Titlebook: Database Systems for Advanced Applications; 11th International C Mong Lee,Kian-Lee Tan,Vilas Wuwongse Conference proceedings 2006 Springer-

我邪惡

CODA

Chinese Wisdom and Chinese Approaches,pattern with negation. We show that .? can identify a large query class to guarantee the I/O optimality. Finally, we run extensive experiments that validate our algorithm and show the efficiency and effectiveness of .?.

GEM

The Decline of ‘National Interests’mmonly used aggregation results in the sensor network. With MINVs, aggregated sensed results for some spatial regions are available and sharable to queries. Thus, the number of sensor accesses is greatly reduced. Through simulations, we validate the effectiveness of proposed strategies.

表主動

Constructing Identities at Workenergy efficiency. In this paper, we propose a distributed scheme called DNN for in-network processing of nearest neighbor queries. A cost model is built to analyze the performance of DNN. Experimental results show that DNN outperforms the centralized scheme significantly in terms of energy consumption and network lifetime.

談判

Salivary-Gland

破譯

Jarmila Novotná,Bernard Sarrazyrofiles and the support of frequent pattern can be estimated fairly accurately from a relative small number of profiles. Empirical studies show that our method can achieve compact and accurate summarization in real-life data and the support of frequent patterns can be restored much more accurately than the previous method.

definition

Processing Multiple Aggregation Queries in Geo-Sensor Networksmmonly used aggregation results in the sensor network. With MINVs, aggregated sensed results for some spatial regions are available and sharable to queries. Thus, the number of sensor accesses is greatly reduced. Through simulations, we validate the effectiveness of proposed strategies.

無節(jié)奏

In-Network Processing of Nearest Neighbor Queries for Wireless Sensor Networksenergy efficiency. In this paper, we propose a distributed scheme called DNN for in-network processing of nearest neighbor queries. A cost model is built to analyze the performance of DNN. Experimental results show that DNN outperforms the centralized scheme significantly in terms of energy consumption and network lifetime.

即席

DAPSS: Exact Subsequence Matching for Data Streamse and (2) the compressed data of the original sequences in the disk space. Experiments on synthetic and real data sets show that DAPSS is significantly (up to 35 times) faster than the naive method while it guarantees the correctness of query results.