44711812
An open real-time environment for parallel and distributed systems
Most computer-based systems have hard real-time constraints. Schedulers in complex systems must be designed to manage a set of applications developed and deployed independently. We study an open real-time environment architecture for distributed systems where real-time applications may run concurrently with non-real-time applications. The architecture uses a two-level scheduling scheme. Each application is assigned a sporadic server to schedule the processes in the application. All sporadic servers are then scheduled by a system-wide fixed priority scheduler. Using the proposed open environment architecture, all hard real-time applications are guaranteed to have their reserved CPU utilization in order to meet all their deadlines. The guarantee is independent of the behaviors of all other applications in the same system. We present the schedulability analysis methods on systems with or without shared memory.
27364789
Efficient on-line schedulability tests for priority driven real-time systems
Many computer systems, such as those for open system environments or multimedia services, need an efficient schedulability test for online admission control of new jobs. Although various polynomial-time schedulability tests have been proposed, they often fail to decide the schedulability of the system precisely when the system is heavily loaded. This paper presents efficient online schedulability tests which are are shown to be more precise and efficient than any existing polynominal-time schedulability tests. Moreover, our proposed tests can be used for the multiframe model, where a task may have different computation times in different periods. We show the performance of the proposed schedulability tests in several simulation experiments.
41113698
Scheduling Jobs with Temporal Distance Constraints
The job scheduling problems for real-time jobs with temporal distance constraints (JSD) are presented. In JSD, the start times of two related jobs must be within a given distance. The general JSD problem is NP-hard. We define the multilevel unit-time JSD (MUJSD) problem for systems with $m$ chains of unit-time jobs in which neighboring jobs in each chain must be scheduled within $c$ time units. We present an $O(n^2)$-time algorithm, where $n$ is the total number of jobs in the system, and also an $O(m^2 c^2)$-time algorithm. Some other variations of the JSD problems are also investigated.
27737931
Designing multimedia applications on real-time systems with SMP architecture
Large real-time multimedia systems such as flight simulators have adopted multiprocessor architecture to handle the large amount of events and computations. Existing realtime scheduling algorithms designed for single-processor systems such as Rate Monotonic (RM) and Earliest Deadline First Algorithm (EDF) have very poor performance on multiprocessor systems. On the other hand, most online scheduling algorithms for multiprocessor systems have poor schedulability conditions for real-time applications. In this paper, we study different ways to design real-time applications on SMP machines.
5475349
Scheduling Real-Time Systems with End-to-End Timing Constraints Using the Distributed Pinwheel Model
Real-time distributed applications have timing constraints on tasks running on several processors. To design real-time systems with end-to-end performance requirements, we need to have algorithms to schedule and to coordinate tasks on different processor nodes. An end-to-end scheduling approach based on the pinwheel scheduling model is presented for distributed real-time systems, We show how tasks on different nodes may be transformed to have periods consisting of only harmonic numbers. With harmonic periods, we can use a polynomial-time algorithm to find the start and finish times of each task on each node. Phase alignment algorithms are then applied to adjust the phases between schedules of neighboring nodes so that the overall end-to-end delay is minimized. Using the distributed pinwheel model, schedules on different nodes are synchronized to lessen the delays. For many real-time systems, this approach provides a predictable performance and a short end-to-end delay.
15072976
The design and implementation of real-time schedulers in RED-linux
Researchers in the real-time system community have designed and studied many advanced scheduling algorithms. However, most of these algorithms have not been implemented since it is very difficult to support new scheduling algorithms on most operating systems. To address this problem, we enhance the scheduling mechanism in Linux to provide a flexible scheduling framework. In the real-time and embedded Linux (RED-Linux) project, we implement a general scheduling framework which divides the system scheduler into two components: dispatcher and allocator. The dispatcher provides the mechanism of system scheduling and resides in the kernel space. The allocator is used to define the scheduling policy and implemented as a user space function. This framework allows users to implement application-specific schedulers in the user space which is easy to program and to debug. The framework also relieves the deficiency from the stock Linux scheduler which is not designed for real-time applications. To further enhance its power, a hierarchical scheduling mechanism has been provided in RED-Linux to allow a system designer to integrate different real-time applications together. Using scheduling groups, real-time jobs can be managed and scheduled in a hierarchical manner. In this paper, we discuss how the group mechanism is implemented in RED-Linux.
