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Articles by M. Marikkannan
Total Records ( 2 ) for M. Marikkannan
  D. Prabakar , M. Marikkannan and S. Karthik
  The wireless sensor networks due to its invincible property finds its application in several areas. For all these applications, the energy utilization is the factor which determines the performance of the sensor networks. Routing of information and transmitting the same to the base station plays a vital role because the nodes are battery operated and the energy resources are scarce. The study proposes a novel protocol called Position Based Gossiping (PBG) for providing a solution for addressing the problems in gossiping technique. The proposed technique enhances the energy within the network and improves the lifetime of the network as compared to the conventional routing protocols. Moreover, the energy between the nodes are equalized which considerably enhances the lifetime of the network. As added the protocol minimizes the delay in transmission and loss of data packets.
  S. Raja Ranganathan , M. Marikkannan and S. Karthik
  In semantic web, the information flow obtained from different relations is certain and processing those data across the relations are not easy without proper understanding about the semantic mapping between them. It is a complex process to manually identify these mappings and it is not possible over the web. It is required to develop tools for supporting relation mapping for the success of the semantic web. A technique named sealant is designed for machine based learning for identifying the mappings. For two given catalogs, the percept in one relation is identified by sealant and it predicts the most common percepts in other catalogs. A probability based explanations for many resemblance measures are viewed using sealant which works well with all of them. Furthermore, the sealant employs different learning techniques each of which utilizes several information types either in the data occurrence or in the catalog framework of the relations. The matching precision can be enhanced by expanding the sealant for integrating sound understanding and domain restrictions into the matching process. The technique varies with its working ways using clearly explained resemblance perception and effective integration of several types of understanding. The sealant is expanded for identifying difficult mappings between the relations and explains the analysis for its effective utilization.
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