Approximate algorithms for static and continuous range queries in mobile navigation
For many years, spatial range search has been applied to computational geometry and multimedia problems to find interest objects within a given radius. Range search query has traditionally been used to return all objects within a given radius. However, having all objects is not necessary, especially...
Gespeichert in:
| Veröffentlicht in: | Computing Jg. 95; H. 10-11; S. 949 - 976 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Vienna
Springer Vienna
01.10.2013
Springer Nature B.V |
| Schlagworte: | |
| ISSN: | 0010-485X, 1436-5057 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | For many years, spatial range search has been applied to computational geometry and multimedia problems to find interest objects within a given radius. Range search query has traditionally been used to return all objects within a given radius. However, having
all
objects is not necessary, especially when there are already enough objects closer to the query point. Furthermore, expanding the radius may give users better results, especially when there are a lot of objects just outside the search boundary. Therefore, in this paper, we focus on
approximate
range search, where the query results are approximate, rather than exact. We propose
approximate static range search (ARS)
which combines two approaches, namely (i)
lowerbound approximate range search
, and (ii)
upperbound approximate range search
. Using
ARS
, we are able to deliver a better performance, together with low false hit and reasonable false miss. We also extend
ARS
in the context of a continuous query setting, in which the query moves. This is particularly important in spatial databases as a mobile user who invokes the query is moving. In terms of continuous range search, the intention is to find split points—the locations where the query results will be updated. Accordingly, we propose two methods for
approximate continuous range search
, namely (i)
range search minimization
, and (ii)
split points minimization
. Our performance evaluation which compares our methods with the traditional continuous range search shows that our methods considerably reduce the number of split points, thereby improving overall performance. |
|---|---|
| AbstractList | For many years, spatial range search has been applied to computational geometry and multimedia problems to find interest objects within a given radius. Range search query has traditionally been used to return all objects within a given radius. However, having all objects is not necessary, especially when there are already enough objects closer to the query point. Furthermore, expanding the radius may give users better results, especially when there are a lot of objects just outside the search boundary. Therefore, in this paper, we focus on approximate range search, where the query results are approximate, rather than exact. We propose approximate static range search (ARS) which combines two approaches, namely (i) lowerbound approximate range search, and (ii) upperbound approximate range search. Using ARS, we are able to deliver a better performance, together with low false hit and reasonable false miss. We also extend ARS in the context of a continuous query setting, in which the query moves. This is particularly important in spatial databases as a mobile user who invokes the query is moving. In terms of continuous range search, the intention is to find split points-the locations where the query results will be updated. Accordingly, we propose two methods for approximate continuous range search, namely (i) range search minimization, and (ii) split points minimization. Our performance evaluation which compares our methods with the traditional continuous range search shows that our methods considerably reduce the number of split points, thereby improving overall performance. For many years, spatial range search has been applied to computational geometry and multimedia problems to find interest objects within a given radius. Range search query has traditionally been used to return all objects within a given radius. However, having all objects is not necessary, especially when there are already enough objects closer to the query point. Furthermore, expanding the radius may give users