On Greedy Routing in Degree-bounded Graphs over d-Dimensional Internet Coordinate Embeddings - Autenrieth, Marcus; Frey, Hannes (Proceedings of the Conference on Networked Systems (NetSys))
In this paper we will introduce a new d-dimensional graph for constructing geometric application layer overlay net-works. Our approach will use internet coordinates, embedded using the L∞ -metric. After describing the graph structure, we will show how it limits maintenance overhead by bounding each node’s out-degree and how it supports greedy routing using one-hop neighbourhood information in each routing step. We will further show that greedy routing can always compute a path in our graph and we will also prove that in each forwarding step the next hop is closer to the destination than the current node.

Meta-data based Search in Structured Peer-to-Peer Networks - Jayesh Parekh, Chintan

MapReduce in Software Defined Networks - Splietker, Malte

Subsidiarity between economic freedom and harmonized regulation: is there an optimal degree of European integration? - Gilroy, Bernard Michael; Schreckenberg, Heike; Seiler, Volker (Federal Governance)

Technologiestandort Deutschland und internationale Wissensspillover. - Gilroy, Bernard Michael; Lukas, Elmar; Heimann, Christian (Jahrbücher für Nationalokonomie 6 Statistik)

Basic income and labour supply: The German case - Gilroy, Bernard Michael; Heimann, Anastasia; Schopf, Mark (Basic Income Studies)

Ist Fairer Handel Wirklich Fair? - Gilroy, Bernard Michael; Nguyen, Birke Thuy Duong (WiSt-Wirtschaftswissenschaftliches Studium)

Water as an alternative asset - Gilroy, Bernard Michael; Schreckenberg, Heike; Seiler, Volker

Lösungsverfahren für das many-to-one Matching Problem - Herzog, Elvira

Locally Self-Adjusting Tree Networks - Avin, Chen; Häupler, Bernhard; Lotker, Zvi; Scheideler, Christian; Schmid, Stefan (Proceedings of the 27th IEEE International Parallel and Distributed Processing Symposium (IPDPS))
This paper initiates the study of self-adjusting networks (or distributed data structures) whose topologies dynamically adapt to a communication pattern $σ$. We present a fully decentralized self-adjusting solution called SplayNet. A SplayNet is a distributed generalization of the classic splay tree concept. It ensures short paths (which can be found using local-greedy routing) between communication partners while minimizing topological rearrangements. We derive an upper bound for the amortized communication cost of a SplayNet based on empirical entropies of $σ$, and show that SplayNets have several interesting convergence properties. For instance, SplayNets features a provable online optimality under special requests scenarios. We also investigate the optimal static network and prove different lower bounds for the average communication cost based on graph cuts and on the empirical entropy of the communication pattern $σ$. From these lower bounds it follows, e.g., that SplayNets are optimal in scenarios where the requests follow a product distribution as well. Finally, this paper shows that in contrast to the Minimum Linear Arrangement problem which is generally NP-hard, the optimal static tree network can be computed in polynomial time for any guest graph, despite the exponentially large graph family. We complement our formal analysis with a small simulation study on a Facebook graph.

