Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320096
M. Stonebraker
For this closing panel discussion, we will recruit a collection of participants from the attendees and organizers. Each will agree to present one or more outrageous ideas that are too wacky to get funded and/or incapable of being turned into least-publishable units (LPUs). Less adventuresome panelists can present their pet peeve about research activities pursued by other in the DBMS community. Risk averse panelists can discuss more mundane problems which they would like to work on if they had more time or were excused from department committees.
{"title":"Outrageous ideas and/or thoughts while shaving","authors":"M. Stonebraker","doi":"10.1109/ICDE.2004.1320096","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320096","url":null,"abstract":"For this closing panel discussion, we will recruit a collection of participants from the attendees and organizers. Each will agree to present one or more outrageous ideas that are too wacky to get funded and/or incapable of being turned into least-publishable units (LPUs). Less adventuresome panelists can present their pet peeve about research activities pursued by other in the DBMS community. Risk averse panelists can discuss more mundane problems which they would like to work on if they had more time or were excused from department committees.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132163238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320023
Haifeng Liu, H. Jacobsen
In the publish/subscribe paradigm, information providers disseminate publications to all consumers who have expressed interest by registering subscriptions. This paradigm has found wide-spread applications, ranging from selective information dissemination to network management. However, all existing publish/subscribe systems cannot capture uncertainty inherent to the information in either subscriptions or publications. In many situations, exact knowledge of either specific subscriptions or publications is not available. Moreover, especially in selective information dissemination applications, it is often more appropriate for a user to formulate her search requests or information offers in less precise terms, rather than defining a sharp limit. To address these problems, this paper proposes a new publish/subscribe model based on possibility theory and fuzzy set theory to process uncertainties for both subscriptions and publications. Furthermore, an approximate publish/subscribe matching problem is defined and algorithms for solving it are developed and evaluated.
{"title":"Modeling uncertainties in publish/subscribe systems","authors":"Haifeng Liu, H. Jacobsen","doi":"10.1109/ICDE.2004.1320023","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320023","url":null,"abstract":"In the publish/subscribe paradigm, information providers disseminate publications to all consumers who have expressed interest by registering subscriptions. This paradigm has found wide-spread applications, ranging from selective information dissemination to network management. However, all existing publish/subscribe systems cannot capture uncertainty inherent to the information in either subscriptions or publications. In many situations, exact knowledge of either specific subscriptions or publications is not available. Moreover, especially in selective information dissemination applications, it is often more appropriate for a user to formulate her search requests or information offers in less precise terms, rather than defining a sharp limit. To address these problems, this paper proposes a new publish/subscribe model based on possibility theory and fuzzy set theory to process uncertainties for both subscriptions and publications. Furthermore, an approximate publish/subscribe matching problem is defined and algorithms for solving it are developed and evaluated.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116915691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320046
Bernhard Zeller, A. Kemper
According to a survey of the University of Berkeley [P. Lyman et al., (2003)], about 5 Exabytes of new information has been created in 2002. This information explosion affects also the database volumes of enterprise resource planning (ERP) systems like SAP R/3, the market leader for ERP systems. Just like the overall information explosion, the database volumes of ERP systems are growing at a tremendous rate and some of them have reached a size of several Terabytes. OLTP (online transaction processing) databases of this size are hard to maintain and tend to perform poorly. One way to limit the size of a database is data staging, i.e., to make use of an SAP technique called archiving. That is, data which are not needed for every-day operations are demoted from the database (disks) to tertiary storage (tapes). In cooperation with our research group, SAP is adapting their archiving techniques to accelerate the archiving process by integrating new technologies like XML and advanced database features. However, so far no benchmark existed to evaluate different archiving scenarios and to measure the impact of a change in the archiving technique. We therefore designed and implemented a generic benchmark which is applicable to many different system layouts and allows the users to evaluate various archiving scenarios.
