REVIEW ON ARTIFICIAL BEE COLONY ALGORITHM ON BIG DATA TO FIND OUT REQUIRED DATA SOURCES

Big data is a large amount of data which is hard to handle by on hand systems. It requires new structures, algorithms and techniques. As data increases as per volume, dark data also will increase. Artificial Bee Colony algorithm is a part of Swarm Intelligence. It is based on how honey bees are working to find out their food sources. In Big Data there is distributed environment so required sources may be on different places. During process the data these data sources have to find out from different places and analyze a one system. This requires calculation which can help us to find out best option for our required data sources. ABC algorithm is used to overcome limitations of ant colony algorithm. In ant colony initialization will be repeat from starting point in case of failure. In bee colony optimization initialization happens only once. It is used to find out required data source based on parameters out of multiple data sources. Thus, artificial bee colony algorithm can be used to find out best data sources. We can store these derived data sources on cloud for further processing. Bee colony algorithm generally used in data mining and networking field. It can be used for Big Data for identifying data resources.