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Combining GPS and GSM Cell-ID positioning for Proactive Location-based Services Nico Deblauwe Peter Ruppel Department of Fundamental Electricity and Instrumentation Mobile and Distributed Systems Group Faculty of Engineering Institute for Informatics Vrije Universiteit Brussel, Belgium a Ludwig-Maximilians-Universit¨ t Munich, Germany Email: firstname.lastname@example.org Email: peter.ruppel@iﬁ.lmu.de Abstract—Mobile terminals with built-in GPS receivers are current position of a mobile target, which can be done either becoming more and more available, thus the public deployment in a terminal-based, terminal-assisted or network-based fash- of location-based services (LBS) becomes feasible. Upcoming LBS ion. No matter what procedure is chosen, there will always are no longer only reactive but getting more and more proactive, enabling the users to subscribe for certain events and get notiﬁed remain the problem that positioning consumes power on the when e.g. a friend approaches or a point of interest comes mobile target (except for the scenarios where electromagnetic within proximity. However, power consumption for continuous induction is used) and that mobile devices have limited battery tracking is still a mayor issue with mobile terminals. In this capacity. paper we deﬁne this problem and propose solutions for an energy- For proactive LBSs it is not necessary to have a constant efﬁcient combination of GPS and GSM Cell-ID positioning for mobile terminals. We introduce several strategies for extending spatio-temporal accuracy all the time in order to meet the the lifetime of the battery and show how these strategies can be requirements. E.g. a buddy tracker does not need to know integrated into existing middleware solutions. Simulations based the exact positions of other users when they are deﬁnitely far on a realistic proactive multi-user context conﬁrm the approach. away. Only if two users approach at an area within they might be in proximity, it is necessary to determine the exact position Index Terms—Proactive Location-based Services, GPS, GSM Cell-ID, Position Management in order to decide whether they really are close-by or not. Power consumption on the mobile device can be reduced if several positioning methods are combined in an efﬁcient I. I NTRODUCTION manner. Looking at positioning methods that are available Location-based services (LBSs) take into account the posi- with nowadays mobile phones or mobile network providers tion of one or several mobile targets in order to detect, process respectively, there are many alternatives like e.g. Cell-ID, and communicate spatial events. LBSs can be classiﬁed into EoTD, U-TDoA, OTDoA, GPS or A-GPS (refer to , , reactive or proactive services . While the former are simply  for more detailed explanations). Since most of the mobile invoked in a request-response manner (e.g. ”Where is the phones have not yet a built-in GPS receiver, the most widely next ATM from here?”), the latter automatically detect spatial available method today is Cell-ID. It is referred to as a method events a user has subscribed to beforehand, which means to derive the position of a terminal based on the coordinates that the targets need to be continuously tracked. Generally of the serving base transceiver station. Cell-ID positioning speaking proactive LBSs detect when a mobile target enters offers only very low accuracy but area-wide coverage and or leaves a certain geographical zone. Such a zone can be e.g. very low power consumption. GPS is favorable because of its a polygon-shaped area comprising a big shopping mall and the high accuracy, but it is the most power-consuming positioning LBS informs costumers automatically about special discount method and current mobile phone batteries last only a few offers when they enter the site. Or an offender tracking LBS hours when the GPS receiver is turned on. generates an alarm when a person released on parole departs The goal of this paper is to provide a mechanism for by more than a certain distance from his home address, leading proactive LBS that efﬁciently combines GPS with GSM Cell- to a circle-shaped zone with the center at the residence. A ID positioning in order to reduce the power consumption on third and particular challenging scenario is the correlation a mobile terminal. of the positions of multiple simultaneously moving targets, A central position management server is assumed for mon- e.g. a buddy tracker, which alerts a user automatically when itoring and tracking the mobile targets’ positions. Instead of one of her friends approaches. Such LBSs are also based collecting positions periodically, each terminal is conﬁgured on geographical zones, however, these zones are no more by the server dynamically with a so-called position update static but have to be changed over time. The underlying base request (PUreq). The messages are