根据伯克利大学的一项调查[P.]Lyman et al.，(2003)]， 2002年创造了大约5eb的新信息。这种信息爆炸也影响了企业资源规划(ERP)系统的数据库容量，如ERP系统的市场领导者SAP R/3。就像整个信息爆炸一样，ERP系统的数据库量也在以惊人的速度增长，其中一些已经达到了几tb的大小。这种规模的OLTP(在线事务处理)数据库很难维护，而且往往表现不佳。限制数据库大小的一种方法是数据分段，即利用一种称为归档的SAP技术。也就是说，将日常操作不需要的数据从数据库(磁盘)降级到三级存储(磁带)。SAP正在与我们的研究小组合作，通过集成新技术(如XML和高级数据库特性)来调整他们的归档技术，以加速归档过程。然而，到目前为止，还没有基准来评估不同的归档场景和度量归档技术变更的影响。因此，我们设计并实现了一个通用基准测试，它适用于许多不同的系统布局，并允许用户评估各种归档场景。
{"title":"Benchmarking SAP R/3 archiving scenarios","authors":"Bernhard Zeller, A. Kemper","doi":"10.1109/ICDE.2004.1320046","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320046","url":null,"abstract":"According to a survey of the University of Berkeley [P. Lyman et al., (2003)], about 5 Exabytes of new information has been created in 2002. This information explosion affects also the database volumes of enterprise resource planning (ERP) systems like SAP R/3, the market leader for ERP systems. Just like the overall information explosion, the database volumes of ERP systems are growing at a tremendous rate and some of them have reached a size of several Terabytes. OLTP (online transaction processing) databases of this size are hard to maintain and tend to perform poorly. One way to limit the size of a database is data staging, i.e., to make use of an SAP technique called archiving. That is, data which are not needed for every-day operations are demoted from the database (disks) to tertiary storage (tapes). In cooperation with our research group, SAP is adapting their archiving techniques to accelerate the archiving process by integrating new technologies like XML and advanced database features. However, so far no benchmark existed to evaluate different archiving scenarios and to measure the impact of a change in the archiving technique. We therefore designed and implemented a generic benchmark which is applicable to many different system layouts and allows the users to evaluate various archiving scenarios.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115469387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320055
N. Agrawal, Rema Ananthanarayanan, Rahul Gupta, Sachindra Joshi, R. Krishnapuram, Sumit Negi
Data presented on commerce sites runs into thousands of pages, and is typically delivered from multiple back-end sources. This makes it difficult to identify incorrect, anomalous, or interesting data such as $9.99 air fares, missing links, drastic changes in prices and addition of new products or promotions. We describe a system that monitors Web sites automatically and generates various types of reports so that the content of the site can be monitored and the quality maintained. The solution designed and implemented by us consists of a site crawler that crawls dynamic pages, an information miner that learns to extract useful information from the pages based on examples provided by the user, and a reporter that can be configured by the user to answer specific queries. The tool can also be used for identifying price trends and new products or promotions at competitor sites. A pilot run of the tool has been successfully completed at the ibm.com site.
{"title":"EShopMonitor: a Web content monitoring tool","authors":"N. Agrawal, Rema Ananthanarayanan, Rahul Gupta, Sachindra Joshi, R. Krishnapuram, Sumit Negi","doi":"10.1109/ICDE.2004.1320055","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320055","url":null,"abstract":"Data presented on commerce sites runs into thousands of pages, and is typically delivered from multiple back-end sources. This makes it difficult to identify incorrect, anomalous, or interesting data such as $9.99 air fares, missing links, drastic changes in prices and addition of new products or promotions. We describe a system that monitors Web sites automatically and generates various types of reports so that the content of the site can be monitored and the quality maintained. The solution designed and implemented by us consists of a site crawler that crawls dynamic pages, an information miner that learns to extract useful information from the pages based on examples provided by the user, and a reporter that can be configured by the user to answer specific queries. The tool can also be used for identifying price trends and new products or promotions at competitor sites. A pilot run of the tool has been successfully completed at the ibm.com site.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114147527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320010
Brian Babcock, Mayur Datar, R. Motwani
Systems for processing continuous monitoring queries over data streams must be adaptive because data streams are often bursty and data characteristics may vary over time. We focus on one particular type of adaptivity: the ability to gracefully degrade performance via "load shedding" (dropping unprocessed tuples to reduce system load) when the demands placed on the system cannot be met in full given available resources. Focusing on aggregation queries, we present algorithms that determine at what points in a query plan should load shedding be performed and what amount of load should be shed at each point in order to minimize the degree of inaccuracy introduced into query answers. We report the results of experiments that validate our analytical conclusions.
{"title":"Load shedding for aggregation queries over data streams","authors":"Brian Babcock, Mayur Datar, R. Motwani","doi":"10.1109/ICDE.2004.1320010","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320010","url":null,"abstract":"Systems for processing continuous monitoring queries over data streams must be adaptive because data streams are often bursty and data characteristics may vary over time. We focus on one particular type of adaptivity: the ability to gracefully degrade performance via \"load shedding\" (dropping unprocessed tuples to reduce system load) when the demands placed on the system cannot be met in full given available resources. Focusing on aggregation queries, we present algorithms that determine at what points in a query plan should load shedding be performed and what amount of load should be shed at each point in order to minimize the degree of inaccuracy introduced into query answers. We report the results of experiments that validate our analytical conclusions.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126628693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320069
Alin Deutsch, Y. Papakonstantinou, Yu Xu
We extend tree pattern queries into group-by normal form tree pattern (GNFTP) queries, which are nested, perform arbitrary joins, and freely mix bag and set semantics. Here, we describe a subset of XQuery, called OptXQuery and provide a normalization algorithm that rewrites any OptXQuery into a GNFTP query. Key logical query optimizations can be solved for GNFTP/OptXQuery. As a proof-of-concept but also for its own importance and value in query optimization, we developed and evaluated a query minimization algorithm for GNFTP. The rich features of GN-FTP/OptXQuery create key challenges that fundamentally extend the prior work on the problems of minimizing conjunctive queries. An important application of this technique is group-by detection. We extend GNFTP into extGNFTP to capture XQueries outside the OptXQuery set. The extGNFTP notation provides the logical plan optimization framework of our XQuery processor.
