THE DISTRIBUTED LOCATION RESOLUTION PROBLEM AND ITS EFFICIENT SOLUTION

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1 IADIS Intenational Confeence Applied Computing 2006 THE DISTRIBUTED LOCATION RESOLUTION PROBLEM AND ITS EFFICIENT SOLUTION Jög Roth Univesity of Hagen Hagen, Gemany ABSTRACT Location-based applications and sevices become inceasingly impotant fo mobile uses. They take into account a mobile use's cuent location and povide a location-dependent output. To suppot developes of location-based sevices, the Nimbus famewok hides specific details of positioning systems and povides unifom output containing physical as well as symbolic location infomation, which often ae moe suitable fo applications and uses. One basic poblem is the Distibuted Location Resolution Poblem: given a location; which identifiable aeas cove this location, if aea infomation is distibuted among diffeent seves? This pape pesents an algoithm that solves this poblem and uns in the distibuted, self-oganizing Nimbus infastuctue. KEYWORDS Location-based sevice, symbolic location, self-oganizing infastuctue 1. INTRODUCTION The answe to the question "Whee am I?" becomes inceasingly impotant fo mobile uses. In the futue, it will not only be sufficient to know the coodinates of the cuent location, but also to know infomation about the cuent location. Typical questions will be: "Which bus takes me fom hee to the ailway station?" o "Who of my fiends ae cuently in this estauant?". Ove the last yeas, many eseaches developed socalled location-awae applications that espond to such questions. Fo such sevices, expets expect a huge maket potential of seveal billion dollas in evenue woldwide in the next yeas [6, 15]. Location-based sevices often need symbolic location infomation, but most positioning systems only povide physical locations. In this pape we pesent the Nimbus platfom, which povides a solution fo the distibuted location esolution poblem (DLRP): given a location and a set of distibuted computes, each stoing a cetain set of identifiable aeas; which aeas contain this location? Nimbus intoduces a naming scheme and classifies these aeas accoding to hieachies. If an application gets well-defined aea names fo a cetain location, it can easily lookup location-based infomation in e.g. databases o file systems. Poviding these location infomation, the famewok enables applications in the aea of mobile and pevasive computing which othewise wee not conceivable o at least vey cost-intensive. The following examples motivate the benefits of this appoach. Fig. 1. Location-based applications: the univesal emote contol (left), the Nimbus bus planne (ight) 3

2 ISBN: IADIS A univesal location-based emote contol is illustated in fig. 1 (left). It offes diffeent sevices depending on the use's cuent location: at home, it is a taditional emote contol fo home-entetainment equipment. At wok, it is used as an electonic key to open office doos and on tavel, it can be used to pay tickets fo public tanspotation. Such a device is not pimaily inteested in the physical location but, in the type of the cuent position (e.g. home o office). Fig. 1 (ight) pesents a location-based bus planne, developed with the Nimbus famewok. The use simply selects the destination and the application computes the appopiate timetable fo the selected destination, while taking into account the cuent time and location. Afte boading the bus, the planne supevises the cuent location and infoms the use when to exit. Again, this application is not pimaily inteested in the physical coodinates of the use s cuent location, but wants to know at which bus station the use is waiting. As the bus station locations ae stoed decentally (e.g. inside diffeent bus station egistes fo the espective city), we have to look up these data in a distibuted manne. Aeas such as bus stations and offices, but also steets, foests, city centes etc. ae often called symbolic o semantic locations [8, 10, 13]. People expect a lot of semantics and intelligence behind these wods, even though the tem semantic location in its oiginal meaning only descibes an aea that has a cetain identity fo a use o application. Thus, in Nimbus we use the tem identifiable aea instead. Such an aea can uniquely be identified by a name. The naming scheme povides a ough classification of the aea, but the actual semantics behind it is only peceptible inside the espective application. In pinciple, one huge database on a single seve could