exchanged over the data mechanism is called proximity and separation detection and channel of a mobile network like GSM or UMTS. A PUreq will be described below. represents a certain geographical area, requesting the target All kinds of LBSs require mechanisms to determine the to report back with its position to the server when that area has been entered or left. That way the number of messages • If dist(ti , tj ) < ds , separation must not be detected. transmitted over the mobile network is signiﬁcantly reduced. Another way for managing these relations could be by using In the following, the mobile terminals are assumed to the n-body constraint as deﬁned in , which prescribes that possess a GPS receiver (either built-in or externally via a n moving objects are embraceable by a sphere of diameter d Bluetooth connection) and the capability to determine the ID at the same time. By choosing ds = dp = d, n = 2, and b = 0, of the GSM cell they are currently located within. For deriving the two formalisms yield the same result. Due to its broader the Cell-ID, different implementations are possible: one is scope, the ﬁrst formalism will be used in the remainder of this by using the Hayes command set (also colled AT-commands, work. a speciﬁc programming language originally developped for There is not much knowledge available on how to choose communication with modems), which is supported by most dp , ds and b in an optimal way. In order to avoid unstable phones. At the terminal two different positions can be known: behavior, it is a good practice to choose ds − dp > 2b to a high resolution GPS ﬁx and/or the GSM Cell-ID. By avoid repetitive state switching at the borderline of proxim- detecting when it is possible to use the low resolution Cell-ID, ity/separation . Furthermore will the exact choice of the and when there is the need to switch to GPS, it is possible to values depend on the envisaged application and environment. minimize the overall positioning cost for the terminal, being For a staff tracker in an indoor environment (e.g. with WLAN expressed here as the amount of consumed battery power. ﬁngerprinting as positioning technology), it makes sense to For this, efﬁcient server-side strategies have been developed choose values in the order of 50m. For an outdoor buddy to correlate the positions of several targets and issue PUreqs tracker application, values in the range of 100−500m are more to the terminals telling them when to switch from Cell-ID logical. Such an outdoor scenario is assumed in the remainder positioning to GPS and vice versa. of this paper. This paper is structured as follows: section II deﬁnes prox- imity and separation detection and presents new strategies for B. Reference strategy combing GPS and Cell-ID positioning. Section III evaluates There exists some research on managing proximity and the approach based on a simulation and section IV shows separation among mobile targets. For example, any of the how the approach can be integrated into an existing LBS strategies described in  or  could have been used as our middleware solution. Section V concludes the paper and reference strategy. They have in common that every terminal describes future work. gets assigned a free movement area. As long as a terminal II. D EVELOPED STRATEGIES stays inside its assigned area, per deﬁnition no changes in the Reducing the GPS usage can be reached through detecting proximity/separation relations are possible. Upon reception of the moments that Cell-ID is providing sufﬁcient accuracy for a position update message (PUmsg) from a terminal ti , which the envisaged application. Two different approaches can be happens when the free movement area is left, the positioning pursued: either the GPS receiver is switched off as much as server performs three actions: possible; or switching on the GPS receiver is postponed as 1) Poll the terminals for which proximity (or separation) much as possible. Both approaches are worked out, the ﬁrst is possible, because the minimal (maximal) distance be- being referred to as circle-based and the latter as cell-based tween the updated position of ti and their free movement strategies. First, proximity and separation are deﬁned formally, areas is smaller than dp (or bigger than ds ). Polling and the used reference strategy is explained. forces a terminal to transmit its current position to the server. A. Proximity and separation 2) Verify the proximity and separation relations for all the For detecting the spatial relation between every pair of involved terminals; inform the application if changes are terminals ti and tj , the distance dist(ti , tj ) is mapped to detected. one out of two states: proximity, when the two terminals are 3) Determine the new free movement areas for the set of located nearer to each other than a proximity distance dp , involved terminals, and inform them by sending out the or separation, when those two