8443328
Correct execution of transactions at different isolation levels
Many transaction processing applications execute at isolation levels lower than SERIALIZABLE in order to increase throughput and reduce response time. However, the resulting schedules might not be serializable and, hence, not necessarily correct. The semantics of a particular application determines whether that application will run correctly at a lower level and, in practice, it appears that many applications do. The decision to choose an isolation level at which to run an application and the analysis of the correctness of the resulting execution is usually done informally. We develop a formal technique to analyze and reason about the correctness of the execution of an application at isolation levels other than SERIALIZABLE. We use a new notion of correctness, semantic correctness, a criterion weaker than serializability, to investigate correctness. In particular, for each isolation level, we prove a condition under which the execution of transactions at that level will be semantically correct. In addition to the ANSI/ISO isolation levels of READ UNCOMMITTED, READ COMMITTED, and REPEATABLE READ, we also prove a condition for correct execution at the READ-COMMITTED with first-committer-wins and at SNAPSHOT isolation. We assume that different transactions in the same application can be executing at different levels, but that each transaction is executing at least at READ UNCOMMITTED.
16579446
Mining Correlation between Motifs and Gene Expression
One of the major challenges in the post-genomic era is to determine all DNA-binding transcription factors (TFs) and their regulatory binding sites (motifs) within the genomes. To discover the relationship between the motifs and changes in gene expression, we propose a new algorithm, co-miner (correlation miner). Correlation rules are generated based on the expression profiles of genes with significant expression change through the time course of gene expression. Thus, we may consider the change in gene expression to be causatively associated with the transcription binding sites in the upstream sequences. In addition, we introduce partition and constraint pushing techniques to improve the performance and demonstrate their effectiveness by our experiments. By applying co-miner to a yeast dataset, the relationships between motifs and gene expression revealed by co-miner are confirmed in the literature.
18131628
Automatic workflow verification and generation
Correctness is an important aspect of workflow management systems. However, most of the workflow literature focuses only on the modeling aspects and assumes that a workflow is correct if during the execution it respects the control and data dependency specified by the workflow designer. To address the correctness question properly we propose a new workflow model based on Hoare semantics that allows to: (1) automatically check if the desired outcome of a workflow can be produced by its actual implementation, (2) automatically synthesize a workflow implementation from the workflow specification and a given task library.In particular we: (1) formalize the semantics of workflows and tasks with pre-and postconditions, (2) for each control construct we provide a set of sound inference rules formalizing its semantics. While most of our workflow constructs are standard, two of them are new: the universal and the existential constructs. We then describe algorithms for automatically checking the correctness of workflows and for automatic workflow generation.
7682350
Incremental genetic K-means algorithm and its application in gene expression data analysis
BackgroundIn recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms such as K-means, hierarchical clustering, SOM, etc, genes are partitioned into groups based on the similarity between their expression profiles. In this way, functionally related genes are identified. As the amount of laboratory data in molecular biology grows exponentially each year due to advanced technologies such as Microarray, new efficient and effective methods for clustering must be developed to process this growing amount of biological data.ResultsIn this paper, we propose a new clustering algorithm, Incremental Genetic K-means Algorithm (IGKA). IGKA is an extension to our previously proposed clustering algorithm, the Fast Genetic K-means Algorithm (FGKA). IGKA outperforms FGKA when the mutation probability is small. The main idea of IGKA is to calculate the objective value Total Within-Cluster Variation (TWCV) and to cluster centroids incrementally whenever the mutation probability is small. IGKA inherits the salient feature of FGKA of always converging to the global optimum. C program is freely available at http://database.cs.wayne.edu/proj/FGKA/index.htm.ConclusionsOur experiments indicate that, while the IGKA algorithm has a convergence pattern similar to FGKA, it has a better time performance when the mutation probability decreases to some point. Finally, we used IGKA to cluster a yeast dataset and found that it increased the enrichment of genes of similar function within the cluster.
14239575
Semantics based verification and synthesis of BPEL4WS abstract processes
We introduce a logic model to formally specify the semantics of workflows and their composite tasks described as BPEL4WS abstract processes. Based on the model, we present a set of inference rules to deduce the strongest postcondition and weakest precondition of a workflow and demonstrate that automatic workflow verification is possible due to the restrictions on data manipulation in an abstract process. We then sketch an algorithm that automatically synthesizes a workflow given its specification and a task library.
