Mobile Information Processing Involving Multiple Non-Collaborative Sources

Mobile Information Processing Involving Multiple Non-Collaborative Sources

Say Ying Lim (Monash University, Australia)
DOI: 10.4018/978-1-60566-148-3.ch008
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As more and more servers appearing in the wireless environment provide accesses to mobile users, more and more demand and expectation is required by mobile users toward the available services. Mobile users are no longer satisfied with obtaining data only from one server, but require data from multiple servers either at the same or different locations. This eventually leads to the need for information gathering that spans across several non-collaborative servers. This article describes some of our researches in information gathering from multiple non-collaborative servers that may involve servers that not only accept direct queries from mobile users but also servers that broadcast data. We also look at how location dependent data plays an important role to mobile information gathering.
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The direction of the mobile technology industry is beginning to emerge and advance at a rapid pace as more mobile users have evolved (Myers & Beigl, 2003). Interests in mobile technology have grown exponentially over the last few years and are greatly influenced especially by the dramatic reduction in the cost of hardware and protocol standardization (Hurson & Jiao, 2005; Kapp, 2002). The increase in progression and advancement of mobile technology has created a new paradigm of computing called mobile computing in which people are allowed to be connected wirelessly to access data anytime, anywhere without having to worry about the distance barrier (Lee, Zhu, & Hu, 2005; Lee et al., 2002; Madria, Bhargava, Pitoura, & Kumar, 2000). Users have also become more productive with the achievement of mobility since they are able to access a full range of resources regardless of where they are located and where they are able to get hold of real time information.

The emerging growth of the use of intelligent mobile devices (e.g., mobile phones and PDAs) opens up a whole new world of possibilities, which includes delivering information to mobile devices that are customized and tailored according to their current location (Gutting et al., 2000; Tsalgatidou, Veijalainen, Markkula, Katasonov, & Hadjiefthymiades, 2003; Xu et al., 2003). Mobile queries are requests for certain information that are initiated by mobile users to the appropriate servers from their mobile devices. Query processing in a mobile environment may involve join processing from either single or several different servers with the mobile devices (Liberatore, 2002; Lo, Mamoulis, Cheung, Ho, & Kalnis, 2003). In addition, mobile queries can be performed regardless of where the users are located and the results obtained are influenced by the location of the user. Data that are downloaded from different locations would be different and there is a need to bring together these data according to a user who may want to synchronize the data that are downloaded from different location to be consolidated into a single output. Thus, the intention is to take into account location dependent factors, which allow mobile users to query data without facing location problems (Song, Kang, & Park, 2005; Tse, Lam, Ng, & Chan, 2005; Xu, Tang, & Lee, 2003). This concept is associated with location dependent query.

One of the main objectives of this article is to demonstrate the importance of allowing mobile users who believe that obtaining data from a single server is not enough and may need further processing with data that are obtained from other servers. Furthermore, the user may get data from several servers that are from the same or different providers. In other words, there are times when the user has the desire to gather data from several non-collaborative servers into their mobile devices (Lo, et al, 2003; Malladi & Davis, 2002). Mobile devices have made it capable for mobile users to process and retrieve data from multiple remote databases by sending queries to the servers and then process the multiple data gathered from these sources locally on the mobile devices (Mamoulis, Kalnis, Bakiras, & Li, 2003; Ozakar, Morvan, & Hameurlain, 2005). By processing the data locally, mobile users would have more control over what they actually want as the final result of the query. They can therefore choose to query data from different servers and process them locally according to their requirements. Also, by being able to obtain specific data over several different sites, it would help bring optimum results to mobile user queries. Furthermore, by driving away the computation on the client device, the bandwidth computation may also be reduced.

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Editorial Advisory Board
Table of Contents
Indranil Bose
Chapter 1
Varadharajan Sridhar
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Strategic Outsourcing: Opportunities and Challenges for Telecom Operators
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Sami J. Habib
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Empirical Prediction of Computer-Network Evolution
Chapter 3
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Suitability of IP Telephony in the Public Switched Telephone Network (PSTN): A Case Study
Chapter 4
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A Framework for High-Speed Networking
Chapter 5
Nurul I. Sarkar, Catherine Byrne, Nabeel A.Y. Al-Qirim
Ethernet network technology is still one of the most popular LAN technologies in use today by many organizations and educational institutions... Sample PDF
Updating on Gigabit Ethernet Implementation: The Case of a Large New Zealand Organization
Chapter 6
M. Chandrasekaran, R. S.D. Wahida Banu
This chapter introduces and analyses a class of non-linear congestion control algorithms called polynomial congestion control algorithms. These... Sample PDF
Interaction Between MIMD-Poly & PIPD-Poly Algorithms and other TCP Variants in Multiple Bottleneck TCP Networks
Chapter 7
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A Systematic Approach to the Analysis and Configuration of Audio/Video-on-Demand Services
Chapter 8
Say Ying Lim
As more and more servers appearing in the wireless environment provide accesses to mobile users, more and more demand and expectation is required by... Sample PDF
Mobile Information Processing Involving Multiple Non-Collaborative Sources
Chapter 9
Vilmos Simon
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Network Planning Algorithms for Optimizing Signalling Load in Mobile Networks
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Joon-Yeoul Oh, John P. Mullen
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A Heuristic Solution to the Large Scale Cellular Telecommunication Network Expansion Problem
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Wireless Proxy: Distributed System to Mitigate the Effects of User Mobility Over Streaming Services on IEEE 802.11 Wireless LANs
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R. Radhakrishnan, K. R. Shankarkumar, A. Ebenezer Jeyakumar
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Soft Decision Parallel Interference Cancellation for Multi-Carrier DS-CDMA
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Ghassan Kbar
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Distributed Resources Management in Wireless LANs that Support Fault Tolerance
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Mieso K. Denko
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Cooperative Data Caching and Prefetching in Wireless Ad Hoc Networks
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Essam Natsheh
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A Survey on Fuzzy Reasoning Applications for Routing Protocols in Wireless Ad-Hoc Networks
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Fuzzy Linguistic Knowledge for Active Queue Management in Wireless Ad-Hoc Networks
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