terminals have moved further PUreqs. away from each other again than a separation distance ds . To Because of its efﬁciency and fairly simple implementation, deal with the inaccuracies of positioning methods and to avoid we have opted to use the Dynamic Centered Circles (DCC) excessive position reporting in the neighborhood of dp and ds strategy, which was ﬁrst proposed in , as our reference respectively, a third parameter is needed, being the borderline strategy. Figure 1.a shows a snapshot of free movement areas tolerance b. Then proximity detection is deﬁned as follows : that were calculated with DCC. Each terminal ti is assigned • If dist(ti , tj ) < dp , proximity must be detected. a circular area (called distance job). The center point of the • If dp ≤ dist(ti , tj ) ≤ dp + b, proximity may be detected. circles is the last reported position, and the radii are chosen • If dist(ti , tj ) > dp + bp , proximity must not be detected. in such a way that the mutual distances between a pair of The separation conditions are formulated analogous: targets can never fall below (above) the proximity distance dp • If dist(ti , tj ) > ds + b, separation must be detected. (separation distance ds ) without either one of the two terminals • If ds ≤ dist(ti , tj ) ≤ ds + b, separation may be detected. leaving its circle and thus invoking a PUmsg. This allows Fig. 1. Spatial overview of the strategies, from left to right: a) The original DCC algorithm (GPS only); b) The client-side strategy (GPS and Cell-ID combined); c) The server-side strategy (GPS and Cell-ID combined). The gray area denotes the free movement area, which is circular for a distance job and has the cell shape for a zone job. the server to effectively monitor spatial relations without grid of equal-sized cells. The current cell of each target is needing to track the terminals continuously. The following always known at the location server, and thus this index is two sections present novel strategies that manage multiple only altered when a target performs a partition update, that positioning technologies efﬁciently at the mobile terminals. is when a cell change is reported. Based on the index, it is possible to divide up all ongoing queries (n-body constraints C. Circle-based strategies in their terms) issued to the location system into three classes: The following strategies are an extension of the GPS- Class A refers to queries which are certainly satisﬁed; class based approaches, like DCC (hence the name). The server B queries on the other hand can safely be assumed to be not will calculate the circular zones as before. By matching these satisﬁed. Finally, queries that cannot be answered based on distance jobs to the cell grid of the GSM network, each of the cell information alone are categorized as class C. them can be associated with two sets of cells: the safe cells, Strategy 3: Instead of deﬁning an own grid, we decided which are the cells that are fully contained by the circular to use the cells of the GSM network, with the Cell-ID being zone, and the border cells, which are the cells that coincide equivalent to their index. Now it is possible to break up the with the circular zone. There is no need for having the GPS list of involved terminals in two groups: receiver switched on while being in a safe cell, which leads to • Cell-ID list: terminals for which the accuracy of the a ﬁrst class of energy optimization strategies: when possible, cell grid is sufﬁcient to monitor proximity (when both the calculated distance job and a zone job with the list mindist(ci , cj ) > dp , with ci = cell(ti )) or separation of the safe cells will be sent to terminal. Figure 1.b shows (when maxdist(ci , cj ) < ds ) relations. These are equiv- a snapshot of the same situation; terminals t1 , t2 did receive alent to class A and B queries. a PUreq containing two jobs. Since there were no safe cells • GPS-list: terminals for which no statement can be made found for terminals t3 , t4 , their PUreq contains only a distance about proximity/separation based on information of the job. cells they reside in. This list is equivalent to class C When available, the terminal will opt for monitoring the queries. zone job, since it is more energy efﬁcient. There are now three The rightmost snapshot of ﬁgure 1 illustrates this: terminals possible ways to respond to the event of leaving a safe cell: t1 , t4 are part of the Cell-ID-list, and terminals t2 , t3 are on Strategy 1: switch on the GPS receiver and start monitoring the GPS-list (because mindist(c2 , c3 ) = 0). All the terminals the, less stringent, distance job. The server will only be notiﬁed that are part of the Cell-ID list will now receive a zone job if the circle is left. that contains their current cell. This forces a terminal to send a Strategy 2a: switch on the GPS receiver and transmit a new PUmsg when its current cell is left. For the terminals that PUmsg containing