also extend to single-minded pricing, in which case products are strict complements and every customer seeks to buy a single set of products, which she purchases if the sum of prices is below her valuation for that set. For the min-buying model we show that the revenue maximization problem is not approximable within factor $\mathcal{O}(\log^{\varepsilon}|\mathcal{C}|)$ for some constant $\varepsilon>0$, unless $\mathrm{NP}\subseteq\mathrm{DTIME}(n^{\mathcal{O}(\log\log n)})$, thereby almost closing the gap between the known algorithmic results and previous lower bounds. We also prove inapproximability within $\mathcal{O}(\ell^{\varepsilon})$, $\ell$ being an upper bound on the number of nonzero values per customer, and $\mathcal{O}(|\mathcal{P}|^{\varepsilon})$ under slightly stronger assumptions and provide matching upper bounds. Surprisingly, these hardness results hold even if a price ladder constraint, i.e., a predefined order on the prices of all products, is given. Without the price ladder constraint we obtain similar hardness results for the special case of uniform valuations, i.e., the case that every customer has identical values for all the products she is interested in, assuming specific hardness of the balanced bipartite independent set problem in constant degree graphs or hardness of refuting random 3CNF formulas. Introducing a slightly more general problem definition in which customers are given as an explicit probability distribution, we obtain inapproximability within $\mathcal{O}(|\mathcal{P}|^{\varepsilon})$ assuming $\mathrm{NP}\nsubseteq\bigcap_{\delta>0}\mathrm{BPTIME}(2^{\mathcal{O}(n^{\delta})})$. These results apply to single-minded pricing as well. For the max-buying model a polynomial-time approximation scheme exists if a price ladder is given. We give a matching lower bound by proving strong NP-hardness. Assuming limited product supply, we analyze a generic local search algorithm and prove that it is 2-approximate. Finally, we discuss implications for the rank-buying model. AU - Briest, Patrick AU - Krysta, Piotr ID - 23740 JF - SIAM Journal on Computing SN - 0097-5397 TI - Buying Cheap Is Expensive: Approximability of Combinatorial Pricing Problems ER - TY - CHAP AU - Cord-Landwehr, Andreas AU - Degener, Bastian AU - Fischer, Matthias AU - Hüllmann, Martina AU - Kempkes, Barbara AU - Klaas, Alexander AU - Kling, Peter AU - Kurras, Sven AU - Märtens, Marcus AU - auf der Heide, Friedhelm Meyer AU - Raupach, Christoph AU - Swierkot, Kamil AU - Warner, Daniel AU - Weddemann, Christoph AU - Wonisch, Daniel ID - 20709 SN - 0302-9743 T2 - SOFSEM 2011: Theory and Practice of Computer Science TI - Collisionless Gathering of Robots with an Extent ER - TY - CHAP AU - Cord-Landwehr, Andreas AU - Degener, Bastian AU - Fischer, Matthias AU - Hüllmann, Martina AU - Kempkes, Barbara AU - Klaas, Alexander AU - Kling, Peter AU - Kurras, Sven AU - Märtens, Marcus AU - Meyer auf der Heide, Friedhelm AU - Raupach, Christoph AU - Swierkot, Kamil AU - Warner, Daniel AU - Weddemann, Christoph AU - Wonisch, Daniel ID - 20710 SN - 0302-9743 T2 - Automata, Languages and Programming TI - A New Approach for Analyzing Convergence Algorithms for Mobile Robots ER - TY - CONF AU - Renken, Hendrik AU - Laroque, Christoph AU - Fischer, Matthias ID - 18193 T2 - Proceedings of The 25th European Simulation and Modelling Conference - ESM2011 TI - An Easy Extendable Modeling Framework for Discrete Event Simulation Models and their Visualization ER - TY - GEN AB - We present a parallel rendering system for PC-Clusters to visualize large 3D scenes. One single visualization node, equipped with a high-end graphics adapter, is supported by a group of backend nodes with weak graphics performance. The objects of the scene are distributed among these backend nodes, they serve two purposes: First, they provide an out-of-core memory system for the visualization node. Second, they assist the visualization node's rendering by performing visibility calculations and only sending visible objects to the visualization node. In order to obtain fast rendering with our system, we have to distribute the objects among the backend nodes in a way that does not only guarantee an even distribution of the objects, but also an even distribution of the visibility calculations and the amount of data send to the visualization node. We identify necessary properties of the distribution and argue that a random distribution is a good candidate. Further, in order to reduce the number of objects sent to the visualization node per frame, we employ an approximate hierarchical occlusion culling in each backend node. For this, they are equipped, in addition to the objects assigned to them, with simplified versions of the other objects of the 3D scene. The visualization node is equipped with 512 MiB video memory and supported by 15 backend nodes. This system is able to render a approx. 350 million polygons (approx. 8.5 GiB) large aircraft model between 20 - 30 fps and thus allows a walkthrough in real-time. AU - Suess, Tim AU - Koch, Clemens AU - Jähn, Claudius AU - Fischer, Matthias AU - Meyer auf der Heide, Friedhelm ID - 18194 TI - Parallel Out-of-Core Occlusion Culling ER - TY - CONF AU - Vöcking, Berthold AU - Hoefer, Martin AU - Skopalik, Alexander AU - Penn, Michal AU - Polukarov, Maria ID - 18568 T2 - {IJCAI} 2011, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, TI - Considerate Equilibrium ER -