期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：14
页码：3281
出版社：Journal of Theoretical and Applied
摘要：Load Equilibration is the central attribute in the data stream classification. A huge amount of data is generated from the streams of data in real time applications such as set of transaction process, Intrusion Detection System and so on. A plethora of load equilibration techniques are available but not precised for global optima solutions. The paper re-searched on equilibrating the loads among the nodes. We proposed “Hybridized FA-CO” algorithm that highlights the features of best prediction of nodes for equilibrating the loads. The operators of a firefly are merged with phenomenon of ant system to heighten the generation of global optima solutions. The resources are assigned properly to its corresponding nodes. In data stream, the data is continuous. In data mining networks, the mining of nodes is of great importance. The paper deals with the prediction of nodes to keep up the loads. The continuous attributes like foretell value, foretell time and Rate of mining are used to keep up the loads. Rate of mining is the mining of nodes with least carrying loads. The experimentations are conducted on data mining networks and the performance validation is done. The result proves that the hybridized approach works efficiently for equilibrating the loads.
关键词：Load Equilibration; Firefly Operators; Ant system; Rate of mining; Foretell Value and Foretell time
