Energy and Latency Efficient Access of Wireless XML Stream

2010 ◽  
Vol 21 (1) ◽  
pp. 58-79 ◽  
Author(s):  
Jun Pyo Park ◽  
Chang-Sup Park ◽  
Yon Dohn Chung

In this article, we address the problem of delayed query processing raised by tree-based index structures in wireless broadcast environments, which increases the access time of mobile clients. We propose a novel distributed index structure and a clustering strategy for streaming XML data that enables energy and latencyefficient broadcasting of XML data. We first define the DIX node structure to implement a fully distributed index structure which contains the tag name, attributes, and text content of an element, as well as its corresponding indices. By exploiting the index information in the DIX node stream, a mobile client can access the stream with shorter latency. We also suggest a method of clustering DIX nodes in the stream, which can further enhance the performance of query processing in the mobile clients. Through extensive experiments, we demonstrate that our approach is effective for wireless broadcasting of XML data and outperforms the previous methods.

Author(s):  
Jun Pyo Park ◽  
Chang-Sup Park ◽  
Yon Dohn Chung

In this article, we address the problem of delayed query processing raised by tree-based index structures in wireless broadcast environments, which increases the access time of mobile clients. We propose a novel distributed index structure and a clustering strategy for streaming XML data that enables energy and latency-efficient broadcasting of XML data. We first define the DIX node structure to implement a fully distributed index structure which contains the tag name, attributes, and text content of an element, as well as its corresponding indices. By exploiting the index information in the DIX node stream, a mobile client can access the stream with shorter latency. We also suggest a method of clustering DIX nodes in the stream, which can further enhance the performance of query processing in the mobile clients. Through extensive experiments, we demonstrate that our approach is effective for wireless broadcasting of XML data and outperforms the previous methods.


2005 ◽  
Vol 06 (03) ◽  
pp. 303-321 ◽  
Author(s):  
AGUSTINUS BORGY WALUYO ◽  
BALA SRINIVASAN ◽  
DAVID TANIAR

Data dissemination scheme has been of great interest due to its scalability. In mobile environment, the advantage of such scheme is significant considering the inherent limitations of wireless environment. The application of broadcast indexing scheme in a wireless broadcast environment is necessary to help mobile clients to find the desired data instances efficiently. In this paper, we present a novel index structure called global indexing scheme for location-dependent queries. The proposed scheme is applied in a multi channel wireless environment and designed to serve queries efficiently in which the queries result depend on the mobile clients' current location. We develop a simulation model to find out the access time, tuning time and power consumption performance of global indexing scheme as compared to non-global indexing scheme. Additionally, we analyse the efficiency of valid scope used in the global index scheme as compared with an existing valid scope. It is found that global index performs substantially better than the existing indexing concept.


2017 ◽  
Vol 98 (1) ◽  
pp. 1299-1329 ◽  
Author(s):  
Yongrui Qin ◽  
Quan Z. Sheng ◽  
Hua Wang ◽  
Nickolas J. G. Falkner

Author(s):  
Wei Yan

In order to solve the problem of storage and query for massive XML data, a method of efficient storage and parallel query for a massive volume of XML data with Hadoop is proposed. This method can store massive XML data in Hadoop and the massive XML data is divided into many XML data blocks and loaded on HDFS. The parallel query method of massive XML data is proposed, which uses parallel XPath queries based on multiple predicate selection, and the results of parallel query can satisfy the requirement of query given by the user. In this chapter, the map logic algorithm and the reduce logic algorithm based on parallel XPath queries based using MapReduce programming model are proposed, and the parallel query processing of massive XML data is realized. In addition, the method of MapReduce query optimization based on multiple predicate selection is proposed to reduce the data transfer volume of the system and improve the performance of the system. Finally, the effectiveness of the proposed method is verified by experiment.


Author(s):  
Yan Qi ◽  
Huiping Cao ◽  
K. Selçuk Candan ◽  
Maria Luisa Sapino

In XML Data Integration, data/metadata merging and query processing are indispensable. Specifically, merging integrates multiple disparate (heterogeneous and autonomous) input data sources together for further usage, while query processing is one main reason why the data need to be integrated in the first place. Besides, when supported with appropriate user feedback techniques, queries can also provide contexts in which conflicts among the input sources can be interpreted and resolved. The flexibility of XML structure provides opportunities for alleviating some of the difficulties that other less flexible data types face in the presence of uncertainty; yet, this flexibility also introduces new challenges in merging multiple sources and query processing over integrated data. In this chapter, the authors discuss two alternative ways XML data/schema can be integrated: conflict-eliminating (where the result is cleaned from any conflicts that the different sources might have with each other) and conflict-preserving (where the resulting XML data or XML schema captures the alternative interpretations of the data). They also present techniques for query processing over integrated, possibly imprecise, XML data, and cover strategies that can be used for resolving underlying conflicts.


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