Conferences related to Query processing

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2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


2019 IEEE 21st International Conference on Business Informatics (CBI)

The IEEE CBI series encourages a broad understanding of Business Informatics research, and intends to further its many different facets, theoretical foundations and experiential body of knowledge.


2019 IEEE 35th International Conference on Data Engineering (ICDE)

AI interaction with DB technologyBig Data, Data-Warehousing System ArchitecturesBenchmarking, Performance Modelling, and TuningCrowdsourcingCloud Computing and Database-as-a-ServiceDatabase Privacy, Security, and TrustData ScienceData Integration, Metadata Management, and InteroperabilityData Models, Semantics, Query languagesData Mining and Knowledge DiscoveryData Provenance, Workflows, Scientific Data ManagementData Stream Systems and Sensor NetworksData Visualization and Interactive Data ExplorationDistributed, Parallel and P2P Data ManagementHigh Performance Transaction ManagementInformation Extraction, Data Cleaning CurationModern Hardware and In-Memory Database SystemsQuery Processing, Indexing, and OptimizationScalable Analytics, Graph, RDF, Web Data and Social NetworksStrings, Texts, and Keyword SearchTemporal, Spatial, Mobile and Multimedia DataUncertain, Probabilistic and Approximate Databases


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Periodicals related to Query processing

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Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


Communications Letters, IEEE

Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Computer Graphics and Applications, IEEE

IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a strong combination of peer-reviewed feature articles and refereed departments, including news and product announcements. Special Applications sidebars relate research stories to commercial development. Cover stories focus on creative applications of the technology by an artist or ...


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Most published Xplore authors for Query processing

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Xplore Articles related to Query processing

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A join ordering approach for multicomputer relational databases with highly skewed data

1994 Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences, 1994

Multicomputer machines are currently used for many scientific applications. Recently, attention has been focused on the development of multicomputer database applications. The implementation efforts of database applications on parallel machines confront two fundamental obstacles; database applications are not regular, therefore, there is difficulty to extract any inherent parallelism; the participating relations can be highly skewed, thus causing unbalanced processor utilization. ...


A mini-track on parallel and distributed database systems: track coordinators' introduction

1994 Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences, 1994

The mini-track is organized as follows. Session 1, system overviews, takes a broad look at multidatabase style systems and tools for creating them. It shows how the various aspects of large scale databases fit together to provide a coherent global solution. Session 2, distributed query processing, explores efficient mechanisms for global query processing. It illustrates the functions and structures needed ...


On Producing High and Early Result Throughput in Multijoin Query Plans

IEEE Transactions on Knowledge and Data Engineering, 2011

This paper introduces an efficient framework for producing high and early result throughput in multijoin query plans. While most previous research focuses on optimizing for cases involving a single join operator, this work takes a radical step by addressing query plans with multiple join operators. The proposed framework consists of two main methods, a flush algorithm and operator state manager. ...


Device Database Systems

Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073), 2000

None


Establishing a fuzzy cost model for query optimization in a multidatabase system

1994 Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences, 1994

One of the challenges for query optimization in a multidatabase system (MDBS) is that some local optimization information may not be accurately known at the global level because of local autonomy. Traditional query optimization techniques using a crisp cost model may not be suitable for an MDBS because precise information as required. We present a new technique that performs query ...


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Educational Resources on Query processing

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IEEE-USA E-Books

  • A join ordering approach for multicomputer relational databases with highly skewed data

    Multicomputer machines are currently used for many scientific applications. Recently, attention has been focused on the development of multicomputer database applications. The implementation efforts of database applications on parallel machines confront two fundamental obstacles; database applications are not regular, therefore, there is difficulty to extract any inherent parallelism; the participating relations can be highly skewed, thus causing unbalanced processor utilization. We present the operation ordering segment of DOME, a query optimization environment developed on an Intel i860 hypercube system, that includes techniques to handle the above problems and provide efficient exploitation of the processing power. DOME uses a sampling approach, as part of the query execution process, to derive the statistical information of the relations at every level of a query execution tree. The operation ordering segment examines the statistical information and determines one efficient query execution tree, among many alternatives.<<ETX>>

  • A mini-track on parallel and distributed database systems: track coordinators' introduction

    The mini-track is organized as follows. Session 1, system overviews, takes a broad look at multidatabase style systems and tools for creating them. It shows how the various aspects of large scale databases fit together to provide a coherent global solution. Session 2, distributed query processing, explores efficient mechanisms for global query processing. It illustrates the functions and structures needed to provide good performance to global users. Session 3, query optimization, discusses different methods for optimizing global queries. Cost criteria, correctness aids, and the possibilities of hardware assists are presented. Session 4, aspects of distributed transactions, illustrates the uses and different paradigms associated with transaction processing in distributed databases and multidatabase systems. Session 5, fault tolerance, explores various aspects of preparing for and dealing with various faults in distributed databases and multidatabase systems.<<ETX>>

  • On Producing High and Early Result Throughput in Multijoin Query Plans

    This paper introduces an efficient framework for producing high and early result throughput in multijoin query plans. While most previous research focuses on optimizing for cases involving a single join operator, this work takes a radical step by addressing query plans with multiple join operators. The proposed framework consists of two main methods, a flush algorithm and operator state manager. The framework assumes a symmetric hash join, a common method for producing early results, when processing incoming data. In this way, our methods can be applied to a group of previous join operators (optimized for single-join queries) when taking part in multijoin query plans. Specifically, our framework can be applied by 1) employing a new flushing policy to write in-memory data to disk, once memory allotment is exhausted, in a way that helps increase the probability of producing early result throughput in multijoin queries, and 2) employing a state manager that adaptively switches operators in the plan between joining in-memory data and disk- resident data in order to positively affect the early result throughput. Extensive experimental results show that the proposed methods outperform the state-of-the-art join operators optimized for both single and multijoin query plans.

