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PublicationInterface Algebra for Analysis of Hierarchical Real-Time Systems(2008-04-05) Easwaran, Arvind; Lee, Insup; Sokolsky, OlegComplex real-time embedded systems can be developed using component based design methodologies. Timing requirements of real-time components in the system can be modeled using hierarchical frameworks to capture resource sharing among components under different schedulers. To support component based design for real-time embedded systems, we must then address schedulability analysis of hierarchical scheduling models. In this paper, we propose a generic interface algebra for compositional schedulability analysis of such models. We also define conditions under which this algebra supports incremental analysis, dynamic adaptability, and independent implementability. Furthermore, we also propose a novel periodic resource model based framework for compositional and incremental schedulability analysis of hierarchical scheduling models. This extends our earlier proposed framework with a technique that allows periodic resource models with different periods to be composed together. We formulate this framework in our proposed algebra to demonstrate ease of use of the algebra and to identify framework properties. PublicationHierarchical Scheduling Framework for Virtual Clustering of Multiprocessors(2008-07-02) Easwaran, Arvind; Shin, Insik; Lee, InsupScheduling of sporadic task systems on multiprocessor platforms is an area which has received much attention in the recent past. It is widely believed that finding an optimal scheduler is hard, and therefore most studies have focused on developing algorithms with good utilization bounds. These algorithms can be broadly classified into two categories: partitioned scheduling in which tasks are statically assigned to individual processors, and global scheduling in which each task is allowed to execute on any processor in the platform. In this paper we consider a third, more general, approach called cluster-based scheduling. In this approach each task is statically assigned to a processor cluster, tasks in each cluster are globally scheduled among themselves, and clusters in turn are scheduled on the multiprocessor platform. We develop techniques to support such cluster-based scheduling algorithms, and also consider properties that minimize processor utilization of individual clusters. Since neither partitioned nor global strategies dominate over the other, cluster-based scheduling is a natural direction for research towards achieving improved utilization bounds. PublicationCompositional Analysis Framework using EDP Resource Models(2007-12-03) Easwaran, Arvind; Anand, Madhukar; Lee, InsupCompositional schedulability analysis of hierarchical scheduling frameworks is a well studied problem, as it has wide-ranging applications in the embedded systems domain. Several techniques, such as periodic resource model based abstraction and composition, have been proposed for this problem. However these frameworks are sub-optimal because they incur bandwidth overhead. In this work, we introduce the Explicit Deadline Periodic (EDP) resource model, and present compositional analysis techniques under EDF and DM. We show that these techniques are bandwidth optimal, in that they do not incur any bandwidth overhead in abstraction or composition. Hence, this framework is more efficient when compared to existing approaches. PublicationCARTS: A Tool for Compositional Analysis of Real-Time Systems(2010-11-01) Phan, Linh T.X.; Lee, Jaewoo; Easwaran, Arvind; Ramaswamy, Vinay; Chen, Sanjian; Lee, Insup; Sokolsky, OlegThis paper demonstrates CARTS, a compositional analysis tool for real-time systems. We presented an overview of the underlying theoretical foundation and the architecture design of the tool. CARTS is open source and available for free download at http://rtg.cis.upenn.edu/carts/. PublicationSchedulability Analysis of Hierarchical Real-Time Systems(2007-05-07) Easwaran, Arvind; Shin, Insik; Sokolsky, Oleg; Lee, InsupEmbedded systems are complex as a whole but consist of smaller independent modules interacting with each other. This structure makes embedded systems amenable to compositional design. Real-time embedded systems consist of real-time workloads having temporal deadlines. Compositional design of real-time embedded systems can be done using systems consisting of real-time components arranged in a scheduling hierarchy. Each component consists of some real-time workload and a scheduling policy for the workload. To simplify schedulability analysis for such systems, analysis can be done compositionally using interfaces that abstract the timing requirements of components. To facilitate analysis of dynam- ically changing real-time systems, the framework must support incremental analysis. In this paper, we summarize our work [19, 6] on schedulability analysis for hierarchical real-time systems. We describe a compositional analysis technique that abstracts resource requirements of components using periodic resource models. To support incremental analysis and resource bandwidth minimization, we describe an extension to this interface model. Each extended interface consists of multiple periodic resource models for different periods. This allows the selection of a periodic model that can schedule the system using minimum bandwidth. We also account for context switch overheads in these interfaces. We then describe an associative composition technique for such interfaces that supports incremental analysis.