better results, especially when there are a lot of objects just outside the search boundary. Therefore, in this paper, we focus on approximate range search, where the query results are approximate, rather than exact. We propose approximate static range search (ARS) which combines two approaches, namely (i) lowerbound approximate range search , and (ii) upperbound approximate range search . Using ARS , we are able to deliver a better performance, together with low false hit and reasonable false miss. We also extend ARS in the context of a continuous query setting, in which the query moves. This is particularly important in spatial databases as a mobile user who invokes the query is moving. In terms of continuous range search, the intention is to find split points—the locations where the query results will be updated. Accordingly, we propose two methods for approximate continuous range search , namely (i) range search minimization , and (ii) split points minimization . Our performance evaluation which compares our methods with the traditional continuous range search shows that our methods considerably reduce the number of split points, thereby improving overall performance. Issue Title: Special Issue on Cyber Physical Systems For many years, spatial range search has been applied to computational geometry and multimedia problems to find interest objects within a given radius. Range search query has traditionally been used to return all objects within a given radius. However, having all objects is not necessary, especially when there are already enough objects closer to the query point. Furthermore, expanding the radius may give users better results, especially when there are a lot of objects just outside the search boundary. Therefore, in this paper, we focus on approximate range search, where the query results are approximate, rather than exact. We propose approximate static range search (ARS) which combines two approaches, namely (i) lowerbound approximate range search, and (ii) upperbound approximate range search. Using ARS, we are able to deliver a better performance, together with low false hit and reasonable false miss. We also extend ARS in the context of a continuous query setting, in which the query moves. This is particularly important in spatial databases as a mobile user who invokes the query is moving. In terms of continuous range search, the intention is to find split points--the locations where the query results will be updated. Accordingly, we propose two methods for approximate continuous range search, namely (i) range search minimization, and (ii) split points minimization. Our performance evaluation which compares our methods with the traditional continuous range search shows that our methods considerably reduce the number of split points, thereby improving overall performance.[PUBLICATION ABSTRACT] |
| Author | Taniar, David AL-Khalidi, Haidar Safar, Maytham |
| Author_xml | – sequence: 1 givenname: Haidar surname: AL-Khalidi fullname: AL-Khalidi, Haidar email: haidar.al-khalidi@monash.edu organization: Clayton School of Information Technology, Monash University – sequence: 2 givenname: David surname: Taniar fullname: Taniar, David organization: Clayton School of Information Technology, Monash University – sequence: 3 givenname: Maytham surname: Safar fullname: Safar, Maytham organization: Computer Engineering, Kuwait University |
| BookMark | eNp9kDtLBDEURoMouK7-ALuAjc3ozWOSmVLEFwgWKtiFzOydNctssiZZ0X9vdC1E0CrNOcmXs0e2ffBIyCGDEwagTxOAAl0B4xVw1lZ6i0yYFKqqodbbZALAoJJN_bRL9lJaAAAXTTsh92erVQxvbmkzUjvOQ3T5eZnoECJN2WbXU-tntA8-O78O60Sj9XOkL2uMDhN1ni5D50ak3r66eRGC3yc7gx0THnyfU_J4efFwfl3d3l3dnJ_dVr2Qba5Eg23DlZXYiW6ATncN8kEzoSzWMEiYNbMalVYarGXNzAIfuNWoUQyCiUZMyfHm3vKDsidls3Spx3G0HstSw6SStZTqCz36hS7COvqyrlBCa64EawvFNlQfQ0oRB7OKpUx8NwzMZ2azyWxKZvOZ2eji6F9O7_JXhhytG_81-cZM5ZXSNP7Y9Kf0AVlVk6g |
| CitedBy_id | crossref_primary_10_1016_j_future_2016_03_005 crossref_primary_10_1155_2014_630396 crossref_primary_10_1007_s00607_012_0242_8 crossref_primary_10_1016_j_jcss_2014_12_025 crossref_primary_10_1002_cpe_3169 crossref_primary_10_1007_s11280_015_0332_6 crossref_primary_10_1109_ACCESS_2020_2979432 crossref_primary_10_1016_j_pmcj_2015_05_004 crossref_primary_10_1155_2015_273131 crossref_primary_10_1007_s00607_013_0318_0 crossref_primary_10_1007_s11280_021_00969_1 |
