• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.27-36
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• 2010

The paper proposes RFB(Record Filtering using Bit-vector) join algorithm, an in-network strategy that uses bit-vector to drastically reduce the size of data and hence the communication cost. In addition, by eliminating data not involved in join result prior to actual join, communication cost can be minimized since not all data need to be moved to the join nodes. The simulation result shows that the proposed RFB algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join(SNJ) algorithm.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.126-134
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• 2011

Recently, many researchers are interested in using join queries to correlate sensor readings stored in different regions. In the conventional algorithm, the preliminary join coordinator collects the synopsis from sensor nodes and determines a set of sensor readings that are required for processing the join query. Then, the base station collects only a part of sensor readings instead of whole readings and performs the final join process. However, it has a problem that incurs communication overhead for processing the preliminary join. In this paper, we propose a novel energy-efficient in-network join scheme that solves such a problem. The proposed scheme determines a preliminary join coordinator located to minimize the communication cost for the preliminary join. The coordinator prunes data that do not contribute to the join result and performs the compression of sensor readings in the early stage of the join processing. Therefore, the base station just collects a part of compressed sensor readings with the decompression table and determines the join result from them. In the result, the proposed scheme reduces communication costs for the preliminary join processing and prolongs the network lifetime.

• Journal of KIISE:Databases
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• v.37 no.3
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• pp.165-170
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• 2010

This paper proposes an in-network join strategy SBJ(Semi & Bloom Join), an efficient join strategy for sensor networks, that minimizes communication cost. SBJ is a hybrid join strategy that can reduce energy consumption by using a bloom filter to reduce the size of data that needs to be sent or received in sensor network. The key to reducing the communication cost in SBJ is to eliminate data not involved in the join result in the early stages of join processing. Through simulation, the paper shows that compared to other join strategies in sensor network, SBJ join strategy is more efficient in reducing the communication cost resulting in a significant reduction in battery consumption.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.220-230
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• 2013

In recent years, progress in hardware technology has resulted in the possibility of monitoring many events in real time. The volume of incoming data may be so large, that monitoring all individual data might be intractable. Revisiting any particular record can also be impossible in this environment. Therefore, many database schemes, such as aggregation, join, frequent pattern mining, and indexing, become more challenging in this context. This paper surveys the previous efforts to resolve these issues in processing data streams. The emphasis is on specifying and processing sliding window queries, which are supported in many stream processing engines. We also review the related work on stream query processing, including synopsis structures, plan sharing, operator scheduling, load shedding, and disorder control.