stoe all identifiable aeas, but a single database would be a bottleneck. Moe easonably, a mobile client has local access to the sevice. Moeove, infomation about local aeas is usually available locally and is difficult to administate in a cental database. As a solution, Nimbus povides a distibuted system of Location Seves that stoe the infomation about identifiable aeas in a decentalized manne. Location seves ae connected to each othe in a pee-to-pee style and povide a solution of the DLRP. 2. RELATED WORK Seveal famewoks deal with location data and povide a platfom fo location-based application. E.g., the Open Geospatial Consotium [9] povides a high-level famewok to build location-based sevices. The LORE platfom [2] contains thee key components: a location seve poviding a location sensing API, a moving object database and a spatial publish/subsciption engine. All components ae built accoding to a taditional client/seve achitectue. Nexus [5] intoduces so-called augmented aeas to fomalize location infomation. Augmented aeas epesent spatially limited aeas, which may contain eal as well as vitual objects, whee the latte can only be modified though the Nexus system. Inside the Nexus famewok, diffeent locations can be modeled in the so-called augmented wold model: static objects like houses o steets, mobile objects such as uses o cas and vitual objects such as vitual post-its o vitual kiosks. Between these locations, elations can be defined which expess, e.g., inclusion of aeas. The RAUM location model [1] was designed to addess the needs of netwoked ubiquitous devices such as intelligent cups and memo clips. In its fist vesion it could only stoe locations without any geogaphic infomation. In a second vesion, geometic infomation was added in ode to expess positions of objects. A numbe of platfoms focus on location sensing. The Location Stack [4] povides a layeed appoach to access multiple positioning systems. A simila appoach follows the POS component inside the PoLoS poject [11]. Specific positioning systems ae modeled using wappes. Even though platfoms such as Location Stack and PoLoS simplify the pocess of location sensing, they do not conside the distibuted natue of infomation about locations and focus on the location sensing and fusion function. Geogaphic infomation systems (GIS) and spatial databases povide poweful mechanisms to stoe and etieve location data [14]. They concentate on accessing lage amounts of spatial data. In ou scenaios, howeve, we have to addess issues such as connectivity acoss a netwok and mobility of clients, thus we have to use data distibution concepts, which ae only aely incopoated into existing GIS appoaches. Even though some of the platfoms above povide sevices to discove identifiable aeas, they do not solve the DLRP in its geneal meaning. E.g. in Nexus, a equesting client has to discove the appopiate seve fo the specific aea via a cental egiste. Requests concening multiple seves have to be caied out one afte the othe. LORE is built accoding to a fully centalized client/seve achitectue and does not suppot any distibuted stoage of location infomation. In the following, we descibe a fully distibuted infastuctue that efficiently solves the DLRP without any cental instance. 4

3 IADIS Intenational Confeence Applied Computing NIMBUS The Nimbus famewok suppots developes of location-awae applications. The pimay goal is to povide the most eniched location infomation including identifiable aeas. Once the eniched location infomation is deliveed to the application, the mobile client can use abitay mechanisms to execute the location-based sevice. Established mechanisms such as databases, component sevices, web sevices o simple socket connections can be used to get futhe infomation about the location (fig. 2, left). Fig. 2. Data flow and hieachies in the Nimbus famewok The Nimbus famewok has a mobile pat installed on the mobile system and a netwok pat poviding infomation about the location. The mobile pat takes aw positions and equests the netwok pat to povide an augmentation: it maps any local coodinates to WGS84 coodinates [3] and geneates identifiable aea infomation, which now can easily be pocessed by the application. Using a pedefined name scheme, identifiable aeas can be diectly used fo database queies o as pats of file names. Physical locations ae still useful fo all kinds of geometic queies, e.g. asking fo distances between locations o asking fo diections. Nimbus povides additional