An asynchronous consistency algorithm in smart manufacturing cloud data centers

Abstract

In the smart manufacturing factory, the fresh real-time datas and multiple replications are important for numerically-controlled machine tools. The production datas are stored in distributed cloud data centers (CDCs), so the communication latencies produced by data synchronization may impair the machining performance. In this paper, an asynchronous consistency algorithm (ACA) which is inspired by the nearest infection is proposed to reduce the communication latencies between nodes. The experimental results demonstrate that the proposed algorithm can support lower client-side latencies and increase data stability, thereby improving the production efficiency.

A High Utility Itemset Mining Algorithm Based on Particle Filter

“…Data analysis [1] has recently gained prominence as a feld of study in data mining, which has applications in the aviation industry [2], medicine [3], manufacturing [4], and many other felds [5][6][7][8]. An essential component of data analysis is frequent itemset mining (FIM) [9], which identifes frequent itemsets (FIs) to provide stakeholders with a basis for decision-making.…”