• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.61-69
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• 2021

On-demand broadcast is an effective data dissemination technique in mobile computing environments. This paper explores the issues for scheduling multi-data queries in on-demand broadcast environments, and proposes a new broadcast scheduling scheme named CASS. The proposed scheme prioritizes queries by reflecting the characteristics of multi-data queries, and selects the data that has not been broadcast in the query for the longest time as the broadcast data according to the query priority. Simulation is performed to evaluate the performance of CASS. The simulation results show that the proposed scheme outperforms other schemes in terms of the average response time since it can show highly desirable characteristics in the aspects of query data adjacency and data conflict rate.

• Journal of KIISE:Databases
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• v.32 no.4
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• pp.405-415
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• 2005

Indexing techniques are used to implement selective tuning in wireless environments Indices are broadcast together with data to help mobile clients locate the required information. As a result, clients stay in doze mode most of the time. The drawback of this solution is that broadcast cycles are lengthened due to additional index information. In location-aware mobile services(LAMSs), it is important to reduce the query response time, since a late query response nay contain out-of-date information. In this paper, we present a broadcast-based spatial query processing method (BBS) designed to support k-NN query processing. In the BBS, broadcasted data objects are sorted sequentially based on their locations, and the server broadcasts the location dependent data along with an index segment. The performance of this scheme is investigated in relation to various environmental variables, such as the distributions of the data objects, the average speed of the clients and the size of the service area.

• Journal of Korea Spatial Information System Society
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• v.10 no.1
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• pp.15-28
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• 2008

In ubiquitous sensor networks(USN) environment, it is essential to process region query for user-demand services. Using R-tree is a preferred technique to process region query for in-network query environment. In USN environment, USN middleware must select sensors that transfers region query with accuracy because the lifetime of sensors is that of whole sensor networks. When R-tree is used, however, it blindly passes the region query including non-existent sensors where MBR(Minimum Boundary Rectangle) of R-tree is Intersected by region of query. To solve in this problem, we propose a reconstruction of region query method which is a trie-structured Quad tree in the base station that includes sensors in region of query select with accuracy. We observed that the proposed method delays response time than R-tree, but is useful for reducing communication cost and energy consumption.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.3
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• pp.171-180
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• 2003

A content-based image retrieval(CBIR) system builds the image database using low-level features such as color, shape and texture and provides similar images that user wants to retrieve when the retrieval request occurs. What the user is interest in is a response time in consideration of the building time to build the index database and the response time to obtain the retrieval results from the query image. In a content-based image retrieval system, the similarity computing time comparing a query with images in database takes the most time in whole response time. In this paper, we propose the two-phase search method with the clustering technique of feature vector in order to minimize the similarity computing time. Experimental results show that this two-phase search method is 2-times faster than the conventional full-search method using original features of ail images in image database, while maintaining the same retrieval relevance as the conventional full-search method. And the proposed method is more effective as the number of images increases.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.453-463
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• 2002

With the prevalence of multi-dimensional data such as images, content-based retrieval of data is becoming increasingly important. To handle multi-dimensional data, multi-dimensional index structures such as the R-tree, Rr-tree, TV-tree, and MVP-tree have been proposed. Numerous research results on how to effectively manipulate these structures have been presented during the last decade. Query processing strategies, which is important for reducing the processing time, is one such area of research. In this paper, we propose query processing algorithms for R-tree based structures. The novel aspect of these algorithms is that they make use of the notion of VP filtering, a concept borrowed from the MVP-tree. The filtering notion allows for delaying of computational overhead until absolutely necessary. By so doing, we attain considerable performance benefits while paying insignificant overhead during the construction of the index structure. We implemented our algorithms and carried out experiments to demonstrate the capability and usefulness of our method. Both for range query and incremental query, for all dimensional index trees, the response time using VP filtering was always shorter than without VP filtering. We quantitatively showed that VP filtering is closely related with the response time of the query.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.438-449
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• 2004