sevices elated to location-based sevices (e.g. geocasting) not pesented in this pape. 3.1 The Nimbus Location Model We want to descibe the concept of identifiable aeas in Nimbus moe pecisely. Let P denote the set of all physical locations inside the obseved aea (e.g. all WGS 84 coodinates fom a cetain depth up to a cetain altitude in the atmosphee). We call an aea S P with a cetain meaning an identifiable aea of P. To identify aeas not only by thei geomety, they have a name. An aea with its coesponding name is called a domain. Fo a domain d, d.name denotes the domain name, d.c the domain geomety. Futhe D denotes the set of all domains. Names of identifiable aeas could in pinciple be human-undestandable, but thee is no single human-undestandable epesentation which is suitable fo all conceivable applications. Thus, the aea names ae optimized fo the intenal Nimbus opeations. Once the name space is clealy defined, tansfoming a name to its final epesentation often means simply looking up a sting inside a table. Looking at eal-wold scenaios space is often stuctued hieachically, e.g. a oom is inside a building, a building is in a city and a city is in a county. Thus, we divide the space into hieachies. A hieachy contains domains with a simila meaning, e.g. domains of cities o geogaphical domains. Each hieachy has a oot domain and a numbe of subdomains; each of them can in tun be divided into subdomains. A top node of a subhieachy is called a maste of the coesponding subdomains. A link between a subdomain and its maste is called a elation; maste and subdomain ae called elated, denoted maste subdomain. Names of subdomains ae built simila to Intenet host names, i.e. <sub>.<maste>. Fig. 2 (ight) pesents example hieachies. 3.2 The Distibuted Location Resolution Poblem As ou initial goal, we want to solve the distibuted location esolution poblem (DLRP): Given a location p and a set of distibuted computes, each stoing a cetain set of identifiable aeas d i.c. Which aeas (identified by thei name d i.name) contain p? In fig. 2 (ight) point p esides in the domains A, y.a, x.b and B. Since a maste always fully encloses a subdomain, the esults A and B do not cay additional infomation. A sufficient answe to the question above 5

4 ISBN: IADIS is "y.a and x.b". Bowsing though all hieachies fom the oot down to the smallest domains containing p would cause a lage numbe of equests and netwok taffic in distibuted infastuctues. Theefoe, a second elationship between domains is intoduced, the association. Two domains d 1, d 2 ae associated, denoted d 1 ~ d 2, if they ae not elated and thei shaed aea is not fully coveed by thei espective subdomains. We intoduce the abbeviation Δ( d ) = d. c \ Ue. c (1) e D, d>e fo the domain's aea excluding the subdomains' aea and get the definition d 1 ~ d 2 : (d 1 ) (d 2 ) {}. (2) In fig. 2 (ight) the aea shaed by A and x.b is fully coveed by the domain y.a, thus A and x.b ae not associated since this link would not povide additional infomation. Stating at x.b, only y.a has to be checked. With the help of associations, we now sketch a solution fo the DLRP: DLRP(p) set of names look up an abitay domain d 0 with p (d 0 ) names {d 0.name} fo all d ~ d 0 do if p (d) names names {d.name} If an abitay domain d 0 is available that fulfils the fist condition, the algoithm can efficiently loop though the associated domains. Note that the algoithm assumes that at evey conceivable location, at least one domain d 0 is available that coves this location. This is usually tue fo eal scenaios. We conducted a fomal poof of coectness of this algoithm [12]. 3.3 Looking up Location Seves The question is how to find a domain d 0. To answe this question we now have to switch fom the model view to the infastuctual view of Nimbus in which the domains ae stoed on location seves. Each location seve can stoe a cetain amount of domains, called a cluste. Each location seve is esponsible fo a specific domain and all subdomains, fo which no othe location seve is set up. Associations, elations and aeas can be defined fo clustes and thus fo seves in a canonical manne: two clustes ae elated, if thee exist domains of each cluste that ae elated. An analogous definition can be made fo associations. A aea is the cluste aea without the subseves' cluste aeas. The elation between clustes foms the so-called cluste tee. Fig. 3 shows the infastuctue based on the stoage of clustes. This example uses moe ealistic hieachies impoted fom land suvey offices (see section 4). Fig. 3. The distibuted Nimbus infastuctue One could ague that the communication to un the algoithm above is not acceptable. Fotunately, the infastuctue can poactively collect a lot of infomation to avoid heavy netwok taffic at esolution time: a location seve that stats up, automatically discoves the maste seve and all associated seves and pefoms a egistation in ode to exchange the aeas. As a esult, all infomation equied by the algoithm above is stoed locally on each seve, also by the seve that contains d 0. A client has only to discove that 6

