19666662
Table driven proportional access based real-time Ethernet for safety-critical real-time systems
Ethernet technology has received much attention in embedded system industries because of its cost efficiency, high availability, and popularity. This trend is not an exception even in safety critical real-time systems such as integrated modular avionics systems. To overcome the lack of deterministic characteristics in the Ethernet protocol, we propose a software-oriented approach based on table-driven proportional access. In addition to the protocol details, performance and schedulability analyses, as well as a prototype platform, are described.
30590203
Efficient State-Saving Architectures for Power-Mode Switching
Time and energy is expended in switching between power modes (e.g., active, hibernate, sleep, etc.). Powering off cache is one major reason for this. When there is a switch in the power-mode involving cache power-off, the system spends time and energy in filling the cache with new data (inherent cache misses). In our technique, before powering off the cache, we save its state in Embedded DRAM and bring it back when the previous power mode is restored. Our experiments have showed that in a majority of cases the cache contents are too valuable to be erased. By saving the contents we can reduce switching speed and energy. We present a heuristic to save the most relevant cache contents so that power and delay overheads are minimized. To measure the area overhead a synthesizable VHDL model was designed.
40618061
Transaction Recovery in Distributed DB/DC Systems: A Progressive Approach
10753893
Evaluation of Error Recovery Blocks Used for Cooperating Processes
Three alternatives for implementing recovery blocks (RB's) are conceivable for backward error recovery in concurrent processing. These are the asynchronous, synchronous, and the pseudorecovery point implementations. Asynchronous RB's are based on the concept of maximum autonomy in each of concurrent processes. Consequently, establishment of RB's in a process is made independently of others and unbounded rollback propagations become a serious problem. In order to completely avoid unbounded rollback propagations, it is necessary to synchronize the establishment of recovery blocks in all cooperating processes. Process autonomy is sacrificed and processes are forced to wait for commitments from others to establish a recovery line, leading to inefficiency in time utilization. As a compromise between asynchronous and synchronous RB's we propose to insert pseudorecovery points (PRP's) so that unbounded rollback propagations may be avoided while maintaining process autonomy. We developed probabilistic models for analyzing these three methods under standard assumptions in computer performance analysis, i.e., exponential distributions for related random variables. With these models we have estimated 1) the interval between two successive recovery lines for asynchronous RB's, 2) mean loss in computation power for the synchronized method, and 3) additional overhead and rollback distance in case PRP's are used.
31591898
Scanning the issue - special issue on real-time systems
920212
Resource scheduling in dependable integrated modular avionics
In the recent development of avionics systems, integrated modular avionics (IMA) is advocated for next generation architecture that needs integration of mixed criticality real-time applications. These integrated applications meet their own timing constraints while sharing avionics computer resources. To guarantee timing constraints and dependability of each application, an IMA-based system is equipped with the schemes for spatial and temporal partitioning. We refer the model as SP-RTS (strongly partitioned real-time system), which deals with processor partitions and communication channels as its basic scheduling entities. This paper presents a partition and channel-scheduling algorithm for the SP-RTS. The basic idea of the algorithm is to use a two-level hierarchical schedule that activates partitions (or channels) following a distance-constraints guaranteed cyclic schedule and then dispatches tasks (or messages) according to a fixed priority schedule. To enhance schedulability, we devised heuristic algorithms for deadline decomposition and channel combining. The simulation results show the schedulability analysis of the two-level scheduling algorithm and the beneficial characteristics of the proposed deadline decomposition and channel combining algorithms.
2908844
Operation-based Update Propagation in a Mobile File System
In this paper we describe a technique called operation-based update propagation for efficiently transmitting updates to large files that have been modified on a weakly connected client of a distributed file system. In this technique, modifications are captured above the file-system layer at the client, shipped to a surrogate client that is strongly connected to a server, re-executed at the surrogate, and the resulting files transmitted from the surrogate to the server. If re-execution fails to produce a file identical to the original, the system falls back to shipping the file from the client over the slow network. We have implemented a prototype of this mechanism in the Coda File System on Linux, and demonstrated performance improvements ranging from 40 percents to nearly three orders of magnitude in reduced network traffic and elapsed time. We also found a novel use of forward error correction in this context.
10552627
An efficient parallel join algorithm based on hypercube-partitioning
Many parallel join algorithms have been proposed so far but most of which are developed focused on minimizing the disk I/O and CPU costs. The communication cost, however, is also an important factor that can significantly affect the join processing performance in multiprocessor systems. We propose an efficient parallel join algorithm, called Cube-Robust, for hypercube multicomputers. The proposed algorithm is developed based on the observation that the size ratio of two relations to be joined is the dominant factor in the communication cost. We develop the analytic cost model for the proposed join algorithm. The performance comparisons show that the Cube-Robust join algorithm works better than others proposed earlier in a wide range of size ratios.<<ETX>>
39095893
Comparison of hierarchical and marginal likelihood estimators for binary outcomes
Abstract Likelihood estimation in random-effect models is often complicated because the marginal likelihood involves an analytically intractable integral. Numerical integration such as Gauss–Hermite quadrature is an option, but is generally not recommended when the dimensionality of the integral is high. An alternative is the use of hierarchical likelihood, which avoids such burdensome numerical integration. These two approaches for fitting binary data are compared and the advantages of using the hierarchical likelihood are discussed. Random-effect models for binary outcomes and for bivariate binary-continuous outcomes are considered.
14282973
Closing the Gap: Learning-Based Information Extraction Rivaling Knowledge-Engineering Methods
In this paper, we present a learning approach to the scenario template task of information extraction, where information filling one template could come from multiple sentences. When tested on the MUC-4 task, our learning approach achieves accuracy competitive to the best of the MUC-4 systems, which were all built with manually engineered rules. Our analysis reveals that our use of full parsing and state-of-the-art learning algorithms have contributed to the good performance. To our knowledge, this is the first research to have demonstrated that a learning approach to the full-scale information extraction task could achieve performance rivaling that of the knowledge engineering approach.
850911
Usability-based caching of query results in OLAP systems
In this paper we propose a new cache management scheme for online analytical processing (OLAP) systems based on the usability of query results in rewriting and processing other queries. For effective admission and replacement of OLAP query results, we consider the benefit of query results not only for recently issued queries but for the expected future queries of a current query. We exploit semantic relationships between successive queries in an OLAP session, which are derived from the interactive and navigational nature of OLAP query workloads, in order to classify and predict subsequent future queries. We present a method for estimating the usability of query results for the representative future queries using a probability model for them. Experimental evaluation shows that our caching scheme using the past and future usability of query results can reduce the cost of processing OLAP query workloads effectively only with a small cache size and outperforms the previous caching strategies for OLAP systems.