The Experts below are selected from a list of 208854 Experts worldwide ranked by ideXlab platform
Yan Shi - One of the best experts on this subject based on the ideXlab platform.
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Data Retrieval Scheduling for Multi-Item Requests in Multi-Channel WirelessBroadcast Environments
IEEE Transactions on Mobile Computing, 2014Co-Authors: Yan ShiAbstract:Wireless Data broadcast is a popular Data dissemination method in mobile computing environments because of its capability of concurrently disseminating Data to multiple users. In this paper, we study the Data Retrieval scheduling problem for multi-item requests in multi-channel broadcast environments. To maximize the number of downloads given a deadline, we define a problem called largest number Data Retrieval (LNDR). We prove the decision problem of LNDR is NP-hard, and we investigate approximation algorithm for it. We also define another problem called minimum cost Data Retrieval (MCDR), which aims at downloading a set of requested Data items with the least response time and energy consumption. We prove MCDR is NP-hard to approximate to within any non-trivial factor. Therefore, we investigate heuristic algorithm for it. Finally we provide simulation results to demonstrate the practical efficiency of the proposed algorithms.
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Efficient Parallel Data Retrieval Protocols with MIMO Antennae for Data Broadcast in 4G Wireless Communications
Database and Expert Systems Applications, 2010Co-Authors: Yan Shi, Jiaofei Zhong, Xiaofeng Gao, Weili WuAbstract:Wireless Data Broadcast is an efficient Data dissemination method for public information to a large number of mobile/wireless clients. With the advance of the fourth-generation wireless communication system (4G), mobile devices may embed multiple-input multiple-output (MIMO) antennae to setup multi-connections to a base station. In this paper, we deal with Data Retrieval problem for mobile clients with MIMO antennae to retrieve a set of indexed Data from parallel communication channels. Our purpose is to construct fast and energy efficient Data Retrieval protocols to reduce the response time and energy consumption. We name this problem as parallel Data Retrieval scheduling with MIMO Antennae (PADRS-MIMO), and propose two greedy heuristics named Least Switch Data Retrieval Protocol (Least-Switch) and Best First Data Retrieval Protocol (Best-First). We are the first work to deal with Data Retrieval with MIMO antennae for wireless Data broadcast. We analyze the performances of Least-Switch and Best-First both theoretically and practically. Simulation results prove the efficiency of the two protocols.
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DEXA (2) - Efficient parallel Data Retrieval protocols with MIMO antennae for Data broadcast in 4G wireless communications
Lecture Notes in Computer Science, 2010Co-Authors: Yan Shi, Xiaofeng Gao, Jiaofei ZhongAbstract:Wireless Data Broadcast is an efficient Data dissemination method for public information to a large number of mobile/wireless clients. With the advance of the fourth-generation wireless communication system (4G), mobile devices may embed multiple-input multiple-output (MIMO) antennae to setup multi-connections to a base station. In this paper, we deal with Data Retrieval problem for mobile clients with MIMO antennae to retrieve a set of indexed Data from parallel communication channels. Our purpose is to construct fast and energy efficient Data Retrieval protocols to reduce the response time and energy consumption. We name this problem as parallel Data Retrieval scheduling with MIMO Antennae (PADRS-MIMO), and propose two greedy heuristics named Least Switch Data Retrieval Protocol (Least-Switch) and Best First Data Retrieval Protocol (Best-First). We are the first work to deal with Data Retrieval with MIMO antennae for wireless Data broadcast. We analyze the performances of Least-Switch and Best-First both theoretically and practically. Simulation results prove the efficiency of the two protocols.
Ela Hunt - One of the best experts on this subject based on the ideXlab platform.
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Improved Data Retrieval from TreeBASE via taxonomic and linguistic Data enrichment
BMC Evolutionary Biology, 2009Co-Authors: Nadia Anwar, Ela HuntAbstract:Background TreeBASE, the only Data repository for phylogenetic studies, is not being used effectively since it does not meet the taxonomic Data Retrieval requirements of the systematics community. We show, through an examination of the queries performed on TreeBASE, that Data Retrieval using taxon names is unsatisfactory. Results We report on a new wrapper supporting taxon queries on TreeBASE by utilising a Taxonomy and Classification Database (TCl-Db) we created. TCl-Db holds merged and consolidated taxonomic names from multiple Data sources and can be used to translate hierarchical, vernacular and synonym queries into specific query terms in TreeBASE. The query expansion supported by TCl-Db shows very significant information Retrieval quality improvement. The wrapper can be accessed at the URL http://spira.zoology.gla.ac.uk/app/tbasewrapper.php The methodology we developed is scalable and can be applied to new Data, as those become available in the future. Conclusion Significantly improved Data Retrieval quality is shown for all queries, and additional flexibility is achieved via user-driven taxonomy selection.