5 IADIS Intenational Confeence Applied Computing 2006 seve, which then can execute the algoithm's main loop. In addition, a client can cache pevious esults to impove the execution time even moe. As mobile uses ae distibuted among diffeent location seves, this infastuctue is highly scalable. The appoach does not oveload top-level location seves. One can add a seve and estuctue the espective hieachy, thus it is possible to add seve powe to the infastuctue in a simple way. When a mobile node moves to a specific location, it automatically looks up an appopiate location seve fo the new location, called the Local Location Seve (LLS). The LLS is the epesentative of the infastuctue fo a mobile node. In paticula, the LLS stoes the domain d 0 of the DLRP algoithm. Usually, the LLS can fully answe the queies without any futhe netwok tansactions. Inside the coveed aea, a use can move aound without looking up a new location seve. Only when a mobile use leaves a cetain aea, a new LLS has to be looked up. The lookup uses the following mechanisms: a mobile client eceives infomation about the LLS fom the positioning system, a mobile client pefoms a seach using boadcasting lookups (using e.g., MBone o UDP boadcast), o a mobile client asks anothe location seve (e.g. an old LLS) which eplies a ediect message fo a moe suitable seve. The fist mechanism is most effective, but equies adapting the positioning systems. Nimbus usually uses a combination of the latte two mechanisms. The client pefoms a lookup pocedue as illustated in fig. 4. Fig. 4. The lookup mechanism The coesponding algoithm can be sketches as follows: LLS_lookup LLS askedseves {}; ediect set of fome LLSs if ediect = {} send a boadcast message collect boadcast eplies ediect while not LLS found // i.e. no success message eceived etun eo, if no seve in ediect\askedseves is available send a ediect equest to the geometically neaest seve of ediect\askedseves add this seve to askedseves, emove fom ediect add ediect eply to ediect This algoithm indiectly pefoms a backtacking, if a sequence of ediects gets caught in a dead end. In contast to the esolution algoithm in section 3.2 which mainly uses the logical links between domains, the lookup mechanism is mainly based on thei geomety. Logical links ae only used to geneate answes to clients: a seve which eceives a boadcast o a ediect equest answes accoding to the following ules: If it is the LLS o knows the LLS as its maste, subseve o associated seve, it eplies a success message. If one of its maste, subseve o associated seve is geometically neae to the client, it eplies the neaest one in a ediect message. Othewise no eply is pefomed. It is impotant to note that a boadcast only is equied duing the fist statup. Once connected, a client can lookup an LLS with the help of a ediect equest to any othe seve. Fo this, clients cache addesses of fome LLSs. 3.4 Avoiding Reply Stoms A lookup via boadcast may each many seves. If evey seve answes, the esulting so-called eply stom could oveload a mobile client o its wieless connection. To educe the oveall netwok taffic, a seve e- 7

6 ISBN: IADIS plies a ediect with a cetain pobability. Fo this pupose, a andom numbe and [0, 1) is geneated and only if and < q ediect the ediect message is sent. The value of q ediect is computed accoding to the fomula q0 if < 0 q ediect ( ) = q00 / if 0 and (3) 0 othewise whee is the distance of the domain s bode to the given location; q 0 (0, 1] is the imum value of q ediect ; 0 0 is the imum distance that leads to q ediect = q 0 and 0 is the imum distance to get q ediect > 0. The vaiable is measued using geometic opeations. Fo futhe consideations, we assume that is significantly geate than 0. A easonable assignment is, e.g., q 0 = 0.8, 0 = 100 m and = 1 km. The function q ediect affects two quantities: the aveage numbe of boadcast eplies and the aveage distance of the neaest