the GPS-determined position. are on the GPS-list, the DCC algorithm is used to calculate Strategy 2b: transmit a PUmsg containing the Cell-ID of distance jobs. Looking for safe cells for the terminals on the border cell that was entered. the GPS-list would not make sense, since the circles of the Refer to section III-B for a discussion on the intrinsic distance jobs are too small to contain safe cells. Actually, if differences between these strategies. the circle would contain a cell, in most cases a zone job would have been issued already. D. Cell-based strategy Xu and Jacobson presented in  an algorithm for managing III. E VALUATION spatial queries on a database more efﬁciently. In one of their For testing the applicability of the proposed strategies, indexing methods, the available space is subdivided into a a simulator was constructed to model the behavior of an Cell surface 0.22km2 0.14km2 0.08km2 0.03km2 (cell radius) (≈ 500m) (≈ 400m) (≈ 300m) (≈ 200m) 5 terminals 40% 38% 30% 20% 10 terminals 67% 58% 40% 33% 15 terminals 75% 68% 56% 39% 20 terminals 87% 75% 60% 43% TABLE I P ERCENTAGE OF TIME THAT THE GPS IS SWITCHED ON , IN DEPENDENCE OF THE CELL SIZE FOR 5,10,15 AND 20 MUTUALLY TRACKED TERMINALS ( USING STRATEGY 2 B ) consumption of all the different parts of a mobile terminal, so we chose to monitor the time that the GPS receiver is switched on. This provides a reasonable good indicator for the amount of battery power that can be saved. The global trend in ﬁgure 2 is that the percentage of time that the GPS is used is propor- Fig. 2. Percentage of time during which the GPS receiver is switched on in tional to the number of terminals. This is insurmountable, and dependence on number of terminals due to the decrease in free movement space per terminal. When comparing the different strategies mutually, one can notice that the server side strategy outperforms the other for N < 10, but LBS community. In a proactive fashion, a member of the shifts then to be the worst performing one. Strategies 2a and community is informed as soon as another member approaches 2b always outperform strategy 1 (about 10% extra saving of (=comes into proximity) or leaves again (=separation detec- GPS time). Strategy 2b slightly outperforms strategy 2a for tion). The goal of the simulation is to determine the percentage N = 10, afterwards this gain mitigates. The location of the of time the GPS receiver can be switched off at the mobile turn-over point (lying here around N = 10) where the server- terminal. First some details on the design are provided, after side strategy becomes less efﬁcient, is related to the size of which the simulation results are discussed in detail. the cells of the underlying network. This was veriﬁed by repeating the simulations for different A. Simulator design cell sizes. Table I shows how the efﬁciency increases for The simulator moves a conﬁgurable number of targets decreasing cell sizes; the ﬁrst column reﬂects a suburban on a ﬁeld of 7.5km by 5.5km and executes the proposed situation, and the last column could be a dense urban situation. strategies. The simulated time is close to 1.5h (5000s). Since Though 20 terminals might seem few for a service that will be our goal is comparing the proposed strategies to each other, mass deployed, it is actually a high number of users to track we have opted to study them in a rather agile environment simultaneously. Having thousands of users in a network does of continuously moving targets, that is, rest periods have not mean that all of them need to be tracked mutually: only the been explicitly excluded. We adopted a constant velocity of ones that are related need to be checked. Additionally, it’s not v = 50km/h. It has to be stressed that this is a worst because a contact list in a buddy tracker contains 100 names, case scenario because during the day users normally remain that all will be online at the same time. stationary quite often. The routes of the targets were calculated Besides stretching the time that the GPS is switched off as with a simple mobility model: each terminal moves with a much as possible, it is important to limit the number of times constant velocity into a constant direction, until the borders of that the GPS needs to be started. For a warm start, when the the test area are reached. There, a new direction is randomly ephemeris and almanac data are still present and valid (≈ not chosen. In  they showed that the choice of mobility model older than four hours), it takes 7 − 15s before a position ﬁx has no effect for the simulation results, when the goal is is obtained. For a hot start, that is when the time is known as comparing different strategies mutually. Finally, we did select well, this reduces to about 5s till the ﬁrst position ﬁx. For the a proximity distance dp of 150m, a separation distance ds of presented simulations, the latter case can be assumed relevant 300m and a