Big data Related Technologies, Challenges and Future by Min Chen

By Min Chen

This Springer short presents a entire review of the history and up to date advancements of massive information. the price chain of massive facts is split into 4 levels: facts iteration, information acquisition, facts garage and knowledge research. for every section, the e-book introduces the overall historical past, discusses technical demanding situations and stories the newest advances. applied sciences below dialogue contain cloud computing, web of items, info facilities, Hadoop and extra. The authors additionally discover numerous consultant functions of huge info reminiscent of firm administration, on-line social networks, healthcare and scientific purposes, collective intelligence and shrewdpermanent grids. This publication concludes with a considerate dialogue of attainable learn instructions and improvement tendencies within the box. substantial facts: comparable applied sciences, demanding situations and destiny clients is a concise but thorough exam of this fascinating zone. it really is designed for researchers and pros attracted to tremendous information or similar study. Advanced-level scholars in machine technological know-how and electric engineering also will locate this publication valuable.

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Topics
Computational Intelligence
Data Mining and information Discovery
Control
Artificial Intelligence (incl. Robotics)

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Energy-efficient design of a scalable optical multiplane interconnection architecture. Selected Topics in Quantum Electronics, IEEE Journal of, 17(2):377–383, 2011. 36. Avinash Karanth Kodi and Ahmed Louri. Energy-efficient and bandwidth-reconfigurable photonic networks for high-performance computing (hpc) systems. Selected Topics in Quantum Electronics, IEEE Journal of, 17(2):384–395, 2011. 37. Xia Zhou, Zengbin Zhang, Yibo Zhu, Yubo Li, Saipriya Kumar, Amin Vahdat, Ben Y Zhao, and Haitao Zheng.

In addition, some analytical methods have stringent requirements on data quality. Therefore, data should be pre-processed under many circumstances to integrate the data from different sources, so as to enable effective data analysis. Pre-processing data not only reduces storage expense, but also improves analysis accuracy. Some relational data pre-processing techniques are discussed in the following. 1 Integration Data integration is the cornerstone of modern commercial informatics, which involves the combination of data from different sources and provides users with a uniform view of data [38].

In ACM SIGCOMM Computer Communication Review, volume 39, pages 51–62. ACM, 2009. 28. Chuanxiong Guo, Guohan Lu, Dan Li, Haitao Wu, Xuan Zhang, Yunfeng Shi, Chen Tian, Yongguang Zhang, and Songwu Lu. Bcube: a high performance, server-centric network architecture for modular data centers. ACM SIGCOMM Computer Communication Review, 39(4):63–74, 2009. 29. Nathan Farrington, George Porter, Sivasankar Radhakrishnan, Hamid Hajabdolali Bazzaz, Vikram Subramanya, Yeshaiahu Fainman, George Papen, and Amin Vahdat.

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