• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.8
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• pp.825-834
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• 2018

Broadcasting is a basic data communication method for interconnection networks. There are two types of broadcasting. One-to-all broadcasting is to transmit a message from one node to all other nodes and all-to-all broadcasting is to transmit a message from all the nodes that have messages to other nodes. And by the using way of the transmission port per unit time, there are two schemes of broadcasting. Single port telecommunication(SLA) is to transmit messages from one node that contains the messages to one adjacent node only and all port telecommunication(MLA) is to transmit messages from one node to all adjacent nodes within a time of unit. Matrix hypercube is that an interconnection network has improved network cost than that of hypercube with the same number of nodes. In this paper, we analyze broadcasting scheme of matirx hypercube. First, we propose one-to-all and all-to-all broadcasting algorithms of matrix hypercube. And we prove that one-to-all broadcasting times are 2n+1 and $2{\lceil}{\frac{n}{2}}{\rceil}+1$ based on the SLA and MLA models, respectively. Also, we show all-to-all broadcasting time using SLA model is $5{\times}2^{\frac{n}{2}}-2$ when n=even, and is $5{\times}2^{\frac{n-1}{2}}+2$ when n=odd.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.153-173
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• 2013

The ontology has been gaining increasing interests by recent arise of the semantic web and related technologies. The focus is mostly on inference query processing that requires high-level techniques for storage and searching ontologies efficiently, and it has been actively studied in the area of semantic-based searching. W3C's recommendation is to use RDFS and OWL for representing ontologies. However memory-based editors, inference engines, and triple storages all store ontology as a simple set of triplets. Naturally the performance is limited, especially when a large-scale ontology needs to be processed. A variety of researches on proposing algorithms for efficient inference query processing has been conducted, and many of them are based on using proven relational database technology. However, none of them had been successful in obtaining the complete set of inference results which reflects the five characteristics of the ontology properties. In this paper, we propose a new index structure called hyper cube index to efficiently process inference queries. Our approach is based on an intuition that an index can speed up the query processing when extensive inferencing is required.