eplie. The client is inteested in getting a sufficient numbe of eplies without being oveloaded. In addition, the minimum distance of all eplies should be as nea as possible. We want to exploe some chaacteistics of q ediect which help to contol its behavio. The aveage numbe of aeas completely inside o cut by a cicle with adius can be appoximated by 2 nappox ( ) = π nov + 2π nov (4) Δ Δ whee is the aveage size of all aeas and n ov the aveage numbe of ovelapping aeas at a point in space. Then the expected numbe of boadcast eplies accoding to ou mechanism is 2π n ov 2π nov = = neply qb qediect ( ) d qb 2πq0nov0 1 ln( ) (5) Δ Δ Δ 2 0 Δ 0 whee q b is the pobability to each a seve with a boadcast message. Note that we assume a unifom distibution of hosts eceiving a boadcast. In eality, it depends on netwok-elated popeties not modeled by this analytical appoach. We futhe can appoximate the aveage distance of eplies by Δ ) 0 1 2π nov 2 2π nov = 2 6 = 2 eplyavg qediect ( ) + d (6) nappox ( ) Δ Δ Δ 1 + ln( ) 2 0 which does not depend on q b. As the client uses the neaest answe fo ediection, it is inteested in the expected neaest distance eplymin of all n eply eplies. Fo abitay distibutions, it is difficult o impossible to get a closed fomula fo this distance. In ou case, howeve, we appoximately have a unifom distibution of distances, which is one geat benefit of ou specific q ediect, not poved in this pape. If futhe is significantly geate than 0, we thus can appoximate eplymin by Δ Δ eplymin = (7) neply + 1 q 2 q 2 0n 0 (( 0 / 2) (1 ln( / 0 ))) 1/ qb πq0nov b π ov + Δ + + Δ 0 This appoximation is supisingly useful in eality as shown in ou evaluations. At this point we can summaize two benefits of q ediect. Fist, the client can easily contol the aveage numbe of eplies by, which can be inceased duing untime, if too few eplies aive on aveage. Fo geate, we nealy get a linea dependency of and n eply. Second, the expected distance of the neaest eply emains constant (and low) fo inceasing. As the numbe of ediect equests mainly depends on eplymin, we thus get a low taffic fo ediects. 4. EVALUATIONS The efficiency of the Nimbus mechanisms is evaluated with the help of seveal simulations which use eal impoted data fom the Geman land suvey office. In Gemany, the ATKIS database povides geospatial data fo govenmental puposes [7]. Fo the Nimbus poject, data coveing an aea of 84 km 2 in the aea of Hagen was puchased. It contains appox aw database ecods which wee conveted to appox Nimbus domains, divided into thee hieachies: a hieachy containing the city, pats of the city popeties, 8

7 IADIS Intenational Confeence Applied Computing 2006 sites and buildings, a hieachy containing those domains with a geogaphical meaning, cuently ives and lakes, and a hieachy containing oads and ailways. The location seve application consists of appox lines of Java code (basic libaies excluded). On a 2.8 GHz (Windows XP) compute, the location seve stoing appox domains geneates a esponse to a single esolution equest in 9.7 ms on aveage (only counting the CPU time, not consideing the netwok link). The fist measuements thus conside seveal clients simultaneously equesting esolutions ove the netwok. All caches wee switched off. Once eceiving a esolution esult, the next equest is sent without any delay. This causes a high load to the seves. The seves wee connected via a 100 MBit/s Ethenet switched netwok. The delay fo wieless phone connections would be highe, but with highe delays the measued effects ae diluted and the measuement esult would be less expessive. In addition, it is moe difficult to impose load on location seves using slow connections. Location seves ae Windows XP computes with a CPU speed between 1.8 and 2.8 GHz. The expeiments ae conducted fo 1, 2 and 3 seves (fig. 5, top left). Using moe than one location seve, the load of diffeent uses is distibuted. As expected, the appoach is scalable: the moe location seves ae used, the moe flat is the cuve. Wheneve in eality a location seve is oveloaded, new subseves can easily be intoduced. It is impotant to note that in eality a much highe numbe of uses pe location seve is needed to cause a specific load as clients use a cache and clients usually do not pemanently pefom esolution equests. As an example, we assume that an application needs one location equest pe second and, as a esult of using a cache, only one of five esolution equests ae caied out ove the netwok. Instead of 100 uses, we then