borderline tolerance b of 50m. most of the time. Though the simulations do not take into account these startup delays explicitly, it is still possible to B. Simulation results get an idea of this effect by looking at a histogram (refer to The ﬁrst batch of simulations compares the different strate- ﬁgure 3) with the interval durations when the GPS is switched gies mutually. The reference strategy used is DCC (refer to on. Strategy 3 outperforms the other strategies; in less than section II-B). For the mobile phone network, cells with an 5% of the cases it needs to switch on the GPS for a short average size of 0.25km2 were chosen, which corresponds to a while (10s or less). Also strategy 2b performs rather well, sub-urban situation. The ideal measurement for evaluating the limiting the short GPS periods to about 10%. In a situation proposed strategies would be the actual battery usage (or life with 15 terminals (ﬁgure 3, right graph) one can see that in time). However, it is rather difﬁcult to model the exact energy almost 50% of the cases where the GPS is switched on, it will stay on for more than 150s. This means that strategies 3 and 2a will tend to use the GPS when there is a long-term need for a high resolution (e.g. when terminals are close to each other), and need it less for quick inbetween high-resolution ﬁxes. That in almost 65% of the cases the duration is less than 10s for strategy 2a is inherent to the algorithm and can be seen as it’s biggest shortcoming. Because the studied algorithms have correct performance (timely and faultless detection of proximity and separtion) as a requirement, it is impossible to avoid the need for high-resolution GPS ﬁxes every so often. Further experiments have shown that this need aggravates for an increasing number of terminals, but relaxes for smaller cell sizes. Finally the communication needs of the strategies needs to be veriﬁed. For mobile terminals, communication with the server passes over the air interface, for which cellular bearer services like GPRS, EDGE or UMTS can be used. Because Fig. 4. Number of messages per terminal in dependence on number of bandwidth is a scarce resource and because these services terminals are usually charged (either per used time unit, or per data volume), it is sensible to reduce the total amount of exchanged messages. Figure 4 shows that strategy 1 does not yield a job calculation: in contrast to the circle-based strategies, this signiﬁcant extra message load (less than 5%), compared to is limited to a single cell. Further optimization is possible, by DCC, which is used as reference. The increase in number of building a more hybrid algorithm. messages is caused by server-initiated pollings: a terminal will To put these ﬁgures in perspective for N = 5 terminals: a always respond with its active technology, being Cell-ID when terminal on the move, in a hostile environment of continuously monitoring the zone job. If this is insufﬁcient for the server, a and fast moving terminals, receives and transmits a message second polling is performed, requesting a GPS-position from on average every 30s (DCC) to 20s (cell-based strategy). By the terminal. This leads to a doubling of the polling messages relaxing the assumptions to the situation of a pedestrian user, compared to the GPS-only approach. Because the circle-based this reduces to the exchange of two messages (up and down strategies 2a and 2b transmit a PUmsg as soon as their most link) every 3 to 5 minutes. Additionally, in reality, a person stringent monitoring condition is violated, we did expect the will stand still at certain places for long periods (e.g. at home, increase, which lies around 20%. That strategy 2b performs at work) and short periods (e.g. in a shop or restaurant), so the marginally worse than strategy 2a is because some of the message count will be even smaller. Since accurate predictions PUmsg with Cell-ID will cause the server to initiate a polling would require a lot of assumptions on the user’s behavior for a GPS-position. For the cell-based strategy, the main reason pattern, we have opted not to do so. for the message load doubling lies in the less efﬁcient zone C. Conclusion We looked at different strategies for reducing the time that a GPS receiver is needed. From the evaluation, where the most dynamic proactive scenario was simulated, we can conclude that the third strategy performs best in most cases, since it combines a very good to acceptable reduction in GPS time with the attractive property that it does almost not need quick high resolution ﬁxes from time to time. This comes at the cost, however, of an increased message load, to be communicated over the air interface. Furthermore we can conclude that that strategy 2b and 2a have about the same performance when it comes to reducing the total GPS time. Strategy 2b should be given preference for its better interval duration properties. Finally, it can