Local and Online Algorithms for Facility Location - Pietrzyk, Peter
Diese Arbeit beschäftigt sich mit dem Facility Location Problem. Dies ist ein Optimierungsproblem, bei dem festgelegt werden muss an welchen Positionen Ressourcen zur Verfügung gestellt werden, so dass diese von Nutzern gut erreicht werden können. Es sollen dabei Kosten minimiert werden, die zum einen durch Bereitstellung von Ressourcen und zum anderen durch Verbindungskosten zwischen Nutzern und Ressourcen entstehen. Die Schwierigkeit des Problems liegt darin, dass man einerseits möglichst wenige Ressourcen zur Verfügung stellen möchte, andererseits dafür sorgen muss, dass sich Nutzer nicht all zu weit weg von Ressourcen befinden. Dies würde nämlich hohe Verbindungskosten nach sich ziehen. Das Facility Location Problem wurde bereits sehr intensiv in vielen unterschiedlichen Varianten untersucht. In dieser Arbeit werden drei Varianten des Problems modelliert und neue Algorithmen für sie entwickelt und bezüglich ihres Approximationsfaktors und ihrer Laufzeit analysiert. Jede dieser drei untersuchten Varianten hat einen besonderen Schwerpunkt. Bei der ersten Varianten handelt es sich um ein Online Problem, da hier die Eingabe nicht von Anfang an bekannt ist, sondern Schritt für Schritt enthüllt wird. Die Schwierigkeit hierbei besteht darin unwiderrufliche Entscheidungen treffen zu müssen ohne dabei die Zukunft zu kennen und trotzdem eine zu jeder Zeit gute Lösung angeben zu können. Der Schwerpunkt der zweiten Variante liegt auf Lokalität, die z.B. in Sensornetzwerken von großer Bedeutung ist. Hier soll eine Lösung verteilt und nur mit Hilfe von lokalen Information berechnet werden. Schließlich beschäftigt sich die dritte Variante mit einer verteilten Berechnung, bei welcher nur eine stark beschränkte Datenmenge verschickt werden darf und dabei trotzdem ein sehr guter Approximationsfaktor erreicht werden muss. Die bei der Analyse der Approximationsfaktoren bzw. der Kompetitivität verwendeten Techniken basieren zum großen Teil auf Abschätzung der primalen Lösung mit Hilfe einer Lösung des zugehörigen dualen Problems. Für die Modellierung von Lokalität wird das weitverbreitete LOCAL Modell verwendet. In diesem Modell werden für die Algorithmen subpolynomielle obere Laufzeitschranken gezeigt.

The influence of socio-demographic variables on customer satisfaction and loyalty in the private banking industry - Seiler, Volker; Rudolf, Markus; Krume, Tim (International Journal of Bank Marketing)

Cooperative Transfer Price Negotiations under Incomplete Information - Brangewitz, Sonja; Haake, Claus-Jochen
In this paper, we analyze a model in which two divisions negotiate over an intrafirm transfer price for an intermediate product. Formally, we consider bargaining problems under incomplete information, since the upstream division’s (seller's) costs and downstream division's (buyer's) revenues are supposed to be private information. Assuming two possible types for buyer and seller each, we first establish that the bargaining problem is regular, regardless whether incentive and/or efficiency constraints are imposed. This allows us to apply the generalized Nash bargaining solution to determine transfer payments and transfer probabilities. Furthermore, we derive general properties of this solution for the transfer pricing problem and compare the model developed here with the existing literature for negotiated transfer pricing under incomplete information. In particular, we focus on the models presented in Wagenhofer (1994).
Keywords: Transfer Pricing; Negotiation; Generalized Nash Bargaining Solution; Incomplete Information

Learning Service Recommendations - Jungmann, Alexander; Kleinjohann, Bernd; Kleinjohann, Elisabeth (International Journal of Business Process Integration and Management)
The as a service paradigm reflects the fundamental idea of providing basic coherent functionality in terms of components that can be utilised on demand. These so-called services may also be interconnected in order to provide more complex functionality. Automation of this service composition process is indeed a formidable challenge. In our work, we are addressing this challenge by decomposing service composition into sequential decision making steps. Each step is supported by a recommendation mechanism. If composition requests recur over time and if evaluations of composition results are fed back, a proper recommendation strategy can evolve over time through learning from experience. In this paper, we describe our approach of modelling this service composition and recommendation process as Markov decision process and of solving it by means of reinforcement learning. A case study serves as proof of concept.

Learning Recommendation System for Automated Service Composition - Jungmann, Alexander; Kleinjohann, Bernd (Proceedings of the 10th IEEE International Conference on Services Computing (SCC))
The as a Service paradigm reflects the fundamental idea of providing basic coherent functionality in terms of components that can be utilized on demand. These so-called services may also be interconnected in order to provide more complex functionality. Automation of this service composition process is indeed a formidable challenge. In our work, we are addressing this challenge by decomposing service composition into sequential decision making steps. Each step is supported by a recommendation mechanism. If composition requests recur over time and if evaluations of composition results are fed back, a proper recommendation strategy can evolve over time through learning from experience. In this paper, we describe our general idea of modeling this service composition and recommendation process as Markov Decision Process and of solving it by means of Reinforcement Learning. A case study serves as proof of concept.