| Cites_doi | 10.1145/602259.602266 10.1007/s00454-009-9140-z 10.1007/3-540-45710-0_14 10.1007/978-3-540-77974-2 10.1016/0020-0190(93)90222-U 10.1145/223784.223794 10.1016/B978-012722442-8/50076-8 10.1007/3-540-47724-1_5 10.1016/j.jcss.2010.02.005 10.1145/293347.293348 10.1093/comjnl/bxh060 10.1007/s11042-008-0226-z 10.1007/978-3-642-02982-0_19 10.1109/ICDE.1997.581973 10.1016/j.comgeo.2008.09.009 10.1504/IJWGS.2011.038386 10.1002/9780470391365 10.1016/B978-155860869-6/50033-0 10.4018/jdwm.2011010103 |
| ContentType | Journal Article |
| Copyright | Springer-Verlag Wien 2012 Springer-Verlag Wien 2013 |
| Copyright_xml | – notice: Springer-Verlag Wien 2012 – notice: Springer-Verlag Wien 2013 |
| DBID | AAYXX CITATION 3V. 7SC 7WY 7WZ 7XB 87Z 8AL 8AO 8FD 8FE 8FG 8FK 8FL 8G5 ABUWG AFKRA ARAPS AZQEC BENPR BEZIV BGLVJ CCPQU DWQXO FRNLG F~G GNUQQ GUQSH HCIFZ JQ2 K60 K6~ K7- L.- L.0 L7M L~C L~D M0C M0N M2O MBDVC P5Z P62 PHGZM PHGZT PKEHL PQBIZ PQBZA PQEST PQGLB PQQKQ PQUKI Q9U |
| DOI | 10.1007/s00607-012-0219-7 |
| DatabaseName | CrossRef ProQuest Central (Corporate) Computer and Information Systems Abstracts ABI/INFORM Collection ABI/INFORM Global (PDF only) ProQuest Central (purchase pre-March 2016) ABI/INFORM Collection Computing Database (Alumni Edition) ProQuest Pharma Collection Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni) ProQuest Research Library ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central Database Suite (ProQuest) Business Premium Collection ProQuest Technology Collection ProQuest One Community College ProQuest Central Korea Business Premium Collection (Alumni) ABI/INFORM Global (Corporate) ProQuest Central Student ProQuest Research Library SciTech Collection (ProQuest) ProQuest Computer Science Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection Computer Science Database (ProQuest) ABI/INFORM Professional Advanced ABI/INFORM Professional Standard Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ABI/INFORM Collection (ProQuest) Computing Database Research Library Research Library (Corporate) Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Business ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central Basic |
| DatabaseTitle | CrossRef ABI/INFORM Global (Corporate) ProQuest Business Collection (Alumni Edition) ProQuest One Business Research Library Prep Computer Science Database ProQuest Central Student Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College Research Library (Alumni Edition) ProQuest Pharma Collection ABI/INFORM Complete ProQuest Central ABI/INFORM Professional Advanced ProQuest One Applied & Life Sciences ABI/INFORM Professional Standard ProQuest Central Korea ProQuest Research Library ProQuest Central (New) Advanced Technologies Database with Aerospace ABI/INFORM Complete (Alumni Edition) Advanced Technologies & Aerospace Collection Business Premium Collection ABI/INFORM Global ProQuest Computing ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest SciTech Collection ProQuest Business Collection Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition ProQuest One Business (Alumni) ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) Business Premium Collection (Alumni) |
| DatabaseTitleList | Computer and Information Systems Abstracts ABI/INFORM Global (Corporate) |
| Database_xml | – sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Mathematics Computer Science |
| EISSN | 1436-5057 |
| EndPage | 976 |
| ExternalDocumentID | 3085829571 10_1007_s00607_012_0219_7 |
| Genre | Feature |
| GroupedDBID | -4Z -59 -5G -BR -EM -Y2 -~C -~X .4S .86 .DC .VR 06D 0R~ 0VY 1N0 1SB 2.D 203 28- 29F 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 3V. 4.4 406 408 409 40D 40E 5GY 5QI 5VS 67Z 6NX 6TJ 78A 7WY 8AO 8FE 8FG 8FL 8G5 8TC 8UJ 8VB 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAOBN AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDBF ABDZT ABECU ABFTD ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACUHS ACZOJ ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMOZ AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFFNX AFGCZ AFKRA AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHQJS AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ AKVCP ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARAPS ARCSS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC