9193373
Pfair scheduling of periodic tasks with allocation constraints on multiple processors
Summary form only given. Pfair scheduling for periodic tasks on multiple processors in a time slotted environment can not only guarantee task deadlines to be respected, but also make tasks execute at steady progressive rates. We consider pfair schedulability of periodic tasks with allocation constraints in the sense that some tasks can only be assigned to one or more specified processors. The contributions of the paper lie in the following four aspects. Firstly, we prove that there exists pfair schedule in the case that fixed tasks are assigned to disjoined processor subsets. Secondly, we give a sufficient and necessary condition of the existence of pfair schedule for periodic tasks with arbitrary allocation constraints. Thirdly, we show that pfair schedulability test of periodic tasks with arbitrary allocation constraints can be done in polynomial time. Finally, an online approximate pfair scheduling algorithm called HPA (hierarchical pfair algorithm) is proposed for scheduling fixed and migrating tasks. With HPA although idea a fixed task is not guaranteed to respect its deadline completely, the amount of time by which it misses its deadline is bounded.
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
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.
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.
40618061
Transaction Recovery in Distributed DB/DC Systems: A Progressive Approach
16022713
Query based event extraction along a timeline
In this paper, we present a framework and a system that extracts events relevant to a query from a collection C of documents, and places such events along a timeline. Each event is represented by a sentence extracted from C, based on the assumption that "important" events are widely cited in many documents for a period of time within which these events are of interest. In our experiments, we used queries that are event types ("earthquake") and person names (e.g. "George Bush"). Evaluation was performed using G8 leader names as queries: comparison made by human evaluators between manually and system generated timelines showed that although manually generated timelines are on average more preferable, system generated timelines are sometimes judged to be better than manually constructed ones.
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.
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.
7927244
GM-WTA: An efficient workflow task allocation method in a distributed execution environment
A workflow is a collection of units of work called workflow tasks which cooperatively realize a business objective by utilizing system resources such as databases. The roles of workflow tasks are performed in the order driven by a computer representation of the workflow logic. During completing each task's role, the remote control transfers and the remote resource accesses may often occur in a distributed workflow system. Hence, the efficient distribution of workflow components, especially workflow tasks, is so effective as to improve the performance of workflow processing. If we can place adjacent workflow tasks as close as possible and locate workflow tasks near to the required resources, we can significantly reduce the overhead of workflow processing.In this paper, we propose an efficient workflow task allocation method in a distributed workflow system, which is based on the locality principle. The method that utilizes the concept of graph partitioning can improve the performanace of workflow processing by minimizing the remote processing costs incurred during workflow execution. In addition, we perform several experiments to evaluate our proposed method.
15368609
Data quality in context
ATA-QUALITY (DQ) PROBLEMS ARE INCREASINGLY EVIdent, particularly in organizational databases. Indeed, 50% to 80% of computerized criminal records in the U.S. were found to be inaccurate, incomplete, or ambiguous. The social and economic impact of poor-quality data costs billions of dollars. [5-7, 10]. Organizational databases, however, reside in the larger context of information systems (IS). Within this larger context, data is collected from multiple data sources and stored in databases. From this stored data, useful information is generated for organizational decision-making. A new study reveals businesses are defining data quality with the consumer in mind.