Data integration has evolved to provide efficient data management across distributed and heterogeneous data sources in grid ***, existing works in data integration consider little knowledge about the above application...
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Data integration has evolved to provide efficient data management across distributed and heterogeneous data sources in grid ***, existing works in data integration consider little knowledge about the above applications. In such settings, queries from the same application are processed independently.
In this paper, application properties are noticed in order to improve query performance for data integration. We present a general-purpose and wellmodular architecture for addressing data integration in grid (DIG) environment first, the modules of which can be flexibly deployed to adapt specific ***, special attention has been paid on query processing to accommodate application workflow with the component of query Flow Processor. It introduces multi-query optimization techniques to speed up overall response time for DIG.
In this paper, we address one of the wireless sensor network query processing issues posed due to the lack of support for multiple sensor network queries. The objective of the paper is to provide efficient and effecti...
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In this paper, we address one of the wireless sensor network query processing issues posed due to the lack of support for multiple sensor network queries. The objective of the paper is to provide efficient and effective support to multiple queries so that the set of queries are pre-processed before disseminating them into the sensor network. It is very important that only necessary works will be assigned to the sensor network by virtue of strict energy constraint. The problem is modeled by Minimum Set Cover, which is one of the NP-complete problems. We propose an optimization scheme called TAMPA - a Tabu search-based multiple queries optimization to find an optimal merge order. The final set of queries to be sent into the network then can be derived from that merge order. We evaluate the proposed algorithm by conducting extensive simulation studies. The results show that energy can be significantly saved while the overall workload still satisfies the user requirements.
The ever-increasing load on databases dictates that queries do not need to be processed one by one. multi-query optimization seeks to optimize queries grouped in batches instead of one by one. multi-query optimizers a...
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ISBN:
(纸本)3540290672
The ever-increasing load on databases dictates that queries do not need to be processed one by one. multi-query optimization seeks to optimize queries grouped in batches instead of one by one. multi-query optimizers aim at identifying inter and intra query similarities to bring up sharing of common sub-expressions and hence saving computer resources like time, processor cycles and memory. Of course, the searching takes some resources but so long as the saved resources are more than those used, there is a global benefit. Since queries are random and from different sources, similarities are not guaranteed but since they are addressed to the same schema, it is likely. The search strategy need to be intelligent such that it continues only when there is a high probability of a sharing (hence resource saving) opportunity. We present a search strategy that assembles the queries in an order such that. the benefits are high, that detects null sharing cases and therefore terminates the similar sub-expressions' search as well as removing sub-expressions which already exist else where so as to reduce subsequent searching procedures for a global advantage.
This paper proposes a model for interleaving the execution of multiple queries simultaneously. The queries are rewritten, in the context of each other, in order to induce common subexpressions (CSEs). A CSE will then ...
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ISBN:
(纸本)0769521088
This paper proposes a model for interleaving the execution of multiple queries simultaneously. The queries are rewritten, in the context of each other, in order to induce common subexpressions (CSEs). A CSE will then need to be evaluated once only and its result is used in the evaluation of the queries that contain it, thereby leading to cost saving over the conventional query-at-a-time scenario. Two important aspects characterize the proposed model. First, it rewrites the queries in such a way that the isolated CSEs are, themselves, heuristically efficient to evaluate during query execution. Second, it reduces the optimization overhead (due to query rewriting) by using a divide-and-conquer approach to deduce relationships among inter-query selection conditions on base relations while using only pattern matching to find relationships among higher-order subexpressions (those involving an arbitrary number of joins).
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