B-. B0M BA0 BBWZM BDATZ BENPR BEZIV BGLVJ BGNMA BKOMP BPHCQ BSONS CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DWQXO EAD EAP EBA EBLON EBR EBS EBU ECS EDO EIOEI EJD EMK EPL ESBYG EST ESX FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRNLG FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GQ8 GROUPED_ABI_INFORM_COMPLETE GUQSH GXS H13 HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I09 IHE IJ- IKXTQ ITG ITH ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ K1G K60 K6V K6~ K7- KDC KOV KOW LAS LLZTM M0C M0N M2O M4Y MA- MK~ ML~ N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM P19 P2P P62 P9O PF0 PQBIZ PQBZA PQQKQ PROAC PT4 PT5 Q2X QOK QOS QWB R4E R89 R9I RHV RIG RNI RNS ROL RPX RSV RZK S16 S1Z S26 S27 S28 S3B SAP SCJ SCLPG SCO SDH SDM SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TH9 TN5 TSG TSK TSV TUC TUS U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 Z7R Z7X Z7Z Z81 Z83 Z88 Z8M Z8N Z8R Z8T Z8U Z8W Z92 ZL0 ZMTXR ~8M ~EX AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC ADHKG AEZWR AFDZB AFFHD AFHIU AFKWF AFOHR AGQPQ AHPBZ AHWEU AIXLP AMVHM ATHPR AYFIA CITATION PHGZM PHGZT PQGLB 7SC 7XB 8AL 8FD 8FK JQ2 L.- L.0 L7M L~C L~D MBDVC PKEHL PQEST PQUKI Q9U PUEGO |
| ID | FETCH-LOGICAL-c349t-38e9826a4eb3bf0b7b8e2f7136ae50f40d8d5e67670aa18da02f2a7e7e3f31383 |
| IEDL.DBID | RSV |
| ISICitedReferencesCount | 24 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000325127200003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0010-485X |
| IngestDate | Thu Sep 04 19:14:49 EDT 2025 Wed Nov 26 13:12:19 EST 2025 Sat Nov 29 03:51:35 EST 2025 Tue Nov 18 21:16:19 EST 2025 Fri Feb 21 02:26:12 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 10-11 |
| Keywords | Secondary 68U35 Spatial databases Primary 68P20 Approximate static range Approximate continuous range Query processing |
| Language | English |
| License | http://www.springer.com/tdm |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c349t-38e9826a4eb3bf0b7b8e2f7136ae50f40d8d5e67670aa18da02f2a7e7e3f31383 |
| Notes | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23 |
| PQID | 1437726319 |
| PQPubID | 48322 |
| PageCount | 28 |
| ParticipantIDs | proquest_miscellaneous_1464544638 proquest_journals_1437726319 crossref_primary_10_1007_s00607_012_0219_7 crossref_citationtrail_10_1007_s00607_012_0219_7 springer_journals_10_1007_s00607_012_0219_7 |
| PublicationCentury | 2000 |
| PublicationDate | 20131000 2013-10-00 20131001 |
| PublicationDateYYYYMMDD | 2013-10-01 |
| PublicationDate_xml | – month: 10 year: 2013 text: 20131000 |
| PublicationDecade | 2010 |
| PublicationPlace | Vienna |
| PublicationPlace_xml | – name: Vienna – name: Wien |
| PublicationSubtitle | Archives for Scientific Computing |
| PublicationTitle | Computing |
| PublicationTitleAbbrev | Computing |
| PublicationYear | 2013 |
| Publisher | Springer Vienna Springer Nature B.V |
| Publisher_xml | – name: Springer Vienna – name: Springer Nature B.V |
| References | BustosBNavarroGImproving the space cost of k-nn search in metric spaces by using distance estimatorsMultimed Tools Appl200941221523310.1007/s11042-008-0226-z Tao Y, Papadias D, Shen Q (2002) Continuous nearest neighbor search. In: Proceedings of the 28th international conference on Very Large Data Bases, VLDB ’02, pp 287–298. VLDB Endowment SafarMK nearest neighbor search in navigation systemsMob Inf Syst200513207224 CorralAVassilakopoulosMOn approximate algorithms for distance-based queries using r-treesComput J200548222023810.1093/comjnl/bxh060 SafarMEbrahimiDEdar algorithm for continuous knn queries based on pineIJITWE200614 121 da FonsecaGDMountDMApproximate range searching: The absolute modelComput Geom Theory Appl201043443444410.1016/j.comgeo.2008.09.0091208.65031 AryaSMountDMNetanyahuNSSilvermanRWuAYAn optimal algorithm for approximate nearest neighbor searching fixed dimensionsJ ACM1998456891923167884610.1145/293347.2933481065.68650 GhadiriNBaraani-DastjerdiAGhasem-AghaeeNNematbakhshMAOptimizing the performance and robustness of type-2 fuzzy group nearest-neighbor queriesMob Inf Syst201172123145 AryaSMalamatosTMountDThe effect of corners on the complexity of approximate range searchingDiscrete Comput Geom2009413398443248636910.1007/s00454-009-9140-z1165.68060 Chow C-Y, Mokbel