{"title":"Minimization and group-by detection for nested XQueries","authors":"Alin Deutsch, Y. Papakonstantinou, Yu Xu","doi":"10.1109/ICDE.2004.1320069","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320069","url":null,"abstract":"We extend tree pattern queries into group-by normal form tree pattern (GNFTP) queries, which are nested, perform arbitrary joins, and freely mix bag and set semantics. Here, we describe a subset of XQuery, called OptXQuery and provide a normalization algorithm that rewrites any OptXQuery into a GNFTP query. Key logical query optimizations can be solved for GNFTP/OptXQuery. As a proof-of-concept but also for its own importance and value in query optimization, we developed and evaluated a query minimization algorithm for GNFTP. The rich features of GN-FTP/OptXQuery create key challenges that fundamentally extend the prior work on the problems of minimizing conjunctive queries. An important application of this technique is group-by detection. We extend GNFTP into extGNFTP to capture XQueries outside the OptXQuery set. The extGNFTP notation provides the logical plan optimization framework of our XQuery processor.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124702086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320066
K. Murthy, H. Kriegel, Stefan Schönauer, T. Seidl
We implemented our new approach for efficient similarity search in large databases of tree structures. Our experiments show that filtering significantly accelerates the complex task of similarity search for tree-structured objects. Moreover, they show that no single feature of a tree is sufficient for effective filtering, but only the combination of structural and content-based filters yields good results.
{"title":"Efficient similarity search in large databases of tree structured objects","authors":"K. Murthy, H. Kriegel, Stefan Schönauer, T. Seidl","doi":"10.1109/ICDE.2004.1320066","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320066","url":null,"abstract":"We implemented our new approach for efficient similarity search in large databases of tree structures. Our experiments show that filtering significantly accelerates the complex task of similarity search for tree-structured objects. Moreover, they show that no single feature of a tree is sufficient for effective filtering, but only the combination of structural and content-based filters yields good results.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"93 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124795193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320008
Naresh Neelapala, Romil Mittal, J. Haritsa
The indexing technique commonly used for long strings, such as genomes, is the suffix tree, which is based on a vertical (intra-path) compaction of the underlying trie structure. We investigate an alternative approach to index building, based on horizontal (inter-path) compaction of the trie. In particular, we present SPINE, a carefully engineered horizontally-compacted trie index. SPINE consists of a backbone formed by a linear chain of nodes representing the underlying string, with the nodes connected by a rich set of edges for facilitating fast forward and backward traversals over the backbone during index construction and query search. A special feature of SPINE is that it collapses the trie into a linear structure, representing the logical extreme of horizontal compaction. We describe algorithms for SPINE construction and for searching this index to find the occurrences of query patterns. Our experimental results on a variety of real genomic and proteomic strings show that SPINE requires significantly less space than standard implementations of suffix trees. Further, SPINE takes lesser time for both construction and search as compared to suffix trees, especially when the index is disk-resident. Finally, the linearity of its structure makes it more amenable for integration with database engines.
