@inproceedings{25083, author = {{Jatzkowski, Jan and Kleinjohann, Bernd}}, booktitle = {{Mechatronics}}, location = {{Mai 2015}}, publisher = {{Elsevier}}, title = {{{Self-Reconfiguration of Real-Time Communication within Cyber-Physical Systems}}}, year = {{2015}}, } @misc{251, author = {{Pfannschmidt, Karlson}}, publisher = {{Universität Paderborn}}, title = {{{Solving the aggregated bandits problem}}}, year = {{2015}}, } @article{25107, abstract = {{On-the-fly composition of service-based software solutions is still a challenging task. Even more challenges emerge when facing automatic service composition in markets of composed services for end users. In this paper, we focus on the functional discrepancy between “what a user wants” specified in terms of a request and “what a user gets” when executing a composed service. To meet the challenge of functional discrepancy, we propose the combination of existing symbolic composition approaches with machine learning techniques. We developed a learning recommendation system that expands the capabilities of existing composition algorithms to facilitate adaptivity and consequently reduces functional discrepancy. As a representative of symbolic techniques, an Artificial Intelligence planning based approach produces solutions that are correct with respect to formal specifications. Our learning recommendation system supports the symbolic approach in decision-making. Reinforcement Learning techniques enable the recommendation system to adjust its recommendation strategy over time based on user ratings. We implemented the proposed functionality in terms of a prototypical composition framework. Preliminary results from experiments conducted in the image processing domain illustrate the benefit of combining both complementary techniques.}}, author = {{Jungmann, Alexander and Mohr, Felix}}, journal = {{Journal of Internet Services and Applications 6(1)}}, pages = {{1--18}}, title = {{{An approach towards adaptive service composition in markets of composed services}}}, year = {{2015}}, } @article{25108, abstract = {{Autonomous adaptation in self-adapting embedded real-time systems introduces novel risks as it may lead to unforeseen system behavior. An anomaly detection framework integrated in a real-time operating system can ease the identification of such suspicious novel behavior and, thereby, offers the potential to enhance the reliability of the considered self-x system. However, anomaly detection is based on knowledge about normal behavior. When dealing with self-reconfiguring applications, normal behavior changes. Hence, knowledge base requires adaptation or even re-construction at runtime. The stringent restrictions of real-time systems considering runtime and memory consumption make this task to a really challenging problem. We present our idea for online construction of application behavior knowledge that does not rely on training phase. The applications' behavior is defined by the application's system call invocations. For the knowledge base, we exploit suffix trees as they offer potentials to represent application behavior patterns and associated information in a compact manner. The online algorithm provided by suffix trees is a basis to construct the knowledge base with low computational effort. Anomaly detection and classification is integrated into the online construction method. New behavioral patterns do not unconditionally update the behavior knowledge base. They are evaluated in a context-related manner inspired by Danger Theory, a special discipline of artificial immune systems. Copyright © 2015 John Wiley & Sons, Ltd.}}, author = {{Rammig, Franz-Josef and Stahl, Katharina}}, journal = {{Concurrency and Computation: Practice and Experience }}, title = {{{Online behavior classification for anomaly detection in self-x real-time systems}}}, year = {{2015}}, } @article{25109, author = {{Sudhakar, Krishna and Zhao, Yuhong and Rammig, Franz-Josef}}, journal = {{Concurrency and Computation: Practice and Experience }}, title = {{{Efficient Integration of Online Model Checking into a Small-Footprint Real-Time Operating System}}}, year = {{2015}}, } @article{25110, author = {{Joy, M. tech. Mabel Mary and Rammig, Franz-Josef}}, journal = {{Int. J. of Embedded Systems}}, title = {{{A hybrid methodology to detect memory leaks in soft real time embedded systems software}}}, year = {{2015}}, } @article{25111, author = {{Khaluf, Yara and Birattari, Mauro and Rammig, Franz-Josef}}, journal = {{Springer Jounal Soft Computing }}, title = {{{Analysis of long-term swarm performance based on short-term experiments}}}, year = {{2015}}, } @inproceedings{252, abstract = {{Video streaming is in high demand by mobile users. In cellular networks, however, the unreliable wireless channel leads to two major problems. Poor channel states degrade video quality and interrupt the playback when a user cannot sufficiently fill its local playout buffer: buffer underruns occur. In contrast, good channel conditions cause common greedy buffering schemes to buffer too much data. Such over-buffering wastes expensive wireless channel capacity. Assuming that we can anticipate future data rates, we plan the quality and download time of video segments ahead. This anticipatory download scheduling avoids buffer underruns by downloading a large number of segments before a drop in available data rate occurs, without wasting wireless capacity by excessive buffering.We developed a practical anticipatory scheduling algorithm for segmented video streaming protocols (e.g., HLS or MPEG DASH). Simulation results and testbed measurements show that our solution essentially eliminates playback interruptions without significantly decreasing video quality.}}, author = {{Dräxler, Martin and Blobel, Johannes and Dreimann, Philipp and Valentin, Stefan and Karl, Holger}}, booktitle = {{Proceedings of the 2nd International Conference on Networked Systems (NetSys)}}, pages = {{1----8}}, title = {{{SmarterPhones: Anticipatory Download Scheduling for Wireless Video Streaming}}}, doi = {{10.1109/NetSys.2015.7089073}}, year = {{2015}}, } @inproceedings{253, abstract = {{Group signatures, introduced by Chaum and van Heyst [15], are an important primitive in cryptography. In group signature schemes every group member can anonymously sign messages on behalf of the group. In case of disputes a dedicated opening manager is able to trace signatures - he can extract the identity of the producer of a given signature. A formal model for static group signatures schemes and their security is defined by Bellare, Micciancio, and Warinschi [4], the case of dynamic groups is considered by Bellare, Shi, and Zhang [5]. Both models define group signature schemes with a single opening manager. The main difference between these models is that the number of group members in static schemes is fixed, while in dynamic schemes group members can join the group over time.}}, author = {{Blömer, Johannes and Juhnke, Jakob and Löken, Nils}}, booktitle = {{Proceedings of the Sixth International Conference on Mathematical Aspects of Computer and Information Sciences (MACIS)}}, pages = {{166--180}}, title = {{{Short Group Signatures with Distributed Traceability}}}, doi = {{10.1007/978-3-319-32859-1_14}}, year = {{2015}}, } @article{25312, author = {{Strube, Oliver I. and Rüdiger, Arne A. and Bremser, Wolfgang}}, issn = {{0143-7496}}, journal = {{International Journal of Adhesion and Adhesives}}, pages = {{9--13}}, title = {{{Buildup of biobased adhesive layers by enzymatically controlled deposition on the example of casein}}}, doi = {{10.1016/j.ijadhadh.2015.08.001}}, year = {{2015}}, }