ACEEE Int. J. on Communication, Vol. 01, No. 03, Dec 2010
Resource Identification Using Mobile Queries S. R. Balasundaram1 , A. Saravanan2
1
Assistant Professor, 2Research Scholar 1 blsundar@nitt.edu 1,2 Department of Computer Applications National Institute of Technology,Tiruchirappalli ,India. 2 saro_manj@yahoo.com
distress being experienced during the journey, which is often a time consuming process. The current location of the mobile user will not help to provide the proper index for identifying the nearest required resources from the database. Most of the location based applications have considered only the current location as the index to get the details from the database. The results based on this index may not be an accurate one, because of the user’s mobility. Hence, prediction mechanism is needed for finding the future location of the mobile user, which would be used to define a proper index for identifying the resources from the database.
Abstract - Location based mobile services (LBS) are budding significantly along with development of GPS-enabled mobile phones, smart phones and PDAs. Mobile users may submit the query to the server for knowing about nearest resources such as fuel stations, hospitals, ATM centers etc to get the services. In this scenario, identifying locations of resources is highly significant. This paper focuses on query management in mobile environments to locate the most appropriate location of the required services. Index Terms Mobility, GPS mechanisms, Location based services, Mobile data, Query management.
I. INTRODUCTION With recent advances in wireless technologies and communications, mobile services are becoming an important part in day to day human life. The mobile environment consists of mobile users with information appliances (mobile devices) such as smart phones, cell phones or Personal Digital Assistants (PDA) that will be communicating and interacting with each other. Mobile technologies are extensively involved in real life activities and they allow users to have anytime, anywhere access to information and applications[1,2]. Locations play a vital role in mobile applications to provide the required details for users. For example, when a mobile user wants to find a shopping mall, he is not concerned with shopping mall that are far away from his current location, rather he wants to choose one from several shopping malls that are nearer to his current location. In this case, the application should get the user’s current location details for further processing.An essential part of locationbased application is locating the user’s current location. Global Positioning System (GPS) is a widely used technology for this purpose. With the advances in GPS mechanisms, wireless technologies and the growing popularity of mobile devices, the need for location-based services is gaining considerable attention[3]. Finding the nearest resources from the current location/area of a mobile user during his/her journey, will be a challenging one if the traveling area is long. It is important to identify the resource (like fuel station) as near as possible to the needy people (mobile users) during their journey (Figure 1). This would reduce the amount of
Figure 1. User on Mobility
II. MOBILE DATA MANAGEMENT Managing data in mobile environments is the most significant issues in mobile applications. Mobile data management deals with both local and global data in turn handling various activities such as data access, caching, query processing, location addressing, replication etc [4]. Various aspects of managing data have been dealt by researchers in different situations. Many have proposed location aware mechanisms for exploiting data from the fixed locations to manage data for convenience [5]. Hae Don Chon, Divyakant Agrawal and Amr El Abbadi have developed a location-based application, NAPA (Nearest Available Parking Lot Application), that assists users to find a nearest parking space on campus[6]. Lauri Aalto, Nicklas Gothlin, Jani Korhonen and Timo Ojala have focused on delivering permission-based 25
© 2010 ACEEE DOI: 01.IJCOM.01.03.550
ACEEE Int. J. on Communication, Vol. 01, No. 03, Dec 2010
location-aware mobile advertisements to mobile phones using Bluetooth positioning and Wireless Application Protocol(WAP) Push[7]. J. Hwang, H. Kang, and K. Li have proposed a similarity measure for spatio-temporal trajectories of vehicles. Similar trajectories are required to traverse the same points of interest(POIs)[8]. Ebtisam Amar and Selma Boumerdassi have proposed a location service called Predictive-Hierarchical Location Service (PHLS) that uses a hierarchy of regions to achieve scalability, and predicts the requested location by utilizing previous location information[9].
Assuming that, a mobile user is traveling on a straight path at constant speed, the past and current locations of the mobile users obtained through GPS mechanism, and the future location (xn+1,yn+1) can be predicted using the following formulae: Current and past positions are : (xn,yn) and (xn-1,yn-1). Distance of traveling from past to current position |pc| = √ ( xn - xn-1)2 + (yn - yn-1)2 Future position of xn+1 = xn + |pc| (1) and yn+1 = yn + |pc|. (2) Fig. 2 represents the movement of the mobile users noticed at locations L1 and L2. The future location Lp can be calculated and the nearest available resources (based on that location) will be identified. The methodology for finding the most appropriate location of the resource(s) is given in the following procedure.
A. Location Management Mobile devices, by their very nature, can be operated from a dynamic location. Anytime–anywhere communication and transmission of data uplifts the potentialities and advantages of mobile/wireless technologies. A location-aware or location-based service is highly significant in mobile environments which is driven by location information.Location dependent data depends on the geographical location. The answer to queries over location dependent data depends on the locations of the data and the place of query initiated.
Algorithm Procedure getResource( )
III. LOCATION PREDICTIONS
Begin Let L1,L2….Lp be locations. Let Li is the query initiated location. //Traveler sends request to server Let Lp is the calculated location //Server calculates the future location of traveler //and checks the locations of required Resources Let Resource_Location be the set of locations identified closer to Lp. If more than one location exists with the required resources then Begin d = min { distance(Lp,Resource_Location) }; Select the resource at distance d; End; End.
A number of methods for predicting locations have been discussed by many [10,11]. Most of the applications use the mobile data, i.e. current location, for predicting the future location for taking any decision. In this paper, the significance of the mobile data combined with the locations of resources kept in database is discussed, where the minimum distant resource location is to be identified. It should be noted that straightforward use of indexing is not feasible due to the continuous change of the locations of the mobile users. A. Global Positioning System Let us consider the location data obtained from GPS i.e. latitude and longitude values, the distance calculation will be done between future location of mobile users and resources.
