Features Selection Model for Internet of E-Health Things Using Big Data

Sadia Din, Anand Paul, Nadra Guizani, Syed Hassan Ahmed, Murad Khan, M. Mazhar Rathore

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

Internet of Things (IoT) plays a key role in connecting the e-health system with the cyber world through new services and seamless interconnection between heterogeneous devices. Therefore, it becomes computationally inefficient to analyze and select features from such massive volume of data. Therefore, keeping in view the needs above, this paper presents a system architecture that selects features by using Artificial Bee Colony (ABC). Moreover, a Kalman filter is used in Hadoop ecosystem that is used for removal of noise. Furthermore, traditional MapReduce with ABC is used that enhance the processing efficiency. Moreover, a complete four-tier architecture is also proposed that efficiently aggregate the data, eliminate unnecessary data, and analyze the data by the proposed Hadoop-based ABC algorithm. To check the efficiency of the proposed algorithms exploited in the proposed system architecture, we have implemented our proposed system using Hadoop and MapReduce with the ABC algorithm. ABC algorithm is used to select features, whereas, MapReduce is supported by a parallel algorithm that efficiently processes a huge volume of data sets. The system is implemented using MapReduce tool at the top of the Hadoop parallel nodes with near real-time. Moreover, the proposed system is compared with Swarm approaches and is evaluated regarding efficiency, accuracy, and throughput by using ten different data sets. The results show that the proposed system is more scalable and efficient in selecting features.

Original languageEnglish
Article number8254418
Pages (from-to)1-7
Number of pages7
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
Volume2018-January
DOIs
StatePublished - 2017
Event2017 IEEE Global Communications Conference, GLOBECOM 2017 - Singapore, Singapore
Duration: 4 Dec 20178 Dec 2017

Keywords

  • ABC algorithm
  • Big Data
  • IoT
  • feature selection

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