get a total of 1000 uses that impose the same load to a single location seve. Fig. 5. Evaluations of Nimbus chaacteistics The next measuements pesent the effectiveness of the lookup mechanisms. As a wost case scenaio we assume a sepaate seve pe domain. The impoted data is chaacteized by U = m and nov = We futhe assume that only 5% of seves neae than answe the boadcast, i.e. qb = The function qediect is configued by 0 = 100 m and q0 = 0.8; is vaiable. Fig. 5 (bottom left) pesents the distance of eplying seves. Fom the netwok view, two futhe numbes ae impotant: eplies pe boadcast (fig. 5, top ight) and the ediects to find the LLS (fig. 5, bottom ight). The chats pesent numbes athe than netwok times as they ae moe meaningful. As a fist obsevation, the analysis pesented in section 3.4 is vey accuate even though the eal data has lage vaiations in, e.g., the size of U aeas. Second, the lookup algoithm effectively avoids eply stoms and 9

8 ISBN: IADIS on the othe hand allows a client to contol the numbe of boadcast eplies in a fine-gained manne with the help of. Thid, even though the numbe of eplies inceases, the numbe of ediects to each the LLS emains constant and low fo ou measuements, less than five ediects wee equied on aveage. 5. CONCLUSION AND FUTURE WORK The main goal of Nimbus is to offe eniched location infomation that is easy to pocess. Nimbus povides globally unique physical locations, independently of the undelying positioning systems and identifiable aeas accoding to a pedefined name space. Nimbus eached this goal with the following instuments: a location model which suppots efficient access to decentalized stoed aea data and a distibuted, self-oganizing infastuctue, easily to be administated, designed accoding to scalability issues. Pefomance evaluations show the efficiency and scalability of the appoach. Even though Nimbus eached a high level of completeness, thee ae some open issues. In the cuent implementation, Nimbus stoes domains with a public chaacte. Evey use can access all domains as, e.g., ives o cities have a cetain meaning fo the public. Some domains howeve should not be open fo eveyone, e.g. baacks in a militay aea. We ae cuently woking on appopiate access contol mechanisms. A second issue esults in mobile domains: tains o ships, e.g., pemanently change thei location. In pinciple, Nimbus suppots such domains, but such domains cause a high amount of updates messages. We cuently wok on a mechanism which avoids huge taffic and at the same time ensues consistency. REFERENCES 1. Beigl, M.; Zimme, T.; Decke, C.: A Location Model fo Communicating and Pocessing of Context, Pesonal and Ubiquitous Computing, Vol. 6, No. 5-6, Dec. 2002, Spinge-Velag, Chen, Y.; Chen, X. Y.; Rao, F. Y.; Yu, X. L.; Li, Y.; Liu, D.: LORE: An infastuctue to suppot location-awae sevices, IBM Jounal of Reseach & Development, Vol. 48, No 5/6, Sept. 2004, EUROCONTROL Euopean Oganization fo the Safety of Ai Navigation: WGS 84 - Implementation Manual, Bussels, Belgium, Feb Hightowe, J.; Bumitt, B.; Boiello, G.: The location stack: A layeed model fo location in ubiquitous computing, Poc. of the 4th IEEE Wokshop on mobile Computing Systems & Applications (WMCSA 2002), Callicoon, NY, USA, June IEEE Compute Society Pess, Hohl, F; Kubach, U.; Leonhadi, A.; Schwehm, M.; Rothemel, K.: Nexus - an open global infastuctue fo spatialawae applications, Poc. of the 5th Inten. Confeence on Mobile Computing and Netwoking (MobiCom '99), Seattle, WA, USA, ACM Pess 6. Kelsey Goup: Advetising and E-commece, Land Suvey Office Noth Rhine-Westphalia, 8. Leonhadt, U.: Suppoting Location-Awaeness in Open Distibuted Systems, PhD Thesis, Univ. of London, Open Geospatial Consotium, OGC Home Page, 10. Padhan, S.: Semantic Location, Pesonal Technologies, Vol. 4, No. 4, 2000, Pigouis, N.; Papazafeiopoulos G.; Maias, I.; Hadjiefthymiades S.; Meakos, L.: Building a Geneic Boke fo Location Retieval, Poc. of the IST Mobile & Wieless Communications Summit, Potugal, June Roth, J.: A Decentalized Location Sevice Poviding Semantic Locations, Infomatics Repot 323, Univesity of Hagen, Jan Schilit, B.; Adams, N.; Want, R.: Context-Awae Computing Applications, Wokshop on Mobile Computing Systems and Applications, Santa Cuz, CA, USA, Tomlin, C., D.: Geogaphic Infomation Systems and Catogaphic Modeling, Pentice Hall, UMTS Foum: Enabling UMTS/Thid Geneation Sevices and Applications, Repot 11, Oct. 2000, 10

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