________________________________________ IV. RESOURCE GEO-DATABASE Here, the resources that are taken for consideration specifically belong to the service centers such as ICICI ATM, HP fuel stations, Shopping malls and star rated restaurants. These details are stored in a database with their location name, latitude and longitude values (Table1).
Figure 2. Mobile Users with Available Resources
26 © 2010 ACEEE DOI: 01.IJCOM.01.03.550
ACEEE Int. J. on Communication, Vol. 01, No. 03, Dec 2010
Table 1. Resource_Geo_Database Location Name
Latitude and Longitude Lat ‘x2’ Long - ‘y2’ value value
SELECT Resources,Location,min(Diff) FROM Resource_Geo_Database WHERE Diff IN ( SELECT (sqrt(pow(x2-x1)+pow(y2-y1))) AS Diff FROM Resource_Geo_Database WHERE Resources = ‘Restaurant’ ) //‘Restaurant’: User data
Resources
Trichy
10.80834
78.70197
Fuel Station
Samayapura
10.92389
78.743553
Siruganoor
10.99889
78.793327
Perambalur
11.23611
78.86358
Viluppuram
11.95717
79.47946
Fuel Station, Restaurant Fuel Station, ATM center Fuel Station, ATM center, Shopping Mall Shopping Mall
Tindivanam
12.53579
79.08817
ATM center
Chengalpet
12.70024
79.98234
Tambaram
12.93152
80.1259
Chennai
13.06397
80.24311
Fuel Station
Tanjore
10.79556
79.137718
Fuel Station, Restaurant
Kumbakona
10.96462
79.39074
Shopping Mall
Mayavaram
11.10501
79.65095
ATM center
Thiruvarur
10.77287
79.63952
Fuel Station, Restaurant
Karur
10.95883
78.08597
ATM center, Shopping Mall, Restaurant
Namakkal
11.24438
78.17361
Fuel Station
Salem
11.67273
78.16049
Fuel Station, Restaurant
Dharmapuri
12.12781
78.16245
Fuel Station, ATM center
CONCLUSION Providing information to the needy people who are required the resources, during travel whose required resource(s) can be identified at the minimum distance is the major concern of this work. The significance of mobile technologies with the help of mobile devices and the location data management are discussed in this paper. The mobile data supports to retrieve the location of nearest resources in time and cost effective way.
Fuel Station, Restaurant ATM center, Shopping Mall Restaurant
REFERENCES [1] Vasilis Koudounas and Omar Iqbal, “Mobile Computing : Past, Present And Future,” retrieved from http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/vk5/report. html. [2] Sandeep Jain, “Introduction to Mobile Computing : The way the world is changing!,” retrieved from http://www.acm.org/crossroads/xrds7-2/intro72.html [3] Khondker Shajadul Hasan, Mashiur Rahman, Abul L. Haque, M Abdur Rahman, Tanzil Rahman and M Mahbubur Rasheed, “Cost Effective GPS-GPRS Based Object Tracking System,” Proceedings of the International MultiConference of Engineers and Computer Scientists, Vol I, IMECS 2009, March 18 - 20, Hong Kong. [4] Vijay Kumar, Mobile Database Systems, John Wiley & Sons,Inc. Publication, 2006. [5] Uwe Kubach and Kurt Rothermel, “Estimating the Benefit of Location-Awareness for Mobile Data Management Mechanisms,” Pervasive 2002, LNCS 2414, pp. 225–238, Springer-Verlag Berlin Heidelberg, 2002. [6] Hae Don Chon, Divyakant Agrawal and Amr El Abbadi, “NAPA :Nearest Available Parking lot Application,” IEEE Proceedings of the 18th International Conference on Data Engineering, 2002. [7] Lauri Aalto, Nicklas Göthlin, Jani Korhonen and Timo Ojala, “ Bluetooth and WAP Push Based Location-Aware Mobile Advertising System,” MobiSys’04, June 6–9, Boston, Massachusetts, USA, 2004. [8] J. Hwang, H. Kang and K. Li, “Spatio-temporal Similarity Analysis Between Trajectories on Road Networks,” In Proc. of the International Workshop on Conceptual Modeling for Geographic Information Systems, pp. 280–289, 2005. [9] Ebtisam Amar and Selma Boumerdassi, “Enhancing Location Services with Prediction,” IWCMC’09(ACM), June 21–24, Leipzig, Germany, 2009. [10] George Liu and Gerald Maguire Jr, “A Class of Mobile Motion Prediction Algorithms for Wireless Mobile Computing and Communications,” Mobile Networks and Applications1, pp.113121, A J.C. Baltzer AG Science Publishers, 1996. [11] Liu.T, Bahl. P and Chlamtac. I, “A Hierarchical PositionPrediction Algorithm for Efficient Management of Resources in Cellular Networks,” Proceedings of the IEEE GLOBECOM’97, Phoenix, Arizona, 1997.
A. Finding Nearest Resources When there are more than one resource available to the predicted location, choosing the nearest resource is one of the major features of this work. In the context of providing minimum distant resource to the mobile user, the system involves the following distance calculation. After submitting the query to the server, the predicted location of a mobile user can be calculated by the equations 1 and 2. Diff = sqrt(pow(x2-x1)+pow(y2-y1)) Here, Diff is the distance between two coordinates (lat1,long1) and (lat2, long2). Where (x1,y1) = Predicted location of mobile user and (x2,y2) = Location of resources (Specified as ‘latitude’ and ‘longitude’ in the Table 1) B. Query The nearest location of the resources can be retrieved by the following SQL query: 27 © 2010 ACEEE DOI: 01.IJCOM.01.03.550