More and more users are using the query e-mail according to the increment of use of internet. The operator of internet site desires the users to check the FAQ and Q＆A contents first before sending the query e-mail to the operator However the users try to get the solution for a problem easily by simply sending a query e-mail. Therefore the increment of query e-mail is inevitable, and the site operator is suffering from too heavy loads and spending too much time and cost to reply the query e-mail. In this paper, we are proposing an efficient method of classifying the query e-mail of users automatically by using a neural network. To verify the reasonability of our work, the query e-mails of KORNET are used as the test data, which is actually gathered in KT. A total of 210 learning data and 280 test data were used to test the performance of the proposed approach. From the experiments we got the encouraging result from the view point of application in real life. The proposed approach satisfied the request of users who wanted rapid response for their query e-mail.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.165-174
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• 2000

Recent researches about range queries in OLAP are only concerned with applying an aggregation operator over a certain region. However, data analysts in real world need not only the simple range query pattern but also an extended range query pattern that finds ranges which satisfy a special condition specified by using several aggregation operators. In this work, we define the general form of the extended range query and propose an efficient processing method for the 'MAX -of-SUM' query, which is the representative form of the extended range query pattern. The MAX-of-SUM query finds the range which has the maximum range sum value in data cube where the size of the range is given. The proposed query processing method is based on the prediction of the scope of the range sum values. That is, the search space on the query processing can be reduced by using the result of the prediction, and hence, the query response time is also reduced.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.89-97
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• 2011

In semantic web information system like ontology that access distributed information from network, efficient query processing requires an advanced caching mechanism to reduce the query response time. P2P network system have become an important infra structure in web environment. In P2P network system, when the query is initiated, reducing the demand of data transformation to source peer is important aspect of efficient query processing. Caching of query and query result takes a particular advantage by adding or removing a query term. Many of the answers may already be cached and can be delivered to the user right away. In web environment, semantic caching method has been proposed which manages the cache as a collection of semantic regions. In this paper, we propose the semantic caching technique in cluster environment of peers. Especially, using schema data filtering technique and schema similarity cache replacement method, we enhanced the query processing efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1569-1580
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• 2016

For the 2.4 GHz active RFID to be successful in the market, one of the requirements is the increased battery life. However, currently we do not have any accurate power consumption estimation method. In this study we develop a simulation model, which can be used to estimate power consumption of tag accurately. Six different simulation models are proposed depending on collision algorithm and query command method. To improve estimation accuracy, we classify tag operating modes as the wake-up receive, UHF receive, sleep timer, tag response, and sleep modes. Power consumption and operating time are identified according to the tag operating mode. Query command for simplifying collection and ack command procedure and newly developed collision control algorithm are used in the simulation. Other performance measures such as throughput, recognition time for multi-tags, tag recognition rate including power consumption are compared with those from the current standard ISO/IEC 18000-7.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1489-1515
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• 2022

The number of interconnected real-world devices such as sensors, actuators, and physical devices has increased with the advancement of technology. Due to this advancement, users face difficulties searching for the location of these devices, and the central issue is the findability of Things. In the WoT environment, keyword-based and geospatial searching approaches are used to locate these devices anywhere and on the web interface. A few static methods of indexing and ranking are discussed in the literature, but they are not suitable for finding devices dynamically. The authors have proposed a mechanism for dynamic and efficient searching of the devices in this paper. Indexing and ranking approaches can improve dynamic searching in different ways. The present paper has focused on indexing for improving dynamic searching and has indexed the Things Description in Solr. This paper presents the Things Description according to the model of W3C JSON-LD along with the open-access APIs. Search efficiency can be analyzed with query response timings, and the accuracy of response timings is critical for search results. Therefore, in this paper, the authors have evaluated their approach by analyzing the search query response timings and the accuracy of their search results. This study utilized different indexing approaches such as key-words-based, spatial, and hybrid. Results indicate that response time and accuracy are better with the hybrid approach than with keyword-based and spatial indexing approaches.