Performance analysis of an adaptive query processing strategy for mobile computing

Author(s):  
H. Shibata ◽  
M. Tsukamoto ◽  
S. Nishio
2005 ◽  
Vol 1 (4) ◽  
pp. 225-252 ◽  
Author(s):  
Agustinus Borgy Waluyo ◽  
Bala Srinivasan ◽  
David Taniar

The emergence of mobile computing provides the ability to access information at any time and place. However, as mobile computing environments have inherent factors like power, storage, asymmetric communication cost, and bandwidth limitations, efficient query processing and minimum query response time are definitely of great interest. This survey groups a variety of query optimization and processing mechanisms in mobile databases into two main categories, namely: (i) query processing strategy, and (ii) caching management strategy. Query processing includes both pull and push operations (broadcast mechanisms). We further classify push operation into on-demand broadcast and periodic broadcast. Push operation (on-demand broadcast) relates to designing techniques that enable the server to accommodate multiple requests so that the request can be processed efficiently. Push operation (periodic broadcast) corresponds to data dissemination strategies. In this scheme, several techniques to improve the query performance by broadcasting data to a population of mobile users are described. A caching management strategy defines a number of methods for maintaining cached data items in clients' local storage. This strategy considers critical caching issues such as caching granularity, caching coherence strategy and caching replacement policy. Finally, this survey concludes with several open issues relating to mobile query optimization and processing strategy.


2012 ◽  
Vol 532-533 ◽  
pp. 897-901
Author(s):  
Ming Jun Wei ◽  
Li Chun Xia ◽  
Jian Guo Jin ◽  
Qiu Hong Fan

This paper firstly analyzes the importance and necessity of location dependent query in the mobile computing. Then, it proposes a special case in the application of the location dependent query. That is as follows: Inquirers may send the same location dependent query in different but similar positions. However, the server will not deal with them together but treat them separately. Thus, it will not only cause the waste of system resources but also delay disposal of other queries. According to the principal of clustering we propose a new location Analysis Algorithms-similar merging location analysis algorithm (SMLA). By the algorithm, similar queries can be combined into the same query, so as to reduce the load on central servers, improve system efficiency and query processing performance.


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