5363634
Applying bulk insertion techniques for dynamic reverse nearest neighbor problems
Reverse nearest neighbors queries have emerged as an important class of queries for spatial and other types of databases. The Rdnn-tree is an R-tree based structure that has been shown to perform outstandingly for such kind of queries. However, one practical problem facing it (as well as other type of indexes) is how to effectively construct the index from stretch. In this case, the cost of constructing and maintaining a Rdnn-Tree is about twice the cost of an R-Tree. Normal insertion into a Rdnn-Tree is performed one point at a time, known as single point insertion. The question arises, can insertion be improved there by reducing the construction and maintenance cost. In this paper we propose a bulk-loading technique, which is capable of significantly, improve the performance of constructing the index from stretch, as well as insert a large amount of data. Experiments show that our method outperforms the single point insertion significantly.
362708
Low-Cost RFID Identification Variation
Interests continue to grow in recent years for the adoption of Radio Frequency Identification (RFID) in many different areas including transportation and supply chain management. Those RFID-included objects can be targeted more efficiently by real-time tracking and instant management. However, because of the contact-less type of RFID remote retrieval, the transmission of data in the air is very vulnerable to eavesdropping or appropriation. A primary security concern surrounding RFID technology is the illicit tracking of consumer location and analyzing of their shopping habits or behavior. This paper proposes a more secure and lightweight RFID variation protection protocol which enhances the security of the transmission of information as well as the consumer privacy protection by using randomized control access and two-way identification. In addition, this protocol also improves the overall performance and lowers the cost of RFID tag without any complicated calculation.
16978334
Evaluating a class of distance-mapping algorithms for data mining and clustering
A distance-mapping algorithm takes a set of objects and a distance metric and then maps those objects to a Euclidean or pseudoEuclidean space in such a way that the distances among objects are approximately preserved. Distance mapping algorithms are a useful tool for clustering and visualization in data intensive applications, because they replace expensive distance calculations by sum-of-square calculations. This can make clustering in large databases with expensive distance metrics practical. In this paper we present five distance-mapping algorithms and conduct experiments to compare their performance in data clustering applications. These include two algorithms called FastMap and MetricMap, and three hybrid heuristics that combine the two algorithms in different ways. Experimental results on both synthetic and RNA data show the superiority of the hybrid algorithms. The results imply that FastMap and MetricMap capture complementary information about distance metrics and therefore can be used together to great benefit. The net effect is that multi-day computations may be done in minutes.
7990193
Tool to Generate a Local Internet Weather Report
This paper reports the results of some experiments conducted to measure the Internet congestion, viewed from a local perspective. A user-friendly graphical tool was developed to reflect the “local internet weather”. For a typical user this information is more relevant than the global characteristics, however, the existing tools to measure Internet traffic are not designed with the individual non-technical user in mind.
18266651
A similarity-based soft clustering algorithm for documents
Document clustering is an important tool for applications such as Web search engines. Clustering documents enables the user to have a good overall view of the information contained in the documents that he has. However, existing algorithms suffer from various aspects, hard clustering algorithms (where each document belongs to exactly one cluster) cannot detect the multiple themes of a document, while soft clustering algorithms (where each document can belong to multiple clusters) are usually inefficient. We propose SISC (similarity-based soft clustering), an efficient soft clustering algorithm based on a given similarity measure. SISC requires only a similarity measure for clustering and uses randomization to help make the clustering efficient. Comparison with existing hard clustering algorithms like K-means and its variants shows that SISC is both effective and efficient.