计算机研究与发展
計算機研究與髮展
계산궤연구여발전
Journal of Computer Research and Development
2015年
9期
2002-2013
,共12页
移动对象索引%室内环境%范围查询%轨迹查询%室内图模型
移動對象索引%室內環境%範圍查詢%軌跡查詢%室內圖模型
이동대상색인%실내배경%범위사순%궤적사순%실내도모형
moving object index%indoor space%range query%trajectory query%indoor graph-based m o del
随着室内定位技术的广泛应用，室内位置服务快速发展。移动对象索引技术作为支撑位置服务的核心技术，大多数都基于室外环境，难以直接应用于室内空间。现有的室内移动对象索引，仅关注对移动对象历史数据的查询，且支持的查询类型单一。为此，提出MQII（multiple queries indoor index）索引结构，对移动对象历史和当前位置信息进行索引，能够同时支持对象位置查询、轨迹查询以及时空范围查询。索引采用对象链表和桶链表结构，实现从对象和时空范围2个方面对移动对象数据的管理；提出针对该索引结构的有效更新、查询算法；实验结果表明，与现有室内移动对象索引相比，索引不仅能够支持历史查询和当前查询，还能够同时高效支持对象位置查询、轨迹查询和范围查询。该方法可应用于办公楼、医院等多种室内空间。
隨著室內定位技術的廣汎應用，室內位置服務快速髮展。移動對象索引技術作為支撐位置服務的覈心技術，大多數都基于室外環境，難以直接應用于室內空間。現有的室內移動對象索引，僅關註對移動對象歷史數據的查詢，且支持的查詢類型單一。為此，提齣MQII（multiple queries indoor index）索引結構，對移動對象歷史和噹前位置信息進行索引，能夠同時支持對象位置查詢、軌跡查詢以及時空範圍查詢。索引採用對象鏈錶和桶鏈錶結構，實現從對象和時空範圍2箇方麵對移動對象數據的管理；提齣針對該索引結構的有效更新、查詢算法；實驗結果錶明，與現有室內移動對象索引相比，索引不僅能夠支持歷史查詢和噹前查詢，還能夠同時高效支持對象位置查詢、軌跡查詢和範圍查詢。該方法可應用于辦公樓、醫院等多種室內空間。
수착실내정위기술적엄범응용，실내위치복무쾌속발전。이동대상색인기술작위지탱위치복무적핵심기술，대다수도기우실외배경，난이직접응용우실내공간。현유적실내이동대상색인，부관주대이동대상역사수거적사순，차지지적사순류형단일。위차，제출MQII（multiple queries indoor index）색인결구，대이동대상역사화당전위치신식진행색인，능구동시지지대상위치사순、궤적사순이급시공범위사순。색인채용대상련표화통련표결구，실현종대상화시공범위2개방면대이동대상수거적관리；제출침대해색인결구적유효경신、사순산법；실험결과표명，여현유실내이동대상색인상비，색인불부능구지지역사사순화당전사순，환능구동시고효지지대상위치사순、궤적사순화범위사순。해방법가응용우판공루、의원등다충실내공간。
Moving object index is widely used in location‐based services .Since people spend large parts of their lives in indoor spaces (e .g .hospitals ,shopping malls ,subw ay systems ,etc .) ,effective management of indoor mobile data becomes very important . Existing indoor moving object indices focus on historical data queries ,and only one type of queries is supported .In this paper ,we propose a novel index ,called M QII (multiple queries indoor index ) ,w hich supports not only history queries and present queries ,but also object queries and range queries .M QII is based on graph‐based model , and can index two aspects with the object list and bucket list structure ,such as the object and spatial‐temporal scales .In order to improve the query performance ,we present a RFID (radio frequency identification) data preprocessing method to reduce the size of the input data sets for M QII . Furthermore ,effective update and query algorithms are developed .Experimental results show that compared with existing indoor moving object indices ,the data preprocessing can reduce the amount of data .In addition ,the index we proposed not only supports history queries and present queries ,but also provides efficient object location queries ,trajectory queries and range queries .This method can be used in various indoor spaces such as office buildings ,hospitals and hotels .