MF, Naps J, Nath S (2009) Approximate evaluation of range nearest neighbor queries with quality guarantee. In: SSTD ’09: Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases, pp 283–301. Springer RodriguezJMZuninoACampoMIntroducing mobile devices into grid systems: a surveyInt J Web Grid Serv20117114010.1504/IJWGS.2011.038386 BernMApproximate closest-point queries in high dimensionsInf Process Lett19934529599120974410.1016/0020-0190(93)90222-U0795.68187 Arya S, Mount DM (1993) Approximate nearest neighbor queries in fixed dimensions. In: SODA ’93: Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms, pp 271–280. Society for Industrial and Applied Mathematics Guttman A (1984) R-trees: a dynamic index structure for spatial searching. In: SIGMOD ’84: Proceedings of the 1984 ACM SIGMOD international conference on Management of data pages, ACM. pp 47–57 Sedighian KS, Sharifi M (2012) Coverage rate calculation in wireless sensor networks. Computing : 1–24 Sistla AP, Wolfson O, Chamberlain S, Dao S (1997) Modeling and querying moving objects. In: Proceedings of the thirteenth international conference on data engineering ICDE ’97, pp 422–432. IEEE Computer Society Roussopoulos N, Kelley S, Vincent F (1995) Nearest neighbor queries. In: SIGMOD ’95: Proceedings of the 1995 ACM SIGMOD international conference on Management of data, ACM. pp 71–79 TaniarDLeungCHCRahayuWGoelSHigh performance parallel database processing and grid databases. Wiley Series on Parallel and Distributed Computing2008HobokenWiley10.1002/9780470391365 AL-Khalidi H, Abbas Z, Safar M (2012) Approximate range query processing in spatial network databases. Multimed Syst :1–11 YildizliCPedersen ThomasBSayginYSavasELeviADistributed privacy preserving clustering via homomorphic secret sharing and its application to (vertically) partitioned spatio-temporal dataInt J Data Warehouse Min201171466610.4018/jdwm.2011010103 XuanKZhaoGTaniarDRahayuWSafarMSrinivasanBVoronoi-based range and continuous range query processing in mobile databasesJ Comput Syst Sci2011774637651279926510.1016/j.jcss.2010.02.0051214.68147 de BergMCheongOvan KreveldMOvermarsMComputational geometry: algorithms and applications20083BerlinSpringer MorvanFHameurlainAA mobile relational algebraMob Inf Syst201171120 Papadias D, Zhang J, Mamoulis N, Tao Y (2003) Query processing in spatial network databases. In: VLDB ’2003: Proceedings of the 29th international conference on Very large data bases, VLDB Endowment. pp 802–813 Corral A, Ca nadas J, Vassilakopoulos M (2002) Approximate algorithms for distance-based queries in high-dimensional data spaces using r-trees. In: ADBIS ’02: Proceedings of the 6th East European Conference on Advances in Databases and Information Systems, pp 163–176. Springer Song Z, Roussopoulos N (2001) K-nearest neighbor search for moving query point. In: Proceedings of the 7th international symposium on advances in spatial and temporal databases SSTD ’01, pp 79–96. Springer Philippe RigauxAVSchollMOSpatial databases: with application to GIS2002BurlingtonMorgan Kaufmann B Bustos (219_CR6) 2009; 41 F Morvan (219_CR14) 2011; 7 219_CR1 219_CR21 219_CR3 219_CR25 M Safar (219_CR19) 2005; 1 219_CR22 219_CR23 219_CR8 S Arya (219_CR2) 2009; 41 A Corral (219_CR9) 2005; 48 N Ghadiri (219_CR12) 2011; 7 GD Fonseca da (219_CR10) 2010; 43 D Taniar (219_CR24) 2008 219_CR7 S Arya (219_CR4) 1998; 45 M Bern (219_CR5) 1993; 45 M Berg de (219_CR11) 2008 219_CR18 219_CR15 JM Rodriguez (219_CR17) 2011; 7 M Safar (219_CR20) 2006; 1 AV Philippe Rigaux (219_CR16) 2002 219_CR13 C Yildizli (219_CR27) 2011; 7 K Xuan (219_CR26) 2011; 77 |
| References_xml | – reference: Sedighian KS, Sharifi M (2012) Coverage rate calculation in wireless sensor networks. Computing : 1–24 – reference: GhadiriNBaraani-DastjerdiAGhasem-AghaeeNNematbakhshMAOptimizing the performance and robustness of type-2 fuzzy group nearest-neighbor queriesMob Inf Syst201172123145 – reference: Sistla AP, Wolfson O, Chamberlain S, Dao S (1997) Modeling and querying moving objects. In: Proceedings of the thirteenth international conference on data engineering ICDE ’97, pp 422–432. IEEE Computer Society – reference: XuanKZhaoGTaniarDRahayuWSafarMSrinivasanBVoronoi-based range and continuous range query processing in mobile databasesJ Comput Syst Sci2011774637651279926510.1016/j.jcss.2010.02.0051214.68147 – reference: MorvanFHameurlainAA mobile relational algebraMob Inf Syst201171120 – reference: AryaSMountDMNetanyahuNSSilvermanRWuAYAn optimal algorithm for approximate nearest neighbor searching fixed dimensionsJ ACM1998456891923167884610.1145/293347.2933481065.68650 – reference: TaniarDLeungCHCRahayuWGoelSHigh performance parallel database processing and grid databases. Wiley Series on Parallel and Distributed Computing2008HobokenWiley10.1002/9780470391365 – reference: de BergMCheongOvan KreveldMOvermarsMComputational geometry: algorithms and applications20083BerlinSpringer – reference: Arya S, Mount DM (1993) Approximate nearest neighbor queries in fixed dimensions. In: SODA ’93: Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms, pp 271–280. Society for Industrial and Applied Mathematics – reference: Guttman A (1984) R-trees: a dynamic index structure for spatial searching. In: SIGMOD ’84: Proceedings of the 1984 ACM SIGMOD international conference on Management of data pages, ACM. pp 47–57 – reference: Tao Y, Papadias D, Shen Q (2002) Continuous nearest neighbor search. In: Proceedings of the 28th international conference on Very Large Data Bases, VLDB ’02, pp 287–298. VLDB Endowment – reference: Song Z, Roussopoulos N (2001) K-nearest neighbor search for moving query point. In: Proceedings of the 7th international symposium on advances in spatial and temporal databases SSTD ’01, pp 79–96. Springer – reference: BustosBNavarroGImproving the space cost of k-nn search in metric spaces by using distance estimatorsMultimed Tools Appl200941221523310.1007/s11042-008-0226-z – reference: Corral A, Ca nadas J, Vassilakopoulos M (2002) Approximate algorithms for distance-based queries in high-dimensional data spaces using r-trees. In: ADBIS ’02: Proceedings of the 6th East European Conference on Advances in Databases and Information Systems, pp 163–176. Springer – reference: Roussopoulos N, Kelley S, Vincent F (1995) Nearest neighbor queries. In: SIGMOD ’95: Proceedings of the 1995 ACM SIGMOD international conference on Management of data, ACM. pp 71–79 – reference: SafarMEbrahimiDEdar algorithm for continuous knn queries based on pineIJITWE200614 121 – reference: AryaSMalamatosTMountDThe effect of corners on the complexity of approximate range searchingDiscrete Comput Geom2009413398443248636910.1007/s00454-009-9140-z1165.68060 – reference: CorralAVassilakopoulosMOn approximate algorithms for distance-based queries using r-treesComput J200548222023810.1093/comjnl/bxh060 – reference: AL-Khalidi H, Abbas Z, Safar M (2012) Approximate range query processing in spatial network databases. Multimed Syst :1–11 – reference: Chow C-Y, Mokbel MF, Naps J, Nath S (2009) Approximate evaluation of range nearest neighbor queries with quality guarantee. In: SSTD ’09: Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases, pp 283–301. Springer – reference: Philippe RigauxAVSchollMOSpatial databases: with application to GIS2002BurlingtonMorgan Kaufmann – reference: RodriguezJMZuninoACampoMIntroducing mobile devices into grid systems: a surveyInt J Web Grid Serv20117114010.1504/IJWGS.2011.038386 – reference: BernMApproximate closest-point queries in high dimensionsInf Process Lett19934529599120974410.1016/0020-0190(93)90222-U0795.68187 – reference: da FonsecaGDMountDMApproximate range searching: The absolute modelComput Geom Theory Appl201043443444410.1016/j.comgeo.2008.09.0091208.65031 – reference: YildizliCPedersen ThomasBSayginYSavasELeviADistributed privacy preserving clustering via homomorphic secret sharing and its application to (vertically) partitioned spatio-temporal dataInt J Data Warehouse Min201171466610.4018/jdwm.2011010103 – reference: Papadias D, Zhang J, Mamoulis N, Tao Y (2003) Query processing in spatial network databases. In: VLDB ’2003: Proceedings of the 29th international conference on Very large data bases, VLDB Endowment. pp 802–813 – reference: SafarMK nearest neighbor search in navigation systemsMob Inf Syst200513207224 – ident: 219_CR1 – ident: 219_CR13 doi: 10.1145/602259.602266 – volume: 41 start-page: 398 issue: 3 year: 2009 ident: 219_CR2 publication-title: Discrete Comput Geom doi: 10.1007/s00454-009-9140-z – ident: 219_CR8 doi: 10.1007/3-540-45710-0_14 – volume: 7 start-page: 1 issue: 1 year: 2011 ident: 219_CR14 