be seen that the ﬁrst, most simple, strategy allows already a reasonable GPS time reduction. These conclusions are valid for moving and stationary targets. However, the situation of two targets staying in each others direct vicinity for a longer time (e.g. ofﬁce or school Fig. 3. Duration of intervals that the GPS can be switched off. Simulation situation), is not dealt with efﬁciently by the presented al- for average cell size of 0.22km2 Cell size gorithms. Then the GPS receiver will stay switched on if no Fig. 6. Interaction between the mobile terminal, the positioning server, the GSM Cell-ID database and the location-based service. example, the results of mass war-driving campaigns can be easily undone by switching the network settings (e.g. channel allocations) at a semi-regular basis. As a consequence it is safe to assume that all the needed network information is available. Fig. 5. Layered architecture of positioning server  For the practical implementation, we suggest to use an external server for managing this GSM Cell-ID information (refer to ﬁgure 6), which allows a clear separation of the additional motion detection mechanism is used at the terminal. service and data provider. This way a service provider can IV. A RCHITECTURE easily serve clients of different networks operators, without that the data needs to be local. The latter is rather important A. Existing work for the mobile network providers, who are not very keen u K¨ pper et. al.  developed a layered architecture for on sharing information on their network in a structured way. proactive LBS that can be used to easily integrate the strate- When this data is managed by a separate GSM Cell-ID server gies described above. The goal is to hide the gathering and (basically a GIS server) with access control, possibly even correlation of the targets’ positions from the LBS application. linked to billing schemes, for the queries. This approach makes Figure 5 shows the layers of the model: even more sense if the approach gets extended to UMTS • The positioning layer deals with the positioning methods networks. Because of cell breathing, the shape of the cells that are present at the terminal. will change, and to deal with this a link to the current network • The low-level position management layer (LLPM) man- conﬁguration is needed. ages the different possibilities for controlling the termi- nals: by sending either a PUreq (containing a distance C. Implications on server architecture job and/or a zone job) or by polling the terminal directly. In contrast to the single-technology case, the accuracy of • The high-level position management layer (HLPM) the position information can vary for incoming PUmsgs. To monitors the positions of the terminals. Its main function deal with this we used two different classes for mapping a is managing the proximity and separation relations among terminal’s position: the different pairs of mobile targets. Functions for detect- ing spatial relations between more than two terminals, e.g. k-nearest neighbors or clique detection, are possible too. • The application layer enables LBS applications to sub- scribe for certain location-based events among mobile targets of interest and to get notiﬁed automatically. For proactive single user services like a city guide, an ap- plication can skip the HLPM layer and place directly a PUreq or perform a polling. B. GSM Cell-ID server We assume that it is not possible to use the GSM network for positioning purposes without the agreement and coopera- tion of the mobile network operators. Since it is their network (and investment), it is not likely that they will allow an external organization to make money out of it. For protecting their investment, operators have both legal and technical tools at their disposal. The ﬁrst will mainly be used against companies, since it allows recuperating (a part of the) lost incomes; where Fig. 7. Process ﬂow in server, upon reception of a PUmsg from a terminal. the latter tool can serve to block community efforts. For Left) for circle-based strategies; Right) for cell-based strategy • Point, when the coordinates of the terminal are known • Multi-technology positioning servers. This paper de- precisely, which is the case for GPS. scribes the combination of GPS and GSM Cell-ID po- • Zone, when only the area in which the terminal is located sitioning. Most of the used concepts are actually tech- is known. Practically a zone will either be a polygon (if a nology independent, but the way they are implemented GSM cell is reported) or a circle (for modeling terminals is not general yet. For the development of a positioning inside distance jobs). server that is truly independent of the speciﬁc underlying Furthermore, if the accuracy of the incoming PUmsg is not technologies, more research about the LLPM layer needs sufﬁcient for proper operation, a polling with accuracy speci- to be done, especially how it