In this letter, we propose an energy-efficient in-network processing method for continuous grouped aggregation queries in wireless sensor networks. As in previous work, in our method sensor nodes partially compute aggregates as data flow through them to reduce data transferred. Different from other methods, our method considers group information of partial aggregates when sensor nodes forward them to next-hop nodes in order to maximize data reduction by same-group partial aggregation. Through experimental evaluation, we show that our method outperforms the existing methods in terms of energy efficiency.

There has been much interest in a spatial query which acquires sensor readings from sensor nodes inside specified geographical area of interests. A centralized approach performs the spatial query at a server after acquiring all sensor readings. However, it incurs high wireless transmission cost in accessing all sensor nodes. Therefore, various in-network spatial search methods have been proposed, which focus on reducing the wireless transmission cost. However, the in-network methods sometimes incur unnecessary wireless transmissions because of dead space, which is spatially indexed but does not contain real data. In this paper, we propose a hybrid spatial query processing algorithm which removes the unnecessary wireless transmissions. The main idea of the hybrid algorithm is to find results of a spatial query at a server in advance and use the results in removing the unnecessary wireless transmissions at a sensor network. We compare the in-network method through several experiments and clarify our algorithm's remarkable features.

In the area of wireless sensor networks, the efficient spatial query processing based on the locations of sensor nodes is required. Especially, spatial queries on two sensor networks need a distributed spatial join processing among the sensor networks. Because the distributed spatial join processing causes lots of wireless transmissions in accessing sensor nodes of two sensor networks, our goal of this paper is to reduce the wireless transmissions for the energy efficiency of sensor nodes. In this paper, we propose an energy-efficient distributed spatial join algorithm on two heterogeneous sensor networks, which performs in-network spatial join processing. To optimize the in-network processing, we also propose a Grid-based Rectangle tree (GR-tree) and a grid-based approximation function. The GR-tree reduces the wireless transmissions by supporting a distributed spatial search for sensor nodes. The grid-based approximation function reduces the wireless transmissions by reducing the volume of spatial query objects which should be pushed down to sensor nodes. Finally, we compare naive and existing approaches through extensive experiments and clarify our approach's distinguished features.

With rapid increase of information requirements from various application areas, there has been much research on the efficient information retrieval. A signature is an abstraction of information, and has been applied in many proposals of information retrieval systems. In this paper we evaluate the performance of various signature-based information retrieval methods and provide guidelines for the most effective usage to a given operational environment. We derive analytic performance evaluation models of these access methods based on retrieval time, storage overhead and insertion time. The relationships between various performance parameters are thoroughly investigated. We also perform simulation experiments by using wide range of parameter values and show that the performance experiments agree with those analytic models.

In this paper, we present an efficient index structure for NAND flash memory, called the Dynamic Forest (D-Forest). Since write operations incur high overhead on NAND flash memory, D-Forest is designed to minimize write operations for index updates. The experimental results show that D-Forest significantly reduces write operations compared to the conventional B+-tree.

We propose an efficient dynamic hash index structure suitable for a NAND flash memory environment. Since write operations incur significant overhead in NAND flash memory, our design of index structure focuses on minimizing the number of write operations for hash index updates. Through a set of extensive experiments, we show the effectiveness of the proposed hash index structure in a NAND flash memory environment.

In this paper, a new access method is proposed for current positions of moving objects on road networks in order to efficiently update their positions. In the existing index structures, the connectivity of edges is lost because the intersection points in which three or more edges are split. The proposed index structure preserves the network connectivity, which uses intersection oriented network model by not splitting intersection nodes that three or more edges meet for preserving the connectivity of adjacent road segments. The data node stores not only the positions of moving object but also the connectivity of networks.

Complex rule conditions are commonly required to describe complicated business semantics. In these cases, efficient condition evaluation is crucial for high performance of active database systems. Most previous works used the incremental evaluation techniques, whose operations are relatively expensive due to the processing based on the exact calculation of the condition expression. In this paper we propose a new filtering technique that effectively identifies false condition in an early stage of condition monitoring. Since the results of condition evaluation tend to be false in most practical cases, an efficient filtering method can highly facilitate fast condition evaluation. The proposed filtering technique is developed based on the new perspective of database state and database operations, i. e. , a vector space model. We first present vector representations of database states, database operations, and complex condition expressions. Then, we propose a filtering method based on the properties of a vector space, called the sphere containment test. Our proposed method determines the truth value of the rule conditions only with the delta vectors maintained in main memory. We compare our method with a typical incremental evaluation method and show that the proposed method can give a significant performance enhancement.

In this paper, we propose an effective Web cache admission control algorithm. By selectively admitting objects into the cache, the proposed algorithm can significantly reduce the amount of disk I/O on a Web cache while maintaining a high hit ratio. The proposed algorithm adaptively adjusts its own admission control parameter, requiring no user-supplied parameters. Through extensive experiments, we show the effectiveness of the proposed algorithm.