17622745
Automatic synthesis of multi-tasking implementations from real-time object-oriented models
Presents an approach towards the automatic synthesis of implementations from real-time object-oriented design models. From an application design model that addresses the functional requirements of the system, and given end-to-end timing requirements, our synthesis approach generates a feasible implementation model, i.e. one that will meet the timing requirements. The synthesis process is supported by automatic code generation that can take the application design model and the synthesized implementation model, and can generate code for the target platform. The synthesis of an implementation model is facilitated through the use of a generic (application-independent) implementation architecture, thereby reducing the synthesis problem to selecting a mapping of the application design model to the artifacts of the implementation architecture. In this paper, we use a multi-threaded event handling architecture with fixed event priorities. The synthesis problem then consists of determining priorities for events and mapping events to threads. We show how, given such a mapping, the response times can be analyzed, and then how, using the analysis, a feasible implementation model can be automatically synthesized.
1772294
Scalable real-time system design using preemption thresholds
The maturity of schedulability analysis techniques for fixed-priority preemptive scheduling has enabled the consideration of timing issues at design time using a specification of the tasking architecture and estimates of execution times for tasks. While successful, this approach has limitations since the preemptive multi-tasking model does not scale well for a large number of tasks, and the fixed-priority scheduling theory does not work well with many object-oriented design methods. In this paper, we present an approach that scales well even when the design consists of a large number of concurrent jobs. The approach avoids any unnecessary preemptability in the system, thereby resulting in reduced run-time overheads from preemptions and associated context switches. It also allows significant memory savings by grouping jobs into non-preemptive groups and then sharing the stack space between them. Our approach is based on our earlier work on scheduling using preemption thresholds that allows parametric control over preemptability in a priority-based system. We show that our approach provides significant advantages over one using a fixed-priority preemptive scheduling architecture. The benefits include higher schedulability for small numbers of tasks and lower run-time overheads, and hence better scalability. We develop algorithms that allow design-time consideration of schedulability and automatic synthesis of an implementation model to minimize run-time overheads.
2498388
Scheduling fixed-priority tasks with preemption threshold
In the context of fixed-priority scheduling, feasibility of a task set with non-preemptive scheduling does not imply the feasibility with preemptive scheduling and vice versa. We use the notion of preemption threshold, first introduced by Express Logic, in their ThreadX real-time operating system, to develop a scheduling model that subsumes both preemptive and non-preemptive fixed priority scheduling. Preemption threshold allows a task to only disable preemption of tasks up to a specified threshold priority. Tasks having priorities higher than the threshold are still allowed to preempt. With this new scheduling model, we show that schedulability is improved as compared to both the preemptive and nonpreemptive scheduling models. We develop the equations for computing the worst-case response times, using the concept of level-i busy period. Some useful results about the generalized model are presented and an algorithm for optimal assignment of priority and preemption threshold is designed based on these results.
6926567
Semi-Latent Dirichlet Allocation: A Hierarchical Model for Human Action Recognition
We propose a new method for human action recognition from video sequences using latent topic models. Video sequences are represented by a novel "bag-of-words" representation, where each frame corresponds to a "word". The major difference between our model and previous latent topic models for recognition problems in computer vision is that, our model is trained in a "semi-supervised" way. Our model has several advantages over other similar models. First of all, the training is much easier due to the decoupling of the model parameters. Secondly, it naturally solves the problem of how to choose the appropriate number of latent topics. Thirdly, it achieves much better performance by utilizing the information provided by the class labels in the training set. We present action classification and irregularity detection results, and show improvement over previous methods.
7500432
A Method to Organize A Small-World Based Publish/Subscribe Network In Large-Scale Environment
The paper proposes a Small-World Network Publish/ Subscribe (SWN-P/S) model in large-scale environment, which is a novel Event-based Middleware with Small-World Network (SWN) model. Through connecting brokers into a small world network, SWN-P/S achieves both a strong local clustering and a small average path length among vast brokers. These characteristics help to spread information through the system more rapidly. The paper also put forwards a cloud-partition method to organize brokers in terms of clustering coefficient in SWN. The method is useful to reduce the amount of routing information stored in each broker and to accelerate information dissemination. Comparisons of SWN-P/S with other construction ways for Publish/Subscribe Event-based Middleware show that SWN-P/S is more suitable for building large-scale distributed systems.
9220767
Upright cluster services
The UpRight library seeks to make Byzantine fault tolerance (BFT) a simple and viable alternative to crash fault tolerance for a range of cluster services. We demonstrate UpRight by producing BFT versions of the Zookeeper lock service and the Hadoop Distributed File System (HDFS). Our design choices in UpRight favor simplifying adoption by existing applications; performance is a secondary concern. Despite these priorities, our BFT Zookeeper and BFT HDFS implementations have performance comparable with the originals while providing additional robustness.
19740000
Color Image Segmentation Based on Parameter-Dependent Connected Components
A theory of a parameter-dependent connected components of gray images that takes into account both the gray values of the pixels and the differences of the gray values of the neighboring pixels has been introduced in a previous work. The concept of the parameter-dependent connected components has been applied to gray-scaled images for segmentation successfully. In this paper, the author investigates a method to apply the concept of the parameterdependent connected components to color images for segmentation.
35749769
EFSM-based Testing Strategy for APIs Test of Embedded OS
In this paper, we present a two-phase approach to generate test data for the EFSM model of an embedded operating system. We first build the EFSM model of the system. The model can then be used to automatically generate test data for testing of APIs. We also point out certain issues that need further study.