Continuous and Progressive XML Query Processing and its Applications

2010 ◽  
pp. 181-197
Author(s):  
Stéphane Bressan ◽  
Wee Hyong Tok ◽  
Xue Zhao
Keyword(s):  
Query Processing ◽  
Data Streams ◽  
Ad Hoc ◽  
Data Representation ◽  
Future Trends ◽  
Xml Query Processing ◽  
Processing Techniques ◽  
Xml Technologies ◽  
State Of Art ◽  
Open Issues

Since XML technologies have become a standard for data representation, a great amount of discussion has been generated by the persisting open issues and their possible solutions. In this chapter, the authors consider the design space for XML query processing techniques that can handle ad hoc and continuous XPath or XQuery queries over XML data streams. This chapter presents the state-of-art techniques in continuous and progressive XML query processing. They also discuss several open issues and future trends.

Spatial Data on the Move

2011 ◽  
pp. 103-118
Author(s):  
Wee Hyong Tok ◽  
Stéphane Bresan ◽  
Panagiotis Kalnis ◽  
Baihua Zhengl
Keyword(s):  
Query Processing ◽  
Spatial Data ◽  
Location Based Services ◽  
Spatial Query ◽  
Spatial Query Processing ◽  
Wide Availability ◽  
Research Problems ◽  
Processing Techniques ◽  
Exciting Area ◽  
State Of Art

The pervasiveness of mobile computing devices and wide-availability of wireless networking infrastructure have empowered users with applications that provides location-based services as well as the ability to pose queries to remote servers. This necessitates the need for adaptive, robust, and efficient techniques for processing the queries. In this chapter, we identify the issues and challenges of processing spatial data on the move. Next, we present insights on state-of-art spatial query processing techniques used in these dynamic, mobile environments. We conclude with several potential open research problems in this exciting area.

Spatial Data on the Move

2010 ◽  
pp. 850-864
Author(s):  
Wee Hyong Tok ◽  
Stéphane Bressan ◽  
Panagiotis Kalnis ◽  
Baihua Zheng
Keyword(s):  
Query Processing ◽  
Spatial Data ◽  
Location Based Services ◽  
Spatial Query ◽  
Spatial Query Processing ◽  
Wide Availability ◽  
Research Problems ◽  
Processing Techniques ◽  
Exciting Area ◽  
State Of Art

The pervasiveness of mobile computing devices and wide-availability of wireless networking infrastructure have empowered users with applications that provides location-based services as well as the ability to pose queries to remote servers. This necessitates the need for adaptive, robust, and efficient techniques for processing the queries. In this chapter, we identify the issues and challenges of processing spatial data on the move. Next, we present insights on state-of-art spatial query processing techniques used in these dynamic, mobile environments. We conclude with several potential open research problems in this exciting area.

XML Benchmarking

2010 ◽  
pp. 309-327 ◽  
Author(s):  
Irena Mlynkova
Keyword(s):  
Data Representation ◽  
Xml Data ◽  
Xml Technologies ◽  
Open Issues

Since XML technologies have become a standard for data representation, numerous methods for processing XML data emerge every day. Consequently, it is necessary to compare the newly proposed methods with the existing ones, as well as analyze the effect of a particular method when applied to various types of data. In this chapter, the auhtors provide an overview of existing approaches to XML benchmarking from the perspective of various applications and show that to date the problem has been highly marginalized. Therefore, in the second part of the chapter they discuss persisting open issues and their possible solutions.

Data Streams Processing Techniques Data Streams Processing Techniques

2017 ◽  
pp. 320-344
Author(s):  
Fatma Mohamed ◽  
Rasha M. Ismail ◽  
Nagwa. L. Badr ◽  
Mohamed F. Tolba
Keyword(s):  
Query Processing ◽  
Data Streams ◽  
Optimization Technique ◽  
Integrated System ◽  
Continuous Query ◽  
Stream Data ◽  
Parallel And Distributed Processing ◽  
Fast Processing ◽  
Data Elements ◽  
Processing Techniques

Many modern applications in several domains such as sensor networks, financial applications, web logs and click-streams operate on continuous, unbounded, rapid, time-varying streams of data elements. These applications present new challenges that are not addressed by traditional data management techniques. For the query processing of continuous data streams, we consider in particular continuous queries which are evaluated continuously as data streams continue to arrive. The answer to a continuous query is produced over time, always reflecting the stream data seen so far. One of the most critical requirements of stream processing is fast processing. So, parallel and distributed processing would be good solutions. This paper gives (1) analysis to the different continuous query processing techniques; (2) a comparative study for the data streams execution environments; and (3) finally, we propose an integrated system for processing data streams based on cloud computing which apply continuous query optimization technique on cloud environment.

scholarly journals Opportunistic routing based on partial CSI in MIMO random ad-hoc networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yiftach Richter ◽  
Itsik Bergel
Keyword(s):  
Ad Hoc Networks ◽  
Wireless Ad Hoc Networks ◽  
Data Streams ◽  
Ad Hoc ◽  
Multiple Input Multiple Output ◽  
Opportunistic Routing ◽  
Statistical Characterization ◽  
Routing Scheme ◽  
Single Antenna ◽  
Hoc Networks

AbstractIn this paper we consider opportunistic routing in multiple-input–multiple-output (MIMO) random wireless ad-hoc networks (WANETs). Our analysis uses a proper model of the physical layer together with an abstraction of the higher communication layers. We assume that the nodes are distributed according to a Poisson point process and consider a routing scheme that opportunistically selects the next relay and the number of spatially multiplexed data streams. The routing decisions are based on geographic locations, the channel gains of the neighbor nodes, and the statistical characterization of all other nodes. Unlike the single antenna case, the optimal routing scheme cannot be explicitly expressed. Hence, we propose a smart-routing scheme for MIMO that adapts the number of data streams per user to the channel conditions. The numerical results demonstrate that this scheme outperforms all previously published schemes for this scenario. The findings highlight the importance of channel state information for efficient routing, and the need for an adaptive selection of the number of data streams at each transmitter.

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