  • Device Database Systems

    None

  • Establishing a fuzzy cost model for query optimization in a multidatabase system

    One of the challenges for query optimization in a multidatabase system (MDBS) is that some local optimization information may not be accurately known at the global level because of local autonomy. Traditional query optimization techniques using a crisp cost model may not be suitable for an MDBS because precise information as required. We present a new technique that performs query optimization using a fuzzy cost model that allows fuzzy information. We discuss methods for establishing a fuzzy cost model and introduce two fuzzy optimization criteria that can be used with a fuzzy cost model. We illustrate the benefits of such fuzzy query optimization. We also analyze the computational complexity for the fuzzy query optimization approach and suggest a simple method to reduce the complexity.<<ETX>>

  • A Proxy-Based Approach to Continuous Location-Based Spatial Queries in Mobile Environments

    Caching valid regions of spatial queries at mobile clients is effective in reducing the number of queries submitted by mobile clients and query load on the server. However, mobile clients suffer from longer waiting time for the server to compute valid regions. We propose in this paper a proxy-based approach to continuous nearest-neighbor (NN) and window queries. The proxy creates estimated valid regions (EVRs) for mobile clients by exploiting spatial and temporal locality of spatial queries. For NN queries, we devise two new algorithms to accelerate EVR growth, leading the proxy to build effective EVRs even when the cache size is small. On the other hand, we propose to represent the EVRs of window queries in the form of vectors, called estimated window vectors (EWVs), to achieve larger estimated valid regions. This novel representation and the associated creation algorithm result in more effective EVRs of window queries. In addition, due to the distinct characteristics, we use separate index structures, namely EVR-tree and grid index, for NN queries and window queries, respectively. To further increase efficiency, we develop algorithms to exploit the results of NN queries to aid grid index growth, benefiting EWV creation of window queries. Similarly, the grid index is utilized to support NN query answering and EVR updating. We conduct several experiments for performance evaluation. The experimental results show that the proposed approach significantly outperforms the existing proxy-based approaches.

  • Clustering relations of large databases for parallel querying

    We discuss a technique for clustering relations for parallel querying in a distributed computing environment. Under the scheme, relations of relational database systems are grouped into clusters. Each cluster contains relations which are interrelated based on their primary-secondary key characteristics or commonality of their attributes/fields. Once grouped, the clusters are then distributed across a network of Sun SPARCstations, running the Parallel Virtual Machine (PVM) environment for parallel querying. The PVM system allows the total computing power of a collection of heterogeneous or homogeneous, computing processors to be harnessed for solving large problems. We have carried out parallel execution of SQL relational database queries using about 100 relations of a commercial application.<<ETX>>

  • Dynamic Data Exchange in Distributed RDF Stores

    When RDF datasets become too large to be managed by centralised systems, they are often distributed in a cluster of shared-nothing servers, and queries are answered using a distributed join algorithm. Although such solutions have been extensively studied in relational and RDF databases, we argue that existing approaches exhibit two drawbacks. First, they usually decide statically(i.e., at query compile time) how to shuffle the data, which can lead to missed opportunities for local computation. Second, they often materialise large intermediate relations whose size is determined by the entire dataset (and not the data stored in each server), so these relations can easily exceed the memory of individual servers. As a possible remedy, we present a novel distributed join algorithm for RDF. Our approach decides when to shuffle data dynamically, which ensures that query answers that can be wholly produced within a server involve only local computation. It also uses a novel flow control mechanism to ensure that every query can be answered even if each server has a bounded amount of memory that is much smaller than the intermediate relations. We complement our algorithm with a new query planning approach that balances the cost of communication against the cost of local processing at each server. Moreover, as in several existing approaches, we distribute RDF data using graph partitioning so as to maximise local computation, but we refine the partitioning algorithm to produce more balanced partitions. We show empirically that our techniques can outperform the state of the art by orders of magnitude in terms of query evaluation times, network communication, and memory use. In particular, bounding the memory use in individual servers can mean the difference between success and failure for answering queries with large answer sets.

  • Semantic query optimization in heterogeneous DBMSs

    Semantic query optimization is the process of transforming a query issued by a user into a different query which, because of the semantics of the application, is guaranteed to yield the correct answer for all states of the database. While this process has been successfully applied in centralised databases, its potential for distributed and heterogeneous systems is enormous, as there is the potential to eliminate inter-site joins which are the single biggest cost factor in query processing. Further justification for its use is provided by the fact that users of heterogeneous databases typically issue queries through high-level languages which may result in very inefficient queries if mapped directly, without consideration of the semantics of the system. Even if this is not the case, users cannot be expected to be familiar with the semantics of the component databases, and may consequently issue queries which are unnecessarily complicated. We present the design of a semantic query optimizer for a heterogeneous database management system. It is based on an extension of a centralised implementation which focuses on finding a "near optimal" query that can be derived quickly. The semantics of the application are represented as a relational database and algorithms are defined which access this database to perform transformations to the query.<<ETX>>

  • Distributed join processing performance evaluation

    Efficient join acceleration methods that combine hybrid hashing, join indices and domain vectors with semi-join techniques to accelerate distributed joins are developed. An analytic performance model which allows for parallel execution of the methods at each join site is developed to compare the total task duration time of the methods. The methods are compared over a wide range of memory sizes, semijoin selectivities and network transmission speeds. The distributed join index method performs well if memory size is large and selectivity is low. The distributed hybrid hash method always has the advantage that it requires no residual data to be stored between runs, however performance is poor at low network transmission rates due to high pre-semijoin transmission requirements. The distributed domain vector hash method performs well in high selectivity conditions.<<ETX>>



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