Comprehensive analysis of big data variety landscape

被引:39
作者
Abawajy, Jemal [1 ]
机构
[1] Deakin Univ, Sch Informat Technol, Parallel & Distributed Comp Lab, Melbourne, Vic, Australia
关键词
big data; taxonomy; analysis; network;
D O I
10.1080/17445760.2014.925548
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Big data presents a remarkable opportunity for organisations to obtain critical intelligence to drive decisions and obtain insights as never before. However, big data generates high network traffic. Moreover, the continuous growth in the variety of network traffic due to big data variety has rendered the network to be one of the key big data challenges. In this article, we present a comprehensive analysis of big data variety and its adverse effects on the network performance. We present taxonomy of big data variety and discuss various dimensions of the big data variety features. We also discuss how the features influence the interconnection network requirements. Finally, we discuss some of the challenges each big data variety dimension presents and possible approach to address them.
引用
收藏
页码:5 / 14
页数:10
相关论文
共 22 条
  • [1] Alvaro A, 2013, BIG DATA ANAL SECURI
  • [2] [Anonymous], 2013, GAME CHANGERS 5 OPPO
  • [3] [Anonymous], P 21 ACM S OP SYST P
  • [4] Chang F, 2006, P OP SYST DES IMPL O
  • [5] Managing Data Transfers in Computer Clusters with Orchestra
    Chowdhury, Mosharaf
    Zaharia, Matei
    Ma, Justin
    Jordan, Michael I.
    Stoica, Ion
    [J]. ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2011, 41 (04) : 98 - 109
  • [6] Chowdhury M, 2012, PROCEEDINGS OF THE 11TH ACM WORKSHOP ON HOT TOPICS IN NETWORKS (HOTNETS-XI), P31
  • [7] Processing Flows of Information: From Data Stream to Complex Event Processing
    Cugola, Gianpaolo
    Margara, Alessandro
    [J]. ACM COMPUTING SURVEYS, 2012, 44 (03)
  • [8] Dean J, 2004, P OP SYST DES IMPL O
  • [9] Devlin B., 2012, BIG DATA ZOO TAMING
  • [10] Dirolf M., 2010, MONGODB DEFINITIVE G