In moving object database, the moving objects’ current position must be kept in memory, also to the trajectory, in some case, as same as the future. But the current existing indexes such as SEB tree, SETI tree, 2+3R ...In moving object database, the moving objects’ current position must be kept in memory, also to the trajectory, in some case, as same as the future. But the current existing indexes such as SEB tree, SETI tree, 2+3R tree, 2 3RT tree and etc. can only provide the capability for past and current query, and the TPR Tree, TPR * Tree and etc. can only provide the capability for current and future query. None of them can provide a strategy for indexing the past, current and also the future information of moving objects. In this paper, we propose the past current future Index (PCFI Index) to index the past, current & future information of the moving objects. It is the combination of SETI tree and TPR * tree, the SETI liking index is used for indexing the historical trajectory segments except the front line structure, and the moving objects’ current positions, velocities are indexed via the in memory frontline structure which mainly implemented with TPR * tree. Considering the large update operations on TPR tree of large population, a hash table considering cache sensitivity is also introduced. It works with the frontline part, leading a bottom up update of the tree. The performance analysis proves that the PCFI index can handle most of the query efficiently and provides a uniform solution for the trajectory query, time slice query, internal query and moving query.展开更多
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...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.展开更多
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 possibil...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).展开更多
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 larg...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.展开更多
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 accur...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.展开更多
基金This work is supported by University IT Ressearch Center Project in Korea.
文摘In moving object database, the moving objects’ current position must be kept in memory, also to the trajectory, in some case, as same as the future. But the current existing indexes such as SEB tree, SETI tree, 2+3R tree, 2 3RT tree and etc. can only provide the capability for past and current query, and the TPR Tree, TPR * Tree and etc. can only provide the capability for current and future query. None of them can provide a strategy for indexing the past, current and also the future information of moving objects. In this paper, we propose the past current future Index (PCFI Index) to index the past, current & future information of the moving objects. It is the combination of SETI tree and TPR * tree, the SETI liking index is used for indexing the historical trajectory segments except the front line structure, and the moving objects’ current positions, velocities are indexed via the in memory frontline structure which mainly implemented with TPR * tree. Considering the large update operations on TPR tree of large population, a hash table considering cache sensitivity is also introduced. It works with the frontline part, leading a bottom up update of the tree. The performance analysis proves that the PCFI index can handle most of the query efficiently and provides a uniform solution for the trajectory query, time slice query, internal query and moving query.
基金This work is supported by University IT Research Center ProjectKorea
文摘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.
基金This work is supported by University IT Research Center ProjectKorea.
文摘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).
基金This work is supported by University IT Research Center Project in KOREA.
文摘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.
基金This research was supported by University IT Research Center ProjectKorea
文摘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.
