Analysis and compare of location technologies supporting LBS

Location technology is the key part of location based service. Different technologies have different accuracy, modifying to network and cost of operating. Also these technologies have limitation to network. This paper compares existing popular location technologies and gives some suggestions about choosing of location technologies in GSM and CDMA systems.     

Density-based clustering method in the moving object database

With the rapid advance of wireless communication, tracking the positions of the moving objects is becoming increasingly feasible and necessary. Because a large number of people use mobile phones, we must handle a large moving object database as well as the following problems. How can we provide the customers with high quality service, that means, how can we deal with so many enquiries within as less time as possible? Because of the large number of data, the gap between CPU speed and the size of main memory has increasing considerably. One way to reduce the time to handle enquiries is to reduce the I/O number between the buffer and the secondary storage. An effective clustering of the objects can minimize the I/O-cost between them. In this paper, according to the characteristic of the moving object database, we analyze the objects in buffer, according to their mappings in the two-dimension coordinate, and then develop a density-based clustering method to effectively reorganize the clusters. This new mechanism leads to the less cost of the I/O operation and the more efficient response to enquiries.     

Hybrid location determination technology within urban and indoor environment based on Cell-ID and path loss

The location determination technology based on simple delay evaluations or GPS is not accurate enough or even impossible in urban and indoor environments due to the multi-path propagation. To enhance the location accuracy and reduce the operation cost within these environments, this paper proposes a novel hybrid location determination technology which combines CELL-ID with the database correlation method. The proposed method generate the prediction database of path loss according to CELL-ID, and after the computation the smallest squared error of measured path loss and the prediction path loss,the location of the mobile terminal is decided by the coordinates of the best matching matrix entry.     

Tracking data management using topology of moving object database system for moving object constrained trajectory in LBS application

Advances in wireless technologies and positioning technologies and spread of wireless devices, an interest in LBS (Location Based Service) is arising. To provide location based service, tracking data should have been stored in moving object database management system (called MODBMS) with proper policies and managed efficiently. So the methods which acquire the location information at regular time intervals then, store and manage have been studied. In this paper, we suggest tracking data management techniques using topology that is corresponding to the moving path of moving object. In our techniques, we update the MODBMS when moving object arrived at a street intersection or a curved road which is represented as the node in topology and predict the location at past and future with attribute of topology and linear function. In this technique, location data that are corresponding to the node in topology are stored, thus reduce the number of update and amount of data. Also in case predicting the location, because topology are used as well as existing location information, accuracy for prediction is increased than applying linear function or spline function.     

Design and analysis of generic LBS application developing platform

Location based services is promising due to its novel working style and contents. A software platform is proposed to provide application programs of typical location based services and support new applications developing efficiently. The analysis shows that this scheme is easy implemented, low cost and adapt to all kinds of mobile nework system.     

Version based spatial record management techniques for spatial database management system

The search operation of spatial data was a principal operation in existent spatial database management system, but the update operation of spatial data such as tracking are occurring frequently in the spatial database management system recently. So, necessity of concurrency improvement among transactions is increasing. In general database management system, many techniques have been studied to solve concurrency problem of transaction. Among them, multi-version algorithm does to minimize interference among transactions. However, to apply existent multi-version algorithm to improve concurrency of transaction to spatial database management system, the waste of storage happens because it must store entire version for spatial record even if only aspatial data of spatial record is changed. This paper has proposed the record management techniques to managese parating aspatial data version and spatial data version to decrease waste of storage for record version and improve concurrency among transactions.     

A recovery method using recently updated record information in shared-nothing spatial database cluster

A shared-nothing spatial database cluster is system that provides continuous service even if some system failure happens in any node. So, an efficient recovery of system failure is very important. Generally, the existing method recovers the failed node by using both cluster log and local log. This method, however, cause several problems that increase communication cost and size of cluster log. This paper proposes novel recovery method using recently updated record information in shared-nothing spatial database cluster. The proposed technique utilizes update information of records and pointers of actual data. This makes a reduction of log size and communication cost. Consequently, this reduces recovery time of failed node due to less processing of update operations.     

An efficient selectivity estimation method for spatial query optimization with topological relationships

Many commercial database systems maintain histograms to summarize the contents of relations and permit the efficient estimation of query result sizes and the access plan cost. In spatial database systems, most spatial query predicates are consisted of topological relationships between spatial objects, and it is very important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multidimensional histogram and the transformation scheme. Proposed scheme applies two-partition strategy on transformed object space to generate spatial histogram and estimates the selectivity of topological predicates based on the topological characteristics of the transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in most spatial query optimizers.     

Parallel recovery method in shared-nothing spatial database cluster system

Shared-nothing spatial database cluster system provides high availability since a replicated node can continue service even if any node in cluster system was crashed. However if the failed node wouldn‘t be recovered quickly, whole system performance will decrease since the other nodes must process the queries which the failed node may be processed. Therefore the recovery of cluster system is very important to provide the stable service. In most previous proposed techniques, external logs should be recorded in all nodes even if the failed node does not exist. So update transactions are processed slowly. Also recovery time of the failed node increases since a single storage for all database is used to record external logs in each node. Therefore we propose a parallel recovery method for recovering the failed node quickly.     

An improved R-tree based on childnode＇s probability

R-Tree is a good structure for spatial searching. But in this indexing structure, either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).