An efficient divide-and-conquer approach for big data analytics in machine-to-machine communication

Neurocomputing

Volumn 174, Issue , 2016, Pages 439-453

  Ahmad, Awais ^a   Paul, Anand ^a   Rathore, M Mazhar ^a  

^a Kyungpook National University   (South Korea)

Author keywords

Big Data; Data fusion domain; Divide and conquer; M2M

Indexed keywords

COMMUNICATION SATELLITES; COMPUTATIONAL EFFICIENCY; COMPUTER ARCHITECTURE; DATA FUSION; DATA HANDLING; DATA MINING; EFFICIENCY; EXTRACTION; FEATURE EXTRACTION; MEMORY ARCHITECTURE;

DATA FUSION DOMAIN; DIVIDE AND CONQUER; DIVIDE-AND-CONQUER APPROACH; LIVING ENVIRONMENT; M2M; MACHINE-TO-MACHINE COMMUNICATIONS; SEQUENTIAL MANNERS; SYSTEM ARCHITECTURES;

BIG DATA;

ALGORITHM; ARTICLE; CLASSIFICATION; COMPUTER MEMORY; COMPUTER NETWORK; COMPUTER SYSTEM; DATA ANALYSIS; DATA BASE; DATA PROCESSING; DECISION SUPPORT SYSTEM; FEASIBILITY STUDY; INFORMATION PROCESSING; INFORMATION STORAGE; INFORMATION SYSTEM; MACHINE TO MACHINE COMMUNICATION; PHYSICAL PARAMETERS; PRIORITY JOURNAL;

EID: 84945582178     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2015.04.109     Document Type: Article

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