21762961
Voltage-Clock-Scaling Adaptive Scheduling Techniques for Low Power in Hard Real-Time Systems
Many embedded systems operate under severe power and energy constraints. Voltage clock scaling is one mechanism by which energy consumption may be reduced: it is based on the fact that power consumption is a quadratic function of the voltage, while the speed is a linear function. We show how voltage scaling can be scheduled to reduce energy usage while still meeting real-time deadlines.
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.
31591898
Scanning the issue - special issue on real-time systems
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.
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.
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.
9259468
Classification of Multiple Cancer Types by Multicategory Support Vector Machines Using Gene Expression Data
MOTIVATION
High-density DNA microarray measures the activities of several thousand genes simultaneously and the gene expression profiles have been used for the cancer classification recently. This new approach promises to give better therapeutic measurements to cancer patients by diagnosing cancer types with improved accuracy. The Support Vector Machine (SVM) is one of the classification methods successfully applied to the cancer diagnosis problems. However, its optimal extension to more than two classes was not obvious, which might impose limitations in its application to multiple tumor types. We briefly introduce the Multicategory SVM, which is a recently proposed extension of the binary SVM, and apply it to multiclass cancer diagnosis problems.


RESULTS
Its applicability is demonstrated on the leukemia data (Golub et al., 1999) and the small round blue cell tumors of childhood data (Khan et al., 2001). Comparable classification accuracy shown in the applications and its flexibility render the MSVM a viable alternative to other classification methods.


SUPPLEMENTARY INFORMATION
http://www.stat.ohio-state.edu/~yklee/msvm.htm
6394953
Accelerating Database Processing at e-Commerce Sites
Most e-commerce Web sites dynamically generate their contents through a three-tier server architecture composed of a Web server, an application server, and a database server. In such an architecture, the database server easily becomes a bottleneck to the overall performance. In this paper, we propose WDBAccel, a high-performance database server accelerator that significantly improves the throughput of the database processing, and thus that of the overall Web site. WDBAccel eliminates costly, complex query processing needed to obtain query results by reusing previous query results for subsequent queries. This differentiates WDBAccel from other database cache systems, which replicate a database into multiple conventional DBMS’s and distribute queries among them. We evaluate the performance of WDBAccel by using the queries of the TPC-W benchmark. The measurement results show that WDBAccel outperforms DBMS-based cache systems by up to an order of magnitude.
8697700
Probabilistic Retrieval Incorporating the Relationships of Descriptors Incrementally
The previous probabilistic retrieval models assume that the relevance probability of a document is independent of the descriptors that are not specified in a query. This is not true in practice because there can be many descriptors that represent the same concept. The probabilistic retrieval model developed in this paper overcomes this unsuitable assumption and incorporates the relationships of descriptors. A learning method is also proposed to figure out the relationships incrementally. Each time retrieval results are available, the method identifies in the relevant documents the descriptors that designate the concepts specified by the query descriptors. Although it employs user feedbacks like relevance feedback, it attempts to capture certain stable relationships of descriptors from many past user queries rather than to distinguish relevant documents from non-relevant ones for a particular query. We show through experiments that the proposed information retrieval method improves retrieval effectiveness over time.
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>>