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Item type:Publication, Access status: with files , Usability of Symbolic Regression for Hybrid System Identification - System Classes and Parameters(2024-11-26); ; ; 13 17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Efficient and effective multi-objective optimization for real-time multi-task systems(Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing, 2023-07-26); Embedded real-time multi-task systems must often not only comply with timing constraints but also need to meet energy requirements. However, optimizing energy consumption might lead to higher Worst-Case Execution Time (WCET), leading to an un-schedulable system, as frequently executed code can easily differ from timing-critical code. To handle such an impasse in this paper, we formulate a Metaheuristic Algorithm-based Multi-objective Optimization (MAMO) for multi-task real-time systems. But, performing multiple WCET, energy, and schedulability analyses to solve a MAMO poses a bottleneck concerning compilation times. Therefore, we propose two novel approaches - Path-based Constraint Approach (PCA) and Impact-based Constraint Approach (ICA) - to reduce the solution search space size and to cope with this problem. Evaluations showed that PCA and ICA reduced compilation times by 85.31% and 77.31%, on average, over MAMO. For all the task sets, out of all solutions found by ICA-FPA, on average, 88.89% were on the final Pareto front.Publicationtype: Conference Paper22 85 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Towards multi-objective dynamic SPM allocation(Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing, 2023-07-26); Most real-time embedded systems are required to fulfill timing constraints while adhering to a limited energy budget. Small ScratchPad Memory (SPM) poses a common hardware constraint on embedded systems. Static SPM allocation techniques are limited by the SPM's stringent size constraint, which is why this paper proposes a Dynamic SPM Allocation (DSA) model at the compiler level for the dynamic allocation of a program to SPM during runtime. To minimize Worst-Case Execution Time (WCET) and energy objectives, we propose a multi-objective DSA-based optimization. Static SPM allocations might inherently use SPM sub-optimally, while all proposed DSA optimizations are only single-objective. Therefore, this paper is the first step towards a DSA that trades WCET and energy objectives simultaneously. Even with extra DSA overheads, our approach provides better quality solutions than the state-of-the-art multi-objective static SPM allocation and ILP-based single-objective DSA approach.Publicationtype: Conference Paper18 20 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Clustering solutions of multiobjective function inlining problem(2023-07); Hard real time-systems are often small devices operating on batteries that must react within a given deadline, so they must satisfy their timing, code size, and energy consumption requirements. Since these three objectives contradict each other, compilers for real-time systems go towards multiobjective optimizations which result in sets of trade-off solutions. A system designer can use the solution sets to choose the most suitable system configuration. Evolutionary algorithms can find trade-off solutions but the solution set might be large which complicates the task of the system designer. We propose to divide the solution set into clusters, so the system designer chooses the most suitable cluster and examines a smaller subset in detail. In contrast to other clustering techniques, our method guarantees that the sizes of all clusters are less than a predefined limit. Our method clusters a set by using any existing clustering method, divides clusters with sizes exceeding the predefined size into smaller clusters, and reduces the number of clusters by merging small clusters. The method guarantees that the final clusters satisfy the size constraint. We demonstrate our approach by considering a well-known compiler-based optimization called function inlining. It substitutes function calls by the function bodies which decreases the execution time and energy consumption of a program but increases its code size.Publicationtype: Conference Paper5 30 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Addressing the node discovery problem in fog computingIn recent years, the Internet of Things (IoT) has gained a lot of attention due to connecting various sensor devices with the cloud, in order to enable smart applications such as: smart traffic management, smart houses, and smart grids, among others. Due to the growing popularity of the IoT, the number of Internet-connected devices has increased significantly. As a result, these devices generate a huge amount of network traffic which may lead to bottlenecks, and eventually increase the communication latency with the cloud. To cope with such issues, a new computing paradigm has emerged, namely: fog computing. Fog computing enables computing that spans from the cloud to the edge of the network in order to distribute the computations of the IoT data, and to reduce the communication latency. However, fog computing is still in its infancy, and there are still related open problems. In this paper, we focus on the node discovery problem, i.e., how to add new compute nodes to a fog computing system. Moreover, we discuss how addressing this problem can have a positive impact on various aspects of fog computing, such as fault tolerance, resource heterogeneity, proximity awareness, and scalability. Finally, based on the experimental results that we produce by simulating various distributed compute nodes, we show how addressing the node discovery problem can improve the fault tolerance of a fog computing system.Publicationtype: Conference Paper30 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , TACLeBench : a benchmark collection to support worst-case execution time research(Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing, 2016-12); ; ; ; Engineering related research, such as research on worst-case execution time, uses experimentation to evaluate ideas. For these experiments we need example programs. Furthermore, to make the research experimentation repeatable those programs shall be made publicly available. We collected open-source programs, adapted them to a common coding style, and provide the collection in open-source. The benchmark collection is called TACLeBench and is available from GitHub in version 1.9 at the publication date of this paper. One of the main features of TACLeBench is that all programs are self-contained without any dependencies on standard libraries or an operating system.Publicationtype: Conference PaperScopus© Citations 82 151 108 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Adaptive failure detection and correction in dynamic patient-networksWireless sensors have been studied over recent years for different promising applications with high value for individuals and society. A good example are wireless sensor networks for patients allowing for better and more efficient monitoring of patients in hospitals or even early discharge form hospital and monitoring at home. These visions have hardly led research as reliability is and issue with wireless networks to be known error-prone. In life critical applications like health care this is not an aspect to be handled carelessly. Fail-safety is an important property for patient monitoring systems. The Ambient Assistance for Recovery (AA4R) project of the Hamburg University of Technology researches on a fail-safe patient monitoring system. Our vision is a dynamically distributed system using suitable devices in the area of a patient. The data in the network is stored with redundancy on several nodes. Patient data is analyzed in the network and uploaded to a medical server. As devices appear, disappear and fail, so do the services being executed on those devices. This article focuses on a Reincarnation Service (RS) to track the functionality of the processes. The RS takes suitable actions when a failure is detected to correct or isolate the failure. Checking of the nodes is done adaptively to achieve a good response time to failures and reduce the power consumption. © Martin Ringwelski, Andreas Timm-Giel, and Volker Turau.Publicationtype: Conference Paper201 157 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Avoiding publication and privatization problems on software transactional memory(Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing, 2011-03); This paper presents a new approach to exclude problems arising from dynamically switching between protected concurrent and unprotected single-threaded use of shared data when using software transactional memory in OO languages such as Java. The approach is based on a simple but effective programming model separating transactions from non-transactional operation. It prevents the application programmer from errors but does not force the software transactional memory library to observe non-transactional access and thereby preserves modularity of the software. A prototypical toolchain for validation and source code instrumentation was implemented as a proof of concept. © Holger Machens and Volker Turau.Publicationtype: Conference Paper27