172967
XML subtree reconstruction from relational storage of XML documents
Numerous researchers have proposed to use relational databases to store and query XML documents. In these systems, the elements selected by an XML query are returned to an application either by select mode or by reconstruct mode. For the reconstruct mode, the XML subtrees that are rooted at the selected elements need to be extracted and reconstructed from the relational storage of XML documents. Therefore, XML subtree reconstruction is an important problem since its efficiency has a significant impact on XML query response time. In this paper, we propose (i) a linear XML subtree reconstruction algorithm Reconstruct to reconstruct an XML subtree from the structure-encoded sequence of the subtree that is extracted from the relational database by a structure-encoded sequence retrieval algorithm, (ii) a generic efficient structure-encoded sequence retrieval algorithm RD-SB for a schema-based relational XML storage, and (iii) a generic efficient structure-encoded sequence retrieval algorithm RD-SL for a schema-less relational XML storage. To the best of our knowledge, our algorithms provide the first generic solutions to the XML subtree reconstruction problem that are applicable to all relational XML storage schemes proposed in the literature. Finally, our experiments show that our algorithms are efficient and scalable.
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.
1552056
Pama: a Fast String Matching Algorithm
String matching is a fundamental operation in computer science, and its performance has great impact on many applications including database query, text processing, DNA and protein sequence analysis. In this paper, we propose a fast string matching algorithm, PAMA (PAttern MAtching). The shift rule used by PAMA not only subsumes both the bad character rule and the good suffix rule employed by the well-known Boyer-Moore algorithm, but also employs an additional key observation to enable faster shifting during the string matching process. Theoretically, we prove that from the same alignment, the next shift of PAMA will be at least as much as that of the Boyer-Moore algorithm. Experimentally, we show that PAMA indeed significantly outperforms the original Boyer-Moore algorithm in almost all cases, and outperforms other Boyer-Moore variants such as Tuned-BM, Turbo-BM and Horspool for long patterns (length ≥ 128) or for small alphabets (size < 8).
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.
1137858
Runtime Security Verification for Itinerary-Driven Mobile Agents
We present a new approach to ensure the secure execution of itinerary-driven mobile agents, in which the specification of the navigational behavior of an agent is separated from the specification of its computational behavior. We empower each host with an access control policy so that the host will deny the access from an agent whose itinerary does not conform to the host's access control policy. A host uses model checking algorithms to check if the itinerary of the agent conforms to its access control policy written in mu-calculus, and if so, grant access permission. In order to address the state explosion problem for model checking itineraries, we propose an approach called model generation code. In this approach, instead of verifying the itinerary itself, a host actually checks the conservative models of a mobile agent. If a conservative model does not satisfy the host's access control policy, the mobile agent will provide refined models for further verification. Our preliminary results show that this is a practical and promising approach to ensure the secure execution of mobile agents
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.
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.
2219088
A self-coordinating approach to distributed fair queueing in ad hoc wireless networks
Distributed fair queueing in shared-medium ad hoc wireless networks is non-trivial because of the unique design challenges in such networks, such as location-dependent contention, distributed nature of ad hoc fair queueing, channel spatial reuse, and scalability in the presence of node mobility. In this paper, we seek to devise new distributed, localized, scalable and efficient solutions to this problem. We first analyze an ideal centralized fair queueing algorithm developed for ad hoc networks, and extract the desired global properties that the localized algorithms should possess. We then propose three localized fair queueing models, in which local schedulers self-coordinate their local interactions and collectively achieve the desired global properties. We further describe a novel implementation of the proposed models within the framework of the popular CSMA/CA paradigm and address several practical issues. Our simulations and analysis demonstrate the effectiveness of our proposed design.
11410811
Fair scheduling in wireless packet networks
Fair scheduling of delay and rate-sensitive packet flows over a wireless channel is not addressed effectively by most contemporary wireline fair-scheduling algorithms because of two unique characteristics of wireless media: (1) bursty channel errors and (2) location-dependent channel capacity and errors. Besides, in packet cellular networks, the base station typically performs the task of packet scheduling for both downlink and uplink flows in a cell; however, a base station has only a limited knowledge of the arrival processes of uplink flows. We propose a new model for wireless fair-scheduling based on an adaptation of fluid fair queueing (FFQ) to handle location-dependent error bursts. We describe an ideal wireless fair-scheduling algorithm which provides a packetized implementation of the fluid mode, while assuming full knowledge of the current channel conditions. For this algorithm, we derive the worst-case throughput and delay bounds. Finally, we describe a practical wireless scheduling algorithm which approximates the ideal algorithm. Through simulations, we show that the algorithm achieves the desirable properties identified in the wireless FFQ model.
35964038
Learning Engineering Models with the Minimum Description Length Principle
This paper discusses discovery of mathematical models from engineering data sets. KEDS, a Knowledge-based Equation Discovery System, identifies several potentially overlapping regions in the problem space, each associated with an equation of different complexity and accuracy. The minimum description length principle, together with the KEDS algorithm, is used to guide the partitioning of the problem space. The KEDSMDL algorithm has been tested on discovering models for predicting the performance efficiencies of an internal combustion engine.