Mobility-supporting data management for location-based mobile systems: the special case of single category location repositories

James E. Wyse
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Abstract

Location-based mobile applications require timely generation of user-centric proximities from application-relevant repositories of business locations. The proximity generation requirement is poorly served by conventional query resolution methods which are prone to response time degradation as repositories experience growth. This article reports research on a location-aware method (LAM) specifically devised to resolve queries for rapid proximity generation. Three operational concerns performance, scalability, and manageability provide a basis on which a specific form of LAM, linkcell-based LAM, is examined. Previous evaluative work on linkcell-based LAM focused on multiple category repositories (MCRs) in which business locations are explicitly classified using a predefined set of business categories. The research reported here concerns single category repositories (SCRs), an important special case in which no predefined set of business categories is used. Results show how a reformulated location-aware method may be used to manage SCRs and suggest the means by which scalability is achieved and proximity generation performance is optimised.
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基于位置的移动系统的支持移动性的数据管理:单一类别位置存储库的特殊情况
基于位置的移动应用程序需要从与应用程序相关的业务位置存储库中及时生成以用户为中心的邻近位置。传统的查询解析方法不能很好地满足邻近生成需求,随着存储库的增长,这种方法容易导致响应时间下降。本文报告了一种位置感知方法(LAM)的研究,该方法专门用于解析快速邻近生成的查询。性能、可伸缩性和可管理性三个操作关注点为研究特定形式的LAM(基于链接单元的LAM)提供了基础。先前对基于链接单元的LAM的评估工作侧重于多类别存储库(mcr),其中使用预定义的业务类别集显式地对业务位置进行分类。这里报告的研究涉及单类别存储库(scr),这是一个重要的特殊情况,其中不使用预定义的业务类别集。结果显示了如何使用重新制定的位置感知方法来管理scr,并提出了实现可扩展性和优化邻近生成性能的方法。
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