publication-title: Mob Inf Syst – volume-title: Spatial databases: with application to GIS year: 2002 ident: 219_CR16 – volume-title: Computational geometry: algorithms and applications year: 2008 ident: 219_CR11 doi: 10.1007/978-3-540-77974-2 – ident: 219_CR21 – volume: 45 start-page: 95 issue: 2 year: 1993 ident: 219_CR5 publication-title: Inf Process Lett doi: 10.1016/0020-0190(93)90222-U – ident: 219_CR18 doi: 10.1145/223784.223794 – ident: 219_CR3 – ident: 219_CR15 doi: 10.1016/B978-012722442-8/50076-8 – ident: 219_CR23 doi: 10.1007/3-540-47724-1_5 – volume: 77 start-page: 637 issue: 4 year: 2011 ident: 219_CR26 publication-title: J Comput Syst Sci doi: 10.1016/j.jcss.2010.02.005 – volume: 7 start-page: 123 issue: 2 year: 2011 ident: 219_CR12 publication-title: Mob Inf Syst – volume: 45 start-page: 891 issue: 6 year: 1998 ident: 219_CR4 publication-title: J ACM doi: 10.1145/293347.293348 – volume: 48 start-page: 220 issue: 2 year: 2005 ident: 219_CR9 publication-title: Comput J doi: 10.1093/comjnl/bxh060 – volume: 41 start-page: 215 issue: 2 year: 2009 ident: 219_CR6 publication-title: Multimed Tools Appl doi: 10.1007/s11042-008-0226-z – volume: 1 start-page: 207 issue: 3 year: 2005 ident: 219_CR19 publication-title: Mob Inf Syst – ident: 219_CR7 doi: 10.1007/978-3-642-02982-0_19 – ident: 219_CR22 doi: 10.1109/ICDE.1997.581973 – volume: 43 start-page: 434 issue: 4 year: 2010 ident: 219_CR10 publication-title: Comput Geom Theory Appl doi: 10.1016/j.comgeo.2008.09.009 – volume: 7 start-page: 1 issue: 1 year: 2011 ident: 219_CR17 publication-title: Int J Web Grid Serv doi: 10.1504/IJWGS.2011.038386 – volume-title: High performance parallel database processing and grid databases. Wiley Series on Parallel and Distributed Computing year: 2008 ident: 219_CR24 doi: 10.1002/9780470391365 – volume: 1 start-page: 1 issue: 4 year: 2006 ident: 219_CR20 publication-title: IJITWE – ident: 219_CR25 doi: 10.1016/B978-155860869-6/50033-0 – volume: 7 start-page: 46 issue: 1 year: 2011 ident: 219_CR27 publication-title: Int J Data Warehouse Min doi: 10.4018/jdwm.2011010103 |
| SSID | ssj0002389 |
| Score | 2.1024241 |
| Snippet | For many years, spatial range search has been applied to computational geometry and multimedia problems to find interest objects within a given radius. Range... Issue Title: Special Issue on Cyber Physical Systems For many years, spatial range search has been applied to computational geometry and multimedia problems to... |
| SourceID | proquest crossref springer |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 949 |
| SubjectTerms | Algorithms Approximation Artificial Intelligence Boundaries Computer Appl. in Administrative Data Processing Computer Communication Networks Computer Science Digital maps Information Systems Applications (incl.Internet) Minimization Mobile communications networks Multimedia Navigation Optimization Queries Restaurants Searching Software Engineering Studies Wireless networks |
| SummonAdditionalLinks | – databaseName: ABI/INFORM Collection dbid: 7WY link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LT9wwEB6VbQ_toRRo1S20MhKnIovESdbOCa0qUC9Fldqqyyly_IBI4NDNLuLnM5NNQkGCC8coiW157Hl4xt8HsGdinwrvYm6kSjh64JKXE5tw41VM-G_CixXZhDw5UbNZ_rM7cGu6sspeJ7aK2taGzsgP0K6jIzjBFXN49Y8TaxRlVzsKjTV4iYY6IwYD-fd00MRojlbuL-qaVGWzPqsZtSCik7boUnC0cjmX9-3SnbP5ID_amp3j9ecO-B287RxONl2tkA144cImrPdkDqzb25vw5scA4Npswa8pYY3fVPjsmL44w4YX55cNQxeX0R2kyjAdLKNC9yos62XD5nRLgeEAKfZmVWCXdYkahwV93aJ41OE9_Dk--v3tO-_4F7hJ0nzBE-VyjD50igF36aNSlsoJj1HtRLss8mlklc0cIb5FWsfKapKslk66xCcxhr4fYBTq4D4CK7XQ5BlKY6PUWZELq1AOXqvYaZ3aMUT97BemAycnjoyLYoBVbgVWoMAKElghx_B1-OVqhczx1Mc7vZCKbpM2xZ2ExrA7vMbtRTkTHRxOHkVGaYYhc6LGsN8vhf-aeKzDT093uA2vBfFqtFWBOzBazJfuM7wy14uqmX9pV_EtIrP36g priority: 102 providerName: ProQuest |
| Title | Approximate algorithms for static and continuous range queries in mobile navigation |
| URI | https://link.springer.com/article/10.1007/s00607-012-0219-7 https://www.proquest.com/docview/1437726319 https://www.proquest.com/docview/1464544638 |
| Volume | 95 |