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Improved Data Retrieval from TreeBASE via taxonomic and linguistic Data enrichment
BMC Evolutionary Biology, 2009Co-Authors: Nadia Anwar, Ela HuntAbstract:Background TreeBASE, the only Data repository for phylogenetic studies, is not being used effectively since it does not meet the taxonomic Data Retrieval requirements of the systematics community. We show, through an examination of the queries performed on TreeBASE, that Data Retrieval using taxon names is unsatisfactory.
G.k.v. Narasimha Reddy - One of the best experts on this subject based on the ideXlab platform.
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Data Retrieval for Decentralized Tolerant Military Networks
International Journal of Research, 2015Co-Authors: Z. Mallikarjuna Reddy, G.k.v. Narasimha ReddyAbstract:In this paper, we propose a secure Data Retrieval scheme using CP-ABE for decentralized DTNs where multiple key authorities manage their attributes independently. We demonstrate how to apply the proposed mechanism to securely and efficiently manage the confidential Data distributed in the disruption-tolerant military network.
Jiaofei Zhong - One of the best experts on this subject based on the ideXlab platform.
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Efficient Parallel Data Retrieval Protocols with MIMO Antennae for Data Broadcast in 4G Wireless Communications
Database and Expert Systems Applications, 2010Co-Authors: Yan Shi, Jiaofei Zhong, Xiaofeng Gao, Weili WuAbstract:Wireless Data Broadcast is an efficient Data dissemination method for public information to a large number of mobile/wireless clients. With the advance of the fourth-generation wireless communication system (4G), mobile devices may embed multiple-input multiple-output (MIMO) antennae to setup multi-connections to a base station. In this paper, we deal with Data Retrieval problem for mobile clients with MIMO antennae to retrieve a set of indexed Data from parallel communication channels. Our purpose is to construct fast and energy efficient Data Retrieval protocols to reduce the response time and energy consumption. We name this problem as parallel Data Retrieval scheduling with MIMO Antennae (PADRS-MIMO), and propose two greedy heuristics named Least Switch Data Retrieval Protocol (Least-Switch) and Best First Data Retrieval Protocol (Best-First). We are the first work to deal with Data Retrieval with MIMO antennae for wireless Data broadcast. We analyze the performances of Least-Switch and Best-First both theoretically and practically. Simulation results prove the efficiency of the two protocols.
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DEXA (2) - Efficient parallel Data Retrieval protocols with MIMO antennae for Data broadcast in 4G wireless communications
Lecture Notes in Computer Science, 2010Co-Authors: Yan Shi, Xiaofeng Gao, Jiaofei ZhongAbstract:Wireless Data Broadcast is an efficient Data dissemination method for public information to a large number of mobile/wireless clients. With the advance of the fourth-generation wireless communication system (4G), mobile devices may embed multiple-input multiple-output (MIMO) antennae to setup multi-connections to a base station. In this paper, we deal with Data Retrieval problem for mobile clients with MIMO antennae to retrieve a set of indexed Data from parallel communication channels. Our purpose is to construct fast and energy efficient Data Retrieval protocols to reduce the response time and energy consumption. We name this problem as parallel Data Retrieval scheduling with MIMO Antennae (PADRS-MIMO), and propose two greedy heuristics named Least Switch Data Retrieval Protocol (Least-Switch) and Best First Data Retrieval Protocol (Best-First). We are the first work to deal with Data Retrieval with MIMO antennae for wireless Data broadcast. We analyze the performances of Least-Switch and Best-First both theoretically and practically. Simulation results prove the efficiency of the two protocols.
Nadia Anwar - One of the best experts on this subject based on the ideXlab platform.
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Improved Data Retrieval from TreeBASE via taxonomic and linguistic Data enrichment
BMC Evolutionary Biology, 2009Co-Authors: Nadia Anwar, Ela HuntAbstract:Background TreeBASE, the only Data repository for phylogenetic studies, is not being used effectively since it does not meet the taxonomic Data Retrieval requirements of the systematics community. We show, through an examination of the queries performed on TreeBASE, that Data Retrieval using taxon names is unsatisfactory. Results We report on a new wrapper supporting taxon queries on TreeBASE by utilising a Taxonomy and Classification Database (TCl-Db) we created. TCl-Db holds merged and consolidated taxonomic names from multiple Data sources and can be used to translate hierarchical, vernacular and synonym queries into specific query terms in TreeBASE. The query expansion supported by TCl-Db shows very significant information Retrieval quality improvement. The wrapper can be accessed at the URL http://spira.zoology.gla.ac.uk/app/tbasewrapper.php The methodology we developed is scalable and can be applied to new Data, as those become available in the future. Conclusion Significantly improved Data Retrieval quality is shown for all queries, and additional flexibility is achieved via user-driven taxonomy selection.
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Improved Data Retrieval from TreeBASE via taxonomic and linguistic Data enrichment
BMC Evolutionary Biology, 2009Co-Authors: Nadia Anwar, Ela HuntAbstract:Background TreeBASE, the only Data repository for phylogenetic studies, is not being used effectively since it does not meet the taxonomic Data Retrieval requirements of the systematics community. We show, through an examination of the queries performed on TreeBASE, that Data Retrieval using taxon names is unsatisfactory.