will interact with the un- ﬁcations needs to be sent out, forcing the terminal to switch on derlying positioning layer and above lying HLPM layer. his GPS receiver in the presented work. Figure 7 matches the • Though our work focuses on providing the needed func- strategies presented in sections II-C and II-D to the HLPM and tionality for proximity and separation detection in a multi- LLPM layers, where most of the modiﬁcations are located. user environment, it stays valid in a larger context. For For the circle-based strategies, no changes are needed in instance, the presented building blocks sufﬁce to develop the HLPM (refer to ﬁgure 7, left), which is the core of an electronic city-landmark guide that is energy-efﬁcient the positioning server. We have implemented DCC, for more (single user, proactive LBS). In a next step, this could detailed information on steps 1 to 3, refer to section II.B. The be extended to a public transport navigation LBS  by LLPM layer needs one extra block (number 4) to match the connecting the positioning server to the database with distance jobs against the cell structure. This is not done for vehicle positions, modeling each of them as moving the jobs that originate from separation detection, as their radii landmark. are in 90% of the cases too small. For the cell-based strategy, ACKNOWLEDGMENTS extra processing blocks need to be added to the HLPM (refer to ﬁgure 7, right). Blocks 2 and 4 take care of the veriﬁcation A part of this research is supported by a grant of the IWT, of the proximity relations, and blocks 3 and 5 take care of the the Flemish Institute for the improvement of the scientiﬁc- job creation. technological research in industry. The connection to the GSM Cell-ID server could be made R EFERENCES either at the LLPM or HLPM level. Considering the functional u  A. K¨ pper, G. Treu, and C. Linnhoff-Popien, “TraX: A Device-centric u description of the layers from K¨ pper et. al. , the best place Middleware Framework for Location-based Services,” IEEE Communi- to provide an interface would be the LLPM. The HLPM needs cations Magazine, vol. 44, no. 9, pp. 114–120, September 2006. to be aware off the possibility to use Cell-ID positioning. The  C. Drane, M. Macnaughtan, and C. Scott, “Positioning gsm telephones,” IEEE Communications Magazine, vol. 36, no. 4, pp. 46–54, April 1998. LLPM takes care of managing which terminal uses which  F. Gustafsson and F. Gunnarsson, “Mobile positioning using wireless network and provide the actual data to the HLPM. networks,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 41–53, July 2005. V. C ONCLUSIONS AND FUTURE WORK  G. S. et all., “Signal processing techniques in network-aided positioning,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 12–23, July 2005. We have demonstrated in this paper that it is possible to u  A. K¨ pper and G. Treu, “Efﬁcient proximity and separation detection combine GPS and GSM Cell-ID positioning in a sensible way. among mobile targets for supporting location-based community services,” Our main contributions are 1) a set of concrete strategies ACM SIGMOBILE Mobile Computing and Communications Review, vol. 10, no. 3, pp. 1–12, July 2006. usable for proactive LBS in a multi-user environment (≈  Z. Xu and H.-A. Jacobsen, “Efﬁcient constraint processing for location- tracking); 2) an evaluation of these strategies using multiple aware computing,” in MDM ’05: Proceedings of the 6th international criteria; and 3) an onset on how to implement a tracking conference on Mobile data management. New York, NY, USA: ACM Press, 2005, pp. 3–12. server using multiple positioning technologies. In an suburban  A. Amir, A. Efrat, J. Myllymaki, L. Palaniappan, and K. Wampler, environment, the GPS receiver can be switched off between “Buddy tracking - efﬁcient proximity detection among mobile friends,” 13% (20 users simultaniously tracked) and 60% (5 users) in Proceedings of IEEE INFOCOM 2004, 2004, pp. 298–309.  N. Deblauwe and L. V. Biesen, “An event-driven lbs for public transport: of the time. In a dense urban environment, these numbers design and feasibility study of gsm-based positioning,” in Proceedings of improve to 57% and 80% respectively. The major positive the 45th FICE congress Athens, 2005, pp. 29–35. impact on the lifetime of the terminal’s battery can be clearly seen. We would suggest three directions for the further work: • Further development of the strategies. There is still a potential to improve the presented strategies: e.g. re- ducing the message count for the cell-based strategy, or taking into account the border cells for the circle-based strategies. Furthermore, the development of a prototype has started. We expect to have to adjust the strategies slightly in order to assure performance in real life, for which we have found two mobile network providers willing to provide the needed data.
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