| WOSCitedRecordID | wos000325127200003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVPQU databaseName: ABI/INFORM Collection customDbUrl: eissn: 1436-5057 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002389 issn: 0010-485X databaseCode: 7WY dateStart: 20020201 isFulltext: true titleUrlDefault: https://www.proquest.com/abicomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ABI/INFORM Collection (ProQuest) customDbUrl: eissn: 1436-5057 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002389 issn: 0010-485X databaseCode: M0C dateStart: 20020201 isFulltext: true titleUrlDefault: https://search.proquest.com/abiglobal providerName: ProQuest – providerCode: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 1436-5057 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002389 issn: 0010-485X databaseCode: P5Z dateStart: 20020201 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: Computer Science Database (ProQuest) customDbUrl: eissn: 1436-5057 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002389 issn: 0010-485X databaseCode: K7- dateStart: 20020201 isFulltext: true titleUrlDefault: http://search.proquest.com/compscijour providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1436-5057 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002389 issn: 0010-485X databaseCode: BENPR dateStart: 20020201 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Research Library customDbUrl: eissn: 1436-5057 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0002389 issn: 0010-485X databaseCode: M2O dateStart: 20020201 isFulltext: true titleUrlDefault: https://search.proquest.com/pqrl providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1436-5057 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002389 issn: 0010-485X databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwEB71wQEOtBQQ28fKSD2BLCVOsnaOpWpVqeqyogUWLpET2yVS61Sb3Yqfz0w2SQHRSvRiyYrzGtvj-TQz3wDsF6GLhbMhL6SKOFrgkucjE_HCqZD434QTy2ITcjxW02k6afO46y7avXNJNpq6T3Yj6hAKkxQcz6WUy1VYT4hshiD6-Zde_eIZtLR5UcHEKpl2rsx_PeLPw-jOwvzLKdqcNccbj_rKTXjempbsYLkWXsCK9Vuw0ZVtYO0u3oJnZz1Va_0Szg-IVfxniX3L9NVlNSvnP65rhsYso2yjsmDaG0Yh7aVfVIuazSgfgeE_EMpmpWfXVY66hXl92_B1VP4VfD4-ujg84W2lBV5EcTrnkbIp4gwdI7TOXZDLXFnhEL-OtE0CFwdGmcQSt1ugdaiMpjnU0kobuShEkPsa1nzl7RtguRaabEBZmCC2RqTCKJSM0yq0WsdmAEEn8qxoacipGsZV1hMoNyLMUIQZiTCTA3jX33Kz5OB4aPBuN49Zux1rxDcRoogRqpsBvO0v40Yi74j2FoVHGChOEBxHagDvu7n97RH3vXD7v0bvwFNBBTWacMBdWJvPFnYPnhS387KeDWFVfv02hPUPR-PJJ-ydSo7tWXBIrfiI7ST5PmzW-y_nkvNO |
| linkProvider | Springer Nature |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Nb9QwEB2VggQcKBQQCwWMBBeQReJ4Y-eAUAVUrbZdIVGkvQUntttIbVI2u4X-qf5GZvJVQKK3HjhGSZzYfn4z4483AC_z0EvhXchzpSOOHrjiWWwjnnsdkv6b8KJNNqGmUz2bJZ9X4Lw_C0PbKntObIjaVjnNkb9Fu46OYIyIeX_ynVPWKFpd7VNotLCYuLMfGLLV73Y-Yv--EmLr0_6Hbd5lFeB5JJMFj7RL0Kc2EsPIzAeZyrQTHmO12Lhx4GVgtR070jELjAm1NfS_RjnlIh-FGNBhudfguox0TCNqovjA_Gj-WncbuU3q8axfRQ0a0dK42eQpOFrVhKs_7eCFc_vXemxj5rbW_rcGugt3OoeabbYj4B6suHId1vpkFazjrnW4vTcI1Nb34csmaan_LPDaMXN0gBVZHB7XDF14RmesipyZ0jLayF-Uy2pZszmdwmDYIDS3wIqSHVcZMiorzWmjUlKVD-DrlVT0IayWVekeAcuMMOT5qtwG0lmRCKux373RoTNG2hEEfW-neSe-TjlAjtJBNroBSIoASQkgqRrB6-GVk1Z55LKHN3pQpB0J1ekFIkbwYriN9EFrQqZ02HgU-cmxlMjCI3jTQ--3Iv71wceXf_A53Nze39tNd3emkydwS1AOkWYH5AasLuZL9xRu5KeLop4_a0YQg29XjchfVmZUyg |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6VLUJwoFBALBQwElxAVhPHu3YOCBXaFVVhteIh7S11_IBIrVM2uwX-Gr-OcV4FJHrrgWOUxIntz_PwjL8BeKJjx5mzMdVCJhQtcEHzsUmodjIO_G_MsabYhJhO5XyeztbgZ3cWJqRVdjKxFtSm1GGPfBv1OhqCY0TMtmvTIma7k5cnX2moIBUirV05jQYiB_bHN3Tfqhf7uzjXTxmb7H18_Ya2FQaoTni6pIm0KdrXiqNLmbsoF7m0zKHfNlZ2FDkeGWlGNnCaRUrF0qjw70pYYROXxOjcYbuXYF0k6PQMYP3V3nT2vtcDqAwb4xslHZejeRdTjWoK03Gd8sko6tiUij-14pmp-1d0tlZ6k43_ebhuwPXW1CY7zdq4CWvWb8JGV8aCtFJtE66966lrq1vwYSewrH8v8NoSdfQZO7L8clwRNO5JOH1VaKK8ISHFv_CrclWRRTifQXBwwq4DKTw5LnOUtcSr05q_pPS34dOFdPQODHzp7V0guWIq2MRCm4hbw1JmJGLAKRlbpbgZQtTNfKZbWvZQHeQo6wmla7BkCJYsgCUTQ3jWv3LScJKc9_BWB5CsFU9VdoaOITzub6NgCdEi5S0OXvAJ-YhzlM9DeN7B8Lcm_vXBe-d_8BFcQSBmb_enB_fhKgvFRerUyC0YLBcr-wAu69NlUS0etsuJwOFFQ_IXIZxfHA |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Approximate+algorithms+for+static+and+continuous+range+queries+in+mobile+navigation&rft.jtitle=Computing&rft.au=AL-Khalidi%2C+Haidar&rft.au=Taniar%2C+David&rft.au=Safar%2C+Maytham&rft.date=2013-10-01&rft.issn=0010-485X&rft.eissn=1436-5057&rft.volume=95&rft.issue=10-11&rft.spage=949&rft.epage=976&rft_id=info:doi/10.1007%2Fs00607-012-0219-7&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0010-485X&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0010-485X&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0010-485X&client=summon |