Author(s):  
Say Ying Lim ◽  
Siew Fan Wong

With the increased usage of mobile devices, society is seeing more and more users doing transactions wirelessly. Often, data from a single server may not be sufficient. Rather, data may need to be manipulated and to be gathered from multiple remote servers before useful information can be formed. Mobile transactions are constrained by small screen size of mobile devices, high communication cost, and high memory consumption. Existing techniques from traditional query processing in distributed environments cannot be directly applied to mobile environments. In this paper, the authors propose techniques for processing mobile queries that address the issue of high memory consumption. A set of walkthrough examples was provided and performances of various techniques were examined. The results show that the technique of first downloading primary keys only from one server and then sending a query to the second server using these primary keys before processing for qualified match in the second server gives the best performance.


Author(s):  
Mingzhu Wei ◽  
Ming Li ◽  
Elke A. Rundensteiner ◽  
Murali Mani ◽  
Hong Su

Stream applications bring the challenge of efficiently processing queries on sequentially accessible XML data streams. In this chapter, the authors study the current techniques and open challenges of XML stream processing. Firstly, they examine the input data semantics in XML streams and introduce the state-of-the-art of XML stream processing. Secondly, they compare and contrast the automatonbased and algebra-based techniques used in XML stream query execution. Thirdly, they study different optimization strategies that have been investigated for XML stream processing – in particular, they discuss cost-based optimization as well as schema-based optimization strategies. Lastly but not least, the authors list several key open challenges in XML stream processing.


2013 ◽  
Vol 284-287 ◽  
pp. 3507-3511 ◽  
Author(s):  
Edgar Chia Han Lin

Due to the great progress of computer technology and mature development of network, more and more data are generated and distributed through the network, which is called data streams. During the last couple of years, a number of researchers have paid their attention to data stream management, which is different from the conventional database management. At present, the new type of data management system, called data stream management system (DSMS), has become one of the most popular research areas in data engineering field. Lots of research projects have made great progress in this area. Since the current DSMS does not support queries on sequence data, this project will study the issues related to two types of data. First, we will focus on the content filtering on single-attribute streams, such as sensor data. Second, we will focus on multi-attribute streams, such as video films. We will discuss the related issues such as how to build an efficient index for all queries of different streams and the corresponding query processing mechanisms.


2018 ◽  
Vol 76 (6) ◽  
pp. 4040-4040
Author(s):  
Shobharani Pacha ◽  
Suresh Ramalingam Murugan ◽  
R. Sethukarasi

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