This article is protected by German copyright law. You may copy and distribute this article for your personal use only. Other use is only allowed with written permission by the copyright holder. 79  Oldenbourg Wissenschaftsverlag Der Entwurf des Datenmana- © ät mobiler Anwendungen durch The remainder of the paper ing data on the mobileout device with- anya communication deeper requires In look many intodata cases the managing only systems. methodsvided rudimentary to are the pro- applicationTherefore, developer. we givetroduction also in a how brief todata in- store/manage on mobile devices. is structured asdescribes the storage follows: of data Section onbile 2 mo- devices. Sectionapproaches 3 for focuses managingclient/server on data systems in clients. with Section mobile 4paper. summarizes the Zusammenfassung 10.1524/itit.2009.0526 DOI ng, Horten, Replikation, mobile Informationssysteme gements mobiler Anwendungen istSelbst eine mit nichttriviale den Aufgabe. heutemüssen gängigen Ressourcenbeschränkungen leistungsstärkeren wie die Endgeräten tenz Größe lokaler und Daten, Persis- limitierte Bandbreitebei und der Netzverfügbarkeit Kommunikationder mit Datenspeicherung berücksichtigt Servern werden. oderfokussieren In diesem wir der Artikel auf Energiebedarf existierende Client/Server-Verfahren. Wir Techniken klassifizieren undDatenmanagementfunktionalit unterstützen deneine Designer Zusammenstellung der replizierenden, fundamentaler hortenden und Charakteristika cachenden Lösungen. von  servers aretem, involved like in in(P2P) so approaches, the network called stability peer-to-peer is sys- even worse andbecomes data essential. redundancy However, inarticle this we focus on client/serverproaches. ap- We classify existingniques tech- andof support data management the functionalities for designer mobile applicationsof with a fundamental set replication, characteristics hoarding of andsolutions. Hence, caching we guideveloper the to de- specifics decide, of based theto on target use the application, astrategy. proper Furthermore, even data manag- management – Information Technology 51 (2009) 2 / y consumption of the used al- it it 2/2009 support redundant H.2.4 [Information Systems: Database Management: Systems]; H.2.8 [Information Systems: Database Man- agement: Database Applications]; H.3.2storage]; [Information H.3.4 [Information Systems: Systems: Information Information Storageing, Storage and replication, and Retrieval: mobile Systems Retrieval: information and systems Information Software]; / caching, Cachi hoard- Schwerpunktthema The design of data management for mobile ap- must and Motivation

Data management inronments mobile envi- is affectedacteristics by of thedevices. char- used Mobile devices networkspowered are and battery and wireless networkscompared are, to wiredreliable. networks, Furthermore, wireless un- data transmission isExtensive energy communication intensive. the reduces operation timevices of [12]. mobile Eventems de- client/server with sys- mobilefixed clients that networkedbackbone use components as 1 Introduction data storage and handling. If no KEYWORDS Summary plications is a non-trivialpowerful task. devices, Even we withand today’s must persistence much consider of more theand limited local reliability resources: of data connection size storage,servers, for limited and data bandwidth transmissions constraint to energ remote Hagen Höpfner, Essam Mansour, InternationalDaniela University Nicklas, in University Germany, of Bruchsal, Oldenburg gorithms. In this articleWe we classify focus on existingdata client/server techniques management approaches. and functionalities for supporta mobile set the of applications fundamental designer with characteristics of of caching replication, solutions. hoarding and Überblick über Datenmanagementmechanismen auf mobilen Endgeräten

Mechanisms on Mobile Devices Review of Data Management This article is protected by German copyright law. You may copy and distribute this article for your personal use only. Other use is only allowed with written permission by the copyright holder. How Is all Is the Which kind Are updates allowed on Is the data on theread mobile only device or mutable? Who decides what data ison stored the mobile device, the userthe or system? Is the decision foron storing the data a device static decision? a dynamic or lations: the mobile device? required data guaranteed toon the be mobile device? often does the data that ismobile on device the change? of software is required fortain a technique? cer- user ableneeded to on the specify mobile device? the data We discuss these aspects based 3.1 Caching The easiest waybile to user provide acache with mo- data data onceceived. locally So, it data is iscitly. has to requested Web impli- been andexample, re- WAP automatically browsers, cache WML for or HTML pagesknow and caching approaches pictures. from net- We work based desktop applicationswell as as frommation database based systems. infor- The research on tween server and clients.datahastobecopiedtothemo- Therefore, bile devices whereused offline, it too. One then can findmajor can three be classesmanaging of such redundant approachesa data client for server in mannerture: in caching, the hoarding, litera- and replica- tion. The following questionsto need be answeredmine in the order appropriate to approacha given for deter- application scenario [19]. • • • Figure 2 illustrates, basedvarious important on aspects [10], inthe which three classesother: differ fromThe