Clustering Algorithm with Asynchronous Programming
نویسندگان
چکیده
Clustering is very problematic on big data set in synchronous programming as well as time consuming. Finding optimal result from big misaligned data set is precarious because lack of seamless data pattern. This study emphasizes on reducing time fact and deployment of asynchronous program rather than synchronous model on big data. However, we provide an easy and flexible model named Unified Asynchronous Clustering Model (UACM) for clustering on multi dimensional, misaligned and big data set. The UACM replica segments big data set for parallel processing depending on segmentation of microprocessor. This model uses small unit of process (thread) as per the data set. The UACM architecture is also cost minimizing regarding hardware. This model evaluates the time fact between synchronous and asynchronous programming on large and misaligned data set. However, we implement the UACM model in real time platform without help of clustering tools.
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