@inproceedings{58224, author = {{Kenneweg, Philip and Kenneweg, Tristan and Fumagalli, Fabian and Hammer, Barbara}}, booktitle = {{2024 International Joint Conference on Neural Networks (IJCNN)}}, keywords = {{Training, Schedules, Codes, Search methods, Source coding, Computer architecture, Transformers}}, pages = {{1--8}}, title = {{{No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation}}}, doi = {{10.1109/IJCNN60899.2024.10650124}}, year = {{2024}}, } @inproceedings{48856, abstract = {{There exist many optimal or heuristic priority rules for machine scheduling problems, which can easily be integrated into single-objective evolutionary algorithms via mutation operators. However, in the multi-objective case, simultaneously applying different priorities for different objectives may cause severe disruptions in the genome and may lead to inferior solutions. In this paper, we combine an existing mutation operator concept with new insights from detailed observation of the structure of solutions for multi-objective machine scheduling problems. This allows the comprehensive integration of priority rules to produce better Pareto-front approximations. We evaluate the extended operator concept compared to standard swap mutation and the stand-alone components of our hybrid scheme, which performs best in all evaluated cases.}}, author = {{Bossek, Jakob and Grimme, Christian}}, booktitle = {{2017 IEEE Symposium Series on Computational Intelligence (SSCI)}}, keywords = {{Evolutionary computation, Processor scheduling, Schedules, Scheduling, Sociology, Standards, Statistics}}, pages = {{1–8}}, title = {{{An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling}}}, doi = {{10.1109/SSCI.2017.8285224}}, year = {{2017}}, } @article{17657, abstract = {{Inter-datacenter transfers of non-interactive but timely large flows over a private (managed) network is an important problem faced by many cloud service providers. The considered flows are non-interactive because they do not explicitly target the end users. However, most of them must be performed on a timely basis and are associated with a deadline. We propose to schedule these flows by a centralized controller, which determines when to transmit each flow and which path to use. Two scheduling models are presented in this paper. In the first, the controller also determines the rate of each flow, while in the second bandwidth is assigned by the network according to the TCP rules. We develop scheduling algorithms for both models and compare their complexity and performance.}}, author = {{Cohen, R. and Polevoy, Gleb}}, issn = {{2168-7161}}, journal = {{Cloud Computing, IEEE Transactions on}}, keywords = {{Approximation algorithms, Approximation methods, Bandwidth, Cloud computing, Routing, Schedules, Scheduling}}, number = {{99}}, pages = {{1--1}}, title = {{{Inter-Datacenter Scheduling of Large Data Flows}}}, doi = {{10.1109/TCC.2015.2487964}}, volume = {{PP}}, year = {{2015}}, } @inproceedings{36922, abstract = {{In this paper we present an approach for the self reconfiguration of distributed micro-controllers for increased fault tolerance. Based on a modified distributed system topology utilizing a time division multiple access (TDMA) protocol, i.e., Flex Ray, we present a self-organized distributed coordinator concept which performs the self-reconfiguration in the case of node failures. We introduce a distributed coordinator, which utilizes redundant slots in the Flex Ray communication schedule and combines messages in configured protocol frames and slots to avoid a complete bus restart. As such, the self-reconfiguration is realized by means of predetermined information about resulting changes in the communication dependencies and (re-)assignments determined in the design phase. To retrieve the necessary information, we present an analytical approach, which determines a combined solution for the initial configuration and all possible reconfigurations for the remaining nodes of the Flex Ray network in case of node failures. Hence, through this method we can design self-reconfiguring network-based systems enabling the handling of node failures for an increased fault tolerance.}}, author = {{Klobedanz, Kay and Müller, Wolfgang and Rettberg, Achim}}, keywords = {{Real time systems, Fault tolerant systems, Schedules, Protocols, Redundancy, Delay}}, publisher = {{IEEE}}, title = {{{An Approach for Self-Reconfiguring and Fault-Tolerant Distributed Real-Time Systems}}}, doi = {{10.1109/ISORCW.2012.41}}, year = {{2012}}, } @inproceedings{37006, abstract = {{In this paper we present an approach for the configuration and reconfiguration of FlexRay networks to increase their fault tolerance. To guarantee a correct and deterministic system behavior, the FlexRay specification does not allow a reconfiguration of the schedapproachule during run time. To avoid the necessity of a complete bus restart in case of a node failure, we propose a reconfiguration using redundant slots in the schedule and/or combine messages in existing frames and slots, to compensate node failures and increase robustness. Our approach supports the developer to increase the fault tolerance of the system during the design phase. It is a heuristic, which, additionally to a determined initial configuration, calculates possible reconfigurations for the remaining nodes of the FlexRay network in case of a node failure, to keep the system working properly. An evaluation by means of realistic safety-critical automotive real-time systems revealed that it determines valid reconfigurations for up to 80% of possible individual node failures. In summary, our approach offers major support for the developer of FlexRay networks since the results provide helpful feedback about reconfiguration capabilities. In an iterative design process these information can be used to determine and optimize valid reconfigurations.}}, author = {{Klobedanz, Kay and König, Andreas and Müller, Wolfgang}}, booktitle = {{Proceedings of DATE'11}}, keywords = {{Schedules, Fault tolerant systems, Redundancy, Protocols, Automotive engineering, Genetic algorithms}}, location = {{Grenoble, France}}, publisher = {{IEEE}}, title = {{{A Reconfiguration Approach for Faul-Tolerant FlexRay Networks}}}, doi = {{10.1109/DATE.2011.5763022}}, year = {{2011}}, } @inproceedings{37056, abstract = {{In this paper we present an approach to increase the fault tolerance in FlexRay networks by introducing backup nodes to replace defect ECUs (Electronic Control Units). In order to reduce the memory requirements of such backup nodes, we distribute redundant tasks over different nodes and propose the distributed coordinated migration of tasks of the defect ECU to the backup node at runtime. This approach enhances our former work in, where we extended the FlexRay bus schedule by redundant slots to consider changes in the communication/slot assignment and investigated and evaluated different solutions to migrate the redundant tasks to the backup node using the static and/or dynamic segment of the communication cycle for transmissions. We present the approach of distributed coordination for migration and communication instead of additional dedicated coordinator nodes to further increase the fault tolerance. With this approach we improve the safety of FlexRay networks by avoiding a possible single point of failure due to a dedicated coordinator node also minimizing the necessary time needed for a reconfiguration after an ECU failure. Furthermore, we reduce the overhead within the communication and the demand for additional hardware components.}}, author = {{Klobedanz, Kay and Defo, Gilles B. and Müller, Wolfgang and Kerstan, Timo}}, booktitle = {{Proceedings of SIES 2010}}, keywords = {{Fault tolerant systems, Protocols, Redundancy, Runtime, Payloads, Schedules}}, title = {{{Distributed Coordination of Task Migration for Fault-Tolerant FlexRay Networks}}}, doi = {{10.1109/SIES.2010.5551384}}, year = {{2010}}, }