1,665 research outputs found

    ENHANCING DATABASE PERFORMANCE IN A DSS ENVIRONMENT VIA QUERY CACHING

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    A key element in all decision support systems is availability of sufficiently good and timely data to support the decision making process. Much research was, and is, devoted to data and information quality: attributes, assurance that quality data is used in the decision process, etc. In this paper we concentrate on a particular dimension of data availability and usage -the retrieval of data in a timely and decision enhancing manner. We propose to augment the decision support databases by an adaptive and efficient query cache. The cache contains snapshots of the decision support database, each being the answer to a recently invoked query. A snapshot can be reused by the originating user, or a different user, at a later time --provided the use of cached data leads to savings over the use of a new query, and these savings exceed the cost of using stale date. The proposed scheme is conceptually different from conventional data replication schemes. In data replication schemes the data items to be replicated and the protocols for concurrency control are defined at the system level. In our scheme the cache is populated dynamically and the snapshots it contains are refreshed only if the cost of using stale information is higher than cost of refreshing the snapshots. At the same time, users can still decide to refresh the stored snapshot, based on their own decision environment. Our scheme thus enhances the data retrievalprocess, while supporting a more efficient data retrieval at both the user level and the data warehouse leve

    The Design of a Web Snapshot Management System for Decision Support Applications

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    Database snapshots that are defined and/or delivered via the Web are called web snapshots. This paper addresses the requirements for web snapshot management. A web snapshot management system is proposed; its architecture and functions of the major components are described; new commands are defined to perform web snapshot management activities

    The Design of a Web Document Snapshots Delivery System

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    A web document snapshot is a point-in-time capture of its code and the resulting presentation of executing the code. It is used as a way of electronically preserving historical information published in web documents enabling an organization to audit a web document’s contents at a point in the past and perform business analyses with historical information recorded in it. It is also an archived copy of a web document when it is changed. This research develops a system to deliver snapshots of a web document’s static and dynamic contents when it is requested. The system consists of a Database Snapshot Manager for providing database snapshots and a Web Document Snapshot Manager for providing web document snapshots. Algorithms supporting the two managers are presented

    GossiCrypt: Wireless Sensor Network Data Confidentiality Against Parasitic Adversaries

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    Resource and cost constraints remain a challenge for wireless sensor network security. In this paper, we propose a new approach to protect confidentiality against a parasitic adversary, which seeks to exploit sensor networks by obtaining measurements in an unauthorized way. Our low-complexity solution, GossiCrypt, leverages on the large scale of sensor networks to protect confidentiality efficiently and effectively. GossiCrypt protects data by symmetric key encryption at their source nodes and re-encryption at a randomly chosen subset of nodes en route to the sink. Furthermore, it employs key refreshing to mitigate the physical compromise of cryptographic keys. We validate GossiCrypt analytically and with simulations, showing it protects data confidentiality with probability almost one. Moreover, compared with a system that uses public-key data encryption, the energy consumption of GossiCrypt is one to three orders of magnitude lower

    A Holistic Approach to Lowering Latency in Geo-distributed Web Applications

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    User perceived end-to-end latency of web applications have a huge impact on the revenue for many businesses. The end-to-end latency of web applications is impacted by: (i) User to Application server (front-end) latency which includes downloading and parsing web pages, retrieving further objects requested by javascript executions; and (ii) Application and storage server(back-end) latency which includes retrieving meta-data required for an initial rendering, and subsequent content based on user actions. Improving the user-perceived performance of web applications is challenging, given their complex operating environments involving user-facing web servers, content distribution network (CDN) servers, multi-tiered application servers, and storage servers. Further, the application and storage servers are often deployed on multi-tenant cloud platforms that show high performance variability. While many novel approaches like SPDY and geo-replicated datastores have been developed to improve their performance, many of these solutions are specific to certain layers, and may have different impact on user-perceived performance. The primary goal of this thesis is to address the above challenges in a holistic manner, focusing specifically on improving the end-to-end latency of geo-distributed multi-tiered web applications. This thesis makes the following contributions: (i) First, it reduces user-facing latency by helping CDNs identify and map objects that are more critical for page-load latency to the faster CDN cache layers. Through controlled experiments on real-world web pages, we show the potential of our approach to reduce hundreds of milliseconds in latency without affecting overall CDN miss rates. (ii) Next, it reduces back-end latency by optimally adapting the datastore replication policies (including number and location of replicas) to the heterogeneity in workloads. We show the benefits of our replication models using real-world traces of Twitter, Wikipedia and Gowalla on a 8 datacenter Cassandra cluster deployed on EC2. (iii) Finally, it makes multi-tier applications resilient to the inherent performance variability in the cloud through fine-grained request redirection. We highlight the benefits of our approach by deploying three real-world applications on commercial cloud platforms

    The NorduGrid architecture and tools

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    The NorduGrid project designed a Grid architecture with the primary goal to meet the requirements of production tasks of the LHC experiments. While it is meant to be a rather generic Grid system, it puts emphasis on batch processing suitable for problems encountered in High Energy Physics. The NorduGrid architecture implementation uses the \globus{} as the foundation for various components, developed by the project. While introducing new services, the NorduGrid does not modify the Globus tools, such that the two can eventually co-exist. The NorduGrid topology is decentralized, avoiding a single point of failure. The NorduGrid architecture is thus a light-weight, non-invasive and dynamic one, while robust and scalable, capable of meeting most challenging tasks of High Energy Physics.Comment: Talk from the 2003 Computing in High Energy Physics and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 9 pages,LaTeX, 4 figures. PSN MOAT00

    Supporting End-Users\u27 Non-Consistent Views for Decision Support Applications

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    Database views typically are maintained to be consistent with the database at a specific point in time. There are applications, however, where users may prefer or require views which are not consistent with the database. Supporting non-consistent views provides better information for end-users in a decision support environment such as data warehousing. This paper examines thecharacteristics of non-consistent views and investigates their management
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