Knowledge-Based Verification of Service Compositions - An SMT approach - Walther, Sven; Wehrheim, Heike (Proceedings of the 18th IEEE International Conference on Engineering of Complex Computer Systems (ICECCS))
In the Semantic (Web) Services area, services are considered black boxes with a semantic description of their interfaces as to allow for precise service selection and conﬁguration. The semantic description is usually grounded on domain-speciﬁc concepts as modeled in ontologies. This accounts for types used in service signatures, but also predicates occurring in preconditions and effects of services. Ontologies, in particular those enhanced with rules, capture the knowledge of domain experts on properties of and relations between domain concepts. In this paper, we present a veriﬁcation technique for service compositions which makes use of this domain knowledge. We consider a service composition to be an assembly of services of which we just know signatures, preconditions, and effects. We aim at proving that a composition satisﬁes a (user-deﬁned) requirement, speciﬁed in terms of guaranteed preconditions and required postconditions. As an underlying veriﬁcation engine we use an SMT solver. To take advantage of the domain knowledge (and often, to enable veriﬁcation at all), the knowledge is fed into the solver in the form of sorts, uninterpreted functions and in particular assertions as to enhance the solver’s reasoning capabilities. Thereby, we allow for deductions within a domain previously unknown to the solver. We exemplify our technique on a case study from the area of water network optimization software.

Company Valuation and Growth: Theory, Empirical Evidence and Practical Implementation Issues - Sievers, Sönke
Keywords: Unternehmensbewertung; Unternehmenswachstum; Return on Investment Unternehmensbewertung; Investition; Steuervergünstigung

Klassifizierung unterschiedlicher Ansätze zum Matching von Services - Petrausch, Vanessa

IRIS: A Robust Information System Against Insider DoS-Attacks - Eikel, Martina; Scheideler, Christian (Proceedings of the 25th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA))
In this work we present the first scalable distributed information system,i.e., a system with low storage overhead, that is provably robust againstDenial-of-Service (DoS) attacks by a current insider. We allow acurrent insider to have complete knowledge about the information systemand to have the power to block any ε-fraction of its serversby a DoS-attack, where ε can be chosen up to a constant. The taskof the system is to serve any collection of lookup requests with at most oneper non-blocked server in an efficient way despite this attack. Previously,scalable solutions were only known for DoS-attacks of past insiders, where apast insider only has complete knowledge about some past time pointt_0 of the information system. Scheideler et al. (DISC 2007, SPAA 2009) showedthat in this case it is possible to design an information system so that anyinformation that was inserted or last updated after t_0 is safe against a DoS-attack. But their constructions would not work at all for a current insider. The key idea behindour IRIS system is to make extensive use of coding. More precisely, we presenttwo alternative distributed coding strategies with an at most logarithmicstorage overhead that can handle up to a constant fraction of blocked servers.

Incorporating feedback from application layer into routing and wavelength assignment algorithms - Wette, Philip; Karl, Holger (Proceedings of the 32nd IEEE International Conference on Computer Communications (INFOCOM))
Preemptive Routing and Wavelength Assignment (RWA) algorithms preempt established lightpaths in case not enough resources are available to set up a new lightpath in a Wavelength Division Multiplexing (WDM) network. The selection of lightpaths to be preempted relies on internal decisions of the RWA algorithm. Thus, if dedicated properties of the network topology are required by the applications running on the network, these requirements have to be known to the RWA algorithm.Otherwise it might happen that by preempting a particular lightpath these requirements are violated. If, however, these requirements include parametersknown only at the nodes running the application, the RWA algorithm cannot evaluate the requirements. For this reason an RWA algorithm is needed which incorporates feedback from the application layer in the preemption decisions.This work proposes a simple interface along with an algorithm for computing and selecting preemption candidates in case a lightpath cannot be established. We reason about the necessity of using information from the application layer in the RWA and present two example applications which benefit from this idea.