{"title":"SPINE: putting backbone into string indexing","authors":"Naresh Neelapala, Romil Mittal, J. Haritsa","doi":"10.1109/ICDE.2004.1320008","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320008","url":null,"abstract":"The indexing technique commonly used for long strings, such as genomes, is the suffix tree, which is based on a vertical (intra-path) compaction of the underlying trie structure. We investigate an alternative approach to index building, based on horizontal (inter-path) compaction of the trie. In particular, we present SPINE, a carefully engineered horizontally-compacted trie index. SPINE consists of a backbone formed by a linear chain of nodes representing the underlying string, with the nodes connected by a rich set of edges for facilitating fast forward and backward traversals over the backbone during index construction and query search. A special feature of SPINE is that it collapses the trie into a linear structure, representing the logical extreme of horizontal compaction. We describe algorithms for SPINE construction and for searching this index to find the occurrences of query patterns. Our experimental results on a variety of real genomic and proteomic strings show that SPINE requires significantly less space than standard implementations of suffix trees. Further, SPINE takes lesser time for both construction and search as compared to suffix trees, especially when the index is disk-resident. Finally, the linearity of its structure makes it more amenable for integration with database engines.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131349950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320098
I. Fundulaki, R. Hull, B. Kumar, D. Lieuwen, Arnaud Sahuguet
The web services paradigm holds the promise of tremendous flexibility in how services are combined to meet the needs of individual end-users. The “convergence” of networks (wireline telephony, wireless, data) further enhances the web services paradigm, by enabling the incorporation of real time contextual information (e.g., presence and location) along with opportunities for web services to impact the physical world more immediately (e.g., a vending machine delivering a soda based on a purchase via a cell phone). But it will not be possible for most end-users to enjoy the rich and intricate possibilities, unless a broad variety of personalization technologies are available and respect the end user’s legitimate need for privacy. This seminar begins with examples illustrating why personalization will be so important for the emerging web and converged services. The main body of the seminar focuses on 3 inter-related technologies. First is profile data management, the ability for services to share and access end-user profile data (including address, credit card, “simple” preferences, current location, current presence, ...) as appropriate for the services to be provided. Second is preference and policy management, the ability to store and execute on intricate, interrelated preferences that end-users may have (e.g., “during working hours, calls from strangers should be routed to voice-mail”; “I usually work from 9 to 6, but on Thursdays it is from 8 to 4”; ...). And third is personalized and privacy-conscious data sharing of profile data and preferences, the notion that an end-user should have complete control over what profile and preference data is shared with whom and under what circumstances and how it is interpreted. In addition to describing emerging approaches for providing these capabilities, the seminar will describe how to add value to applications by using personalization, from both the end-user and the application provider perspectives.
{"title":"\"My personal web\": a seminar on personalization and privacy for web and converged services","authors":"I. Fundulaki, R. Hull, B. Kumar, D. Lieuwen, Arnaud Sahuguet","doi":"10.1109/ICDE.2004.1320098","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320098","url":null,"abstract":"The web services paradigm holds the promise of tremendous flexibility in how services are combined to meet the needs of individual end-users. The “convergence” of networks (wireline telephony, wireless, data) further enhances the web services paradigm, by enabling the incorporation of real time contextual information (e.g., presence and location) along with opportunities for web services to impact the physical world more immediately (e.g., a vending machine delivering a soda based on a purchase via a cell phone). But it will not be possible for most end-users to enjoy the rich and intricate possibilities, unless a broad variety of personalization technologies are available and respect the end user’s legitimate need for privacy. This seminar begins with examples illustrating why personalization will be so important for the emerging web and converged services. The main body of the seminar focuses on 3 inter-related technologies. First is profile data management, the ability for services to share and access end-user profile data (including address, credit card, “simple” preferences, current location, current presence, ...) as appropriate for the services to be provided. Second is preference and policy management, the ability to store and execute on intricate, interrelated preferences that end-users may have (e.g., “during working hours, calls from strangers should be routed to voice-mail”; “I usually work from 9 to 6, but on Thursdays it is from 8 to 4”; ...). And third is personalized and privacy-conscious data sharing of profile data and preferences, the notion that an end-user should have complete control over what profile and preference data is shared with whom and under what circumstances and how it is interpreted. In addition to describing emerging approaches for providing these capabilities, the seminar will describe how to add value to applications by using personalization, from both the end-user and the application provider perspectives.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124637516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320071
Gary Kratkiewicz, R. Bostwick, Geoffrey S. Knauth
Models and simulations for analyzing difficult real-world problems often deal with massive amounts of data. The data problem is compounded when the analysis must be repeatedly run to perform what-if analyses. One such model is the Integrated Consumable Item Support (ICIS) Model developed for the U.S. Defense Logistics Agency (DLA). It models DLA's ability to satisfy future wartime requirements for parts, fuel, and food. ICIS uses a number of computation modules to project demands, model sourcing, and identify potential problem items for various commodities and military services. These modules are written in a variety of computer languages and must work together to generate an ICIS analysis.
{"title":"Efficient execution of computation modules in a model with massive data","authors":"Gary Kratkiewicz, R. Bostwick, Geoffrey S. Knauth","doi":"10.1109/ICDE.2004.1320071","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320071","url":null,"abstract":"Models and simulations for analyzing difficult real-world problems often deal with massive amounts of data. The data problem is compounded when the analysis must be repeatedly run to perform what-if analyses. One such model is the Integrated Consumable Item Support (ICIS) Model developed for the U.S. Defense Logistics Agency (DLA). It models DLA's ability to satisfy future wartime requirements for parts, fuel, and food. ICIS uses a number of computation modules to project demands, model sourcing, and identify potential problem items for various commodities and military services. These modules are written in a variety of computer languages and must work together to generate an ICIS analysis.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129507539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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