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By Jeet Kumar, Ashish Awasthi (auth.), Srija Unnikrishnan, Sunil Surve, Deepak Bhoir (eds.)
This e-book constitutes the refereed lawsuits of the overseas convention on Advances in Computing Communications and keep watch over, ICAC3 2011, held in Mumbai, India, in January 2011. The eighty four revised complete papers awarded have been rigorously reviewed and chosen from 309 submissions. The papers deal with concerns reminiscent of AI, man made neural networks, special effects, information warehousing and mining, allotted computing, geo info and statistical computing, studying algorithms, method protection, digital fact, cloud computing, provider orientated structure, semantic net, coding options, modeling and simulation of conversation structures, community structure, community protocols, optical fiber/microwave verbal exchange, satellite tv for pc conversation, speech/image processing, stressed and instant communique, cooperative keep an eye on, and nonlinear keep an eye on, procedure keep watch over and instrumentation, commercial automation, controls in aerospace, robotics, and tool systems.
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Extra resources for Advances in Computing, Communication and Control: International Conference, ICAC3 2011, Mumbai, India, January 28-29, 2011. Proceedings
The reason behind the particular manner of realization is that at the beginning of every reasoning cycle, agent checks for the messages they might have received from other agents. Any message received by them goes in a mailbox and is checked using the default checkmail method, which has the following structure:
This problem is addressed by the algorithm proposed in this paper, which considers both the size and the query frequency of each view to select the top-k views. The views so selected are profitable with respect to size and are capable of answering large number of queries. Further, experiments show that the views selected using the proposed algorithm, in comparison to those selected using HRUA, are able to answer comparatively greater number of queries at the cost of a slight drop in the total cost of evaluating all the views.
The algorithm computes the profit of each view, which is defined as a function of the size and query frequency, and then selects from amongst them the most profitable view for materialization. Unlike HRUA, the proposed algorithm is able to select views that are not only profitable with respect to size but are also able to account for large number of queries. The selected views thereby would reduce the average query response time. Further experiment based comparison between the proposed algorithm and HRUA on parameters TQA and TVEC showed that the proposed algorithm, in comparison to HRUA, was found to achieve significant improvement in TQA at the cost of a slight drop in the TVEC in respect of views selected for materialization.