each grade of possible data manipu- The possibility to work offline: The potential dynamic of data: The required resources: The influence on local data: on [11] per techniquetails in in the more following de- sub-sections. RMS structure. Some newer mobile devices also 3 Client/ServerRecent Approaches mobile information systems work mostlymanner in whereand a clients servers are are client/server- static,vices. mobile powerful Due de- toenergy intensive the wireless data trans- unreliabilitymission of it isantee not a possible permanent to connection guar- be- Figure 1 sides storing data withrectly, the one RMS can di- also usePointbase systems Micro like orthat NanoBase are built [5] onStore top Manager of but support the alevel Record higher of abstraction.in Unfortunately, September 2007DataMirror, the IBM company acquired veloped that Pointbase de- Micro. Therent cur- status is that IBMsupport for will the stop product at any theSeptember end of 2009 [15]. Asis NanoBase new to the community,is no release available atever, the the authors moment. ofpromised How- the on cited paper requeststill that finishing they the website are tem. of the sys- support accessinghandling PIM filesVirtual data through Machine. their However, or manufacturers not Java all implementspective the optional re- Java Specification Requests (JSR 75)nately, [31]. there Unfortu- independent is list nowhich that mobile manufacturer devices support summarizes which JSR, and to focus on a certainfacturer manu- would bethis out article. of Hence, scope ato for developer carefully has check systemtions specifica- before implementingfunctions. certain Schwerpunktthema Devices A good starting point for work- ing with RMSonline in article MIDP [24]. 1.0and The is MIDP the MIDP 1.0 also 2.0 available specifications online are [29; 30]. Be- Mobile devicesbile phones like or other PDAs, programmable lightweight devices are mo- able todata store inling various data storage ways, very oftendepends but strongly on hand- theand operating the system languages. supported Furthermore, mobile de- programming vices differdia. in Some used(like older storage use Palm devices), me- volatilenon-volatile some use flash memory useharddisks,andsomecombine memory, some these media. Currentthe trends go direction in filesystem of for a mobilemany mobile devices, devices desktop e. g., and suchuse that like Windows Mobile,such do a storage provide mechanismNevertheless, there are already. many devices onthemarketthatarenotableto store data inetary formats. files Most current butphones mobile support in Java’s Mobile propri- Infor- mation Device Profile (MIDP)and [26] are equipped withflash non-volatile memory.poses For J2ME-applications security (soMIDlets) called pur- mustthe not file save systemone files can directly. use to However, agement MIDP’s Record Systems Man- (RMS)to in store data order permanentlya on device. such Theform data is of stored devicerecord in the dependent stores binary vides but functions for the accessingvice it independently. API de- Ancan application pro- manage variousEach record of stores. uniquely them identified byte is arrays.ID The a is collection assigneding incrementally of with start- 1.are IDs not reused. of The RMS deleted APIMIDlets records to allows add and remove records. Furthermore, it is possiblerecords to within share thetion (see same Fig. 1). applica- tween applications Sharing is dataMIDP possible be- 2.0. with 2 Storing Data on Mobile 80 This article is protected by German copyright law. You may copy and distribute this article for your personal use only. Other use is only allowed with written permission by the copyright holder. 81 Fur- (PA) (FAR) strat- ches enable the tances using es-  Probability Area Probability Area Inverse Distance and (PAID). Both policies usecept the of con- thevalue, which valid is a scope geometric areareflects of that the access probability a to that data data value from usersWhile PA in mainly that relies on area. cept, that PAID con- further combines itthe with data distance which isthe similar FAR to strategy. 3.2 Replication Replication approa possibility to workdata offline with stored the vice. on The user explicitly thereplicas defines the mobile anddata copies de- on the thefact, mobile required nearly device each [7].ment database In manage- system vendorDBMS offers that mobile can benation used with in a combi- replication backend purposes DBMS (e.Lite for g., [27], IBM DB2 Oracle Everyplace [16], Microsoft SQL Server CE [25], mantic caching,of the location-dependent performance mobile queries users of canexploiting be the improved movementof by patterns the user.the For cache example, is insegments organized [33], in that semantic representlocation-dependent results queries. If of data has tobecause be of deleted storagethest space, Away on Replacement the theegy is cache used. Thisthe approach directional extends Manhattan distance function from [4]firstly, in it threecenter does ways: of notthe the attached calculate segment, locationsecondly, the information; but FAR derives uses relationships between cached segmentscurrent and query the insteading of Manhattan calculat- dis timated weights; anduses finally, knowledge FAR aboutment direction the of move- theHowever, mobile these user. approachessume do that as- location-dependent data is queried only ifregion the – user queries is to that inother region that from locations arewell. Thus, not Zheng et supported al.pose in [37] two pro- otherpolicies cache