6486168
A Dataflow-Oriented Atomicity and Provenance System for Pipelined Scientific Workflows
Scientific workflows have gained great momentum in recent years due to their critical roles in e-Science and cyberinfrastructure applications. However, some tasks of a scientific workflow might fail during execution. A domain scientist might require a region of a scientific workflow to be "atomic". Data provenance, which determines the source data that are used to produce a data item, is also essential to scientific workflows. In this paper, we propose: (i) an architecture for scientific workflow management systems that supports both provenance and atomicity; (ii) a dataflow-oriented atomicity model that supports the notions of commit and abort; and (iii) a dataflow-oriented provenance model that, in addition to supporting existing provenance graphs and queries, also supports queries related to atomicity and failure.
15500177
A unified architecture for the design and evaluation of wireless fair queueing algorithms
Fair queueing in the wireless domain poses significant challenges due to unique issues in the wireless channel such as location-dependent and bursty channel errors. In this paper, we present a wireless fair service model that captures the scheduling requirements of wireless scheduling algorithms, and present a unified wireless fair queueing architecture in which scheduling algorithms can be designed to achieve wireless fair service. We map seven recently proposed wireless fair scheduling algorithms to the unified architecture, and compare their properties through simulation and analysis. We conclude that some of these algorithms achieve the properties of wireless fair service including short-term and long-term fairness, short-term and long-term throughput bounds, and tight delay bounds for channel access.
1875526
Design Issues of Prefetching Strategies for Heterogeneous Software DSM
In distributed shared memory (DSM) systems, one of the major overheads is page fault, because it induces remote memory access latencies. Prefetching strategy permits home nodes sending data to remote nodes in advance, in order to reduce page faults and latencies, as also to improve overall performance; however, it causes accumulated waiting phenomenon, waiting synchronization phenomenon, among others. In heterogeneous environments, considering the fact of different ability among computing hosts, it increases idle time and synchronization time. Therefore, the search for alternatives to reduce these overheads is important. In this paper, we propose a method that utilizes concepts of load balancing in prefetching strategy, where the goal is to reduce idle time and synchronization time. Basically, this approach distributes home pages to appropriate computing nodes and adjusts prefetching strategy's policies into heterogeneous environments
1236934
A Packet Scheduling Approach to QoS Support in Multihop Wireless Networks
Providing packet-level quality of service (QoS) is critical to support both rate-sensitive and delay-sensitive applications in bandwidth-constrained, shared-channel, multihop wireless networks. Packet scheduling has been a very popular paradigm to ensure minimum throughput and bounded delay access for packet flows. This work describes a packet scheduling approach to QoS provisioning in multihop wireless networks. Besides minimum throughput and delay bounds for each flow, our scheduling disciplines seek to achieve fair and maximum allocation of the shared wireless channel bandwidth. However, these two criteria can potentially be in conflict in a generic-topology multihop wireless network where a single logical channel is shared among multiple contending flows and spatial reuse of the channel bandwidth is possible. In this paper, we propose a new scheduling model that addresses this conflict. The main results of this paper are the following: (a) a two-tier service model that provides a minimum “fair” allocation of the channel bandwidth for each packet flow and additionally maximizes spatial reuse of bandwidth, (b) an ideal centralized packet scheduling algorithm that realizes the above service model, and (c) a practical distributed backoff-based channel contention mechanism that approximates the ideal service within the framework of the CSMA/CA protocol.
42944978
Reliability enhancement of electronic packages by design of optimal parameters
Abstract Reliability growth testing involves the selection of optimal design parameters to enhance a product's reliability. This paper proposes a split plot experimental design that accommodates the restriction on randomization on the order of experimental runs caused by the experimental nature of accelerated reliability testing. The proposed experimental design provides statistically relevant solutions about the choice of design parameters, in terms of their reliability impact, in a much shorter time. A degradation model that aids in predicting the failure time for the given problem further supplements this discussion.
30892527
On Design and Implementation of Adaptive Data Classification Scheme for DSM Systems
Distributed Shared Memory (DSM) environment is built by using specific softwares, to combine a number of computer hardware resources into one computing environment. Such environment not only provides an easy way to execute parallel applications, but also combines resources to speedup execution of these applications. DSM systems need to maintain data consistency in memory, what usually leads to communication overhead. Therefore, there exist a number of strategies that can be used to overcome this overhead and improve overall performance. Prefetching strategies have been proven to show great performance in DSM systems, since they can reduce data access communication latencies from remote nodes. However, these strategies also transfer unnecessary prefetching pages to remote nodes. In this research paper, we focus on the analysis of data access pattern during execution of parallel applications. We propose an Adaptive Data Classification scheme to improve prefetching strategy, with the goal to improve overall performance. Adaptive Data Classification scheme classifies data according to the access behavior of pages, so that home node uses past history access patterns of remote nodes to decide whether it needs to transfer related pages to remote nodes. From experimental results, our method can improve the performance of prefetching strategies in DSM systems.