called replacement chanisms on Mobile Devices Caches are primarily used for For mobile data caching of Semantic caches tend to usetic seman- correlationscached between items as a different replacementria crite- [4]. Furthermore, it isanalyze possible contextual to information such as location and tocause replace it data does be- the not current longer context. belong to reducing costs andtransmissions. delays However, ofnot data provide they a full do the offline work information with other system. hand caches are easy On realizable anddonotrequireadditionalfunc- the tionalities such asor synchronization data mining that arereplication required for or hoarding.less, Neverthe- semantic caches needstructure an and index algorithms for retriev- ing and recombiningAnother cached aspect data. oflocal caching data is modificationsmally that not are supported. So, nor- in read it only is scenarios. used location-based services,dependent location- cachingbe strategies applied. can On the basis of se- Classification of caching, hoarding, and replication. Review of Data Management Me The availability of data in the caching in contextformation of system mobilemantic focuses in- caching on insteadpages/blocks of se- or caching objects.query Therefore, results are storedbut as indexed they using are ing the correspond- query [17; 22;possible 32]. Hence, to itqueries analyze is can whether becommunication new with answered the server. without a To certain degreeto it recombine is cached data alsoditional with data possible to ad- answer a query34]. [6; 9; Unfortunately, theare algorithms complex andlimitations suffer of from the strict underlyingcontainment query problem (see18; 36]). [2; 3; 8; cache canit not depends bement on guaranteed strategy. the If as these the used algorithms cache replace- decide ismoving full, about (hopefully) re- notquired longer data. re- However, themight decision be wrongicallybasedonthetime,onwhich because it isa typ- data item isand/or on already accesses in on this the data cache, item. Figure 2 This article is protected by German copyright law. You may copy and distribute this article for your personal use only. Other use is only allowed with written permission by the copyright holder. , , Proc. , pages 56–70, Proc. of the 6th on,´ K. Rothermel, LNCS Proc. of the 4th Annual and T. Pfahl. Hoarding location- based data using clustering. In: of the Int’l Workshop on Mobility Management and Wireless Access pages 164–171, 2006. Optimal implementation of conjunctive queries in relational data bases. In: ACM Symp. on Theory of Computing pages 77–90, 1977. Conjunctive Query Containment Revisited. In: F. N. Afrati and P. G. Kolaitis, editors, Int’l Conf. on Database Theory –’97, ICDT vol. 1186 of 1997. The conclusion is: caching is We explicitly left out peer-to- [1] S. Bürklen, P. J. Marr [2]A.K.ChandraandP.M.Merlin. [3] C. Chekuri and A. Rajaraman. References cation and, therefore, gaveline a guide- for developerscharacteristics of the based targeted appli- oncation. the easy to implement as it simplydata stores implicitly. However, caches are not suitable if data availability needs to be guaranteed evenis if not the connected device toprovider. an information Inis this a case must. Hoardingof replication covers both, aspects and caching works perfectly and inCODA-file system replication form with of laptops. For the more lightweight devicesoption but it not worthwhile. is Theditional ad- an effort thatanalyzing data accessed is is much needed big- ger then for theagement effort and for the cache useravailability man- guarantees. gets To no conclude data this one can say:has If to the guarantee application the developer data must availability, techniques. use replication If thewants to developer reduce only tions, data caching is communica- sufficient. peer approaches and did notcontext discuss awarein data detail. management Bothsearch topics. are However, they are interesting not common re- in today’s applicationsfollow or simple straight forwardcepts. con- Using this infor- . Newer approaches % For example, [23] uses a pre- 4 SummaryThis and Conclusions papertask was of dedicated designing thement to data of manage- the mobileclient/server application paradigm. in We have the in- troduced approaches for storing and managing data on the mobile clients and presented a classificationproaches of ap- for managingdata redundant that arecharacteristics necessary of mobile to devices and facewireless the networks. Furthermore, we discussed the specificsclasses of caching, the hoarding three and repli- diction function basedChain on Models Markov to predictment the move- of ais mobile user. likelyby Data that needed thethe in user cache. is thedeploys The pre-fetched prediction future ation into model regular-pattern algorithms toregular detec- deal movement withdaily both patterns routine) (e. g., andEven though random the parts. rithm prediction is algo- quitehave simple, shown simulations aof prediction efficiency about 95 lyzes data accesses. If,compiles e. a g., C-programm, the the user source code as well asfiles the involved are header cached.tion systems For point of an viewcan hoarding informa- be realized viasuch query as rewriting harmingor select extending conditions thedatabase projection queries. Furthermore, list con- of textual information mightas be hoarding used criteria,For e. g., example, location. [28] orsystems that [20] cache propose datato with the regard current orlocation. a predicted future like [20] use location-dependent log data about frequent queriesbile of mo- usersprobability to maps. buildmation, up the so hoardingadaptive called is to not theusers movement but only also of tocess the changing patterns. data ac- Later,been this extended workpages has for on hoarding mobilesemantic web devices clustering [1] of using items. related data Schwerpunktthema The data replication strategies 3.3 Hoarding The class ofcovers hoarding aspects approaches ofreplication. Similar caching to caches it anda uses replacement of strategy anditly implic- stores datavice. on In addition the algorithms mobile analyze the de- usagedata of that data.fined was So, but not necessary offline is explicitly can needed de- beFurthermore, for found some working andtems hoarding cached. do sys- alsocification support manual of spe- be data cached. Such techniques thatwith overlap the needs replica specification. How- to ever, hoarding can be foundin mainly form ofsuch as hoarding CODAextension file [21]. [35] This systems file and system ana- its Seer can also bebile device adapted. is Ifa always costly the network, connected it to mo- ratio depends between on mobile access the and up- date rate of ashould data be item, replicated whether on it device the or mobile fetchedthe on demand network. over Huangpresent et and al. analysis various ingies strate- based [13] on these metrics. or Sybasewhere Adaptive [14]). The replication process Serverdepends Any- on thearchitecture underlying which could system be a simple client/server approach or aware middle- solution. A client/server archi- tecture offers athe direct client access toMiddle-ware from the approaches serverditional use database. components ad- (theware) that middle- manage the communica- tion between the serverand database(s) mobiledefined clients. similar Replicasdatabase to views. are Therefore, selection (materialized) and projection operationslowed. In are order to al- the allow updates replicated to data, joinare operations mostly not allowed.content Besides definition, the the user canspecify also how andshall when synchronize themobile system updates. device runs If outthe of the memory, user has todeleting replicated free data. it manually by 82 This article is protected by German copyright law. You may copy and distribute this article for your personal use only. 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Weiss. [9] H. Höpfner and K.-U. Sattler. Towards [12] H. Höpfner and C. Bunse. Ressource [11] H. Höpfner. [10] H. Höpfner, C. Türker, and B. König- This article is protected by German copyright law. You may copy and distribute this article for your personal use only. Other use is only allowed with written permission by the copyright holder. is Junior Pro- and active database 2008 from the Dublin Institute ofogy Technol- (DIT), Ireland. His researchinclude interests mobile databases and information systems, context aware systems, temporal XML data management, systems. Address: International University in Ger- many, School of Information Technology, Campus 2, 76646 Bruchsal, Germany, Tel.: +49-7251-700240, Fax: +49-7251-700250, E-Mail: [email protected] 3 Prof. Dr. Daniela Nicklas fessor for database- and internet technology at the Department for Computer Science, University of Oldenburg. She received her Dr. rer. nat. (Ph. D.) 2005Science in from Computer the University of Stuttgart, working on spatial context models andchitectures for ar- location-based applications, and her Diplom (MSc) 2000, alsoputer in Science, Com- with an emphasis on Software Engineering. Her current research interests are mobile applications, context-aware com- puting and data stream technologies. Address: University of Oldenburg, Depart- ment for Computer Science, Escherweg 2, 26121 Oldenburg, Germany, Tel.: +49-441- 9722211, Fax: +49-441-9722202, E-Mail: [email protected] is Assistant is Research Asso- 1 Dr.-Ing. Hagen Höpfner Professor for Databases and Information Systems at the International University in Germany (Bruchsal, Germany). He received his Diplom in Computer Science andPh. his D. in Computer Science inthe 2005 University from of Magdeburg, Germany. His research interests include database theory, transaction processing as well as mobility as- pects of databases and information systems in general. He is co-author oftextbook the on German “Mobile Databases and Infor-mation Systems” and works as aauthor freelance for various German and international magazines. Address: International University in Ger- many, School of Information Technology, Campus 2, 76646 Bruchsal, Germany, Tel.: +49-7251-700239, Fax: +49-7251-700250, E-Mail: [email protected] 2 Dr. Essam Mansour ciate for Databases and Information Systems at the International University in Germany (Bruchsal, Germany). He graduated from Cairo University, Egypt in 2000 with aClass First Honours in Information Systems.then completed He a M. Sc. in Informationtems Sys- in 2003 at the samereceived university. his He Ph. has D. in Computer Science in 2 IEEE IEEE Trans. on , 39(4):447–459, , 54:113–135, Feb Journal of Computer 1 3 , pages 1141–1153, 2002. and D. C. Steere. Coda: AAvailable Highly File System for a Distributed Workstation Environment. Computers Trans. on Computers Apr 1990. querying indefinite data about linearly ordered domains. Invalidation and Replacement Strate- gies for Location-Dependent Data in Mobile Environments. and System Sciences 1997. Schwerpunktthema [36] R. v. d. Meyden. The complexity of [37] B. Zheng, J. Xu, and D. L. Lee. Cache 84