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All Journal International Journal of Electrical and Computer Engineering
Ferdous Hossain
Multimedia University
Computer Science & IT Electrical & Electronics Engineering

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A Survey of Machine Learning Techniques for Self-tuning Hadoop Performance Md. Armanur Rahman; J. Hossen; Venkataseshaiah C; CK Ho; Tan Kim Geok; Aziza Sultana; Jesmeen M. Z. H.; Ferdous Hossain
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (475.262 KB) | DOI: 10.11591/ijece.v8i3.pp1854-1862

Abstract

The Apache Hadoop framework is an open source implementation of MapReduce for processing and storing big data. However, to get the best performance from this is a big challenge because of its large number configuration parameters. In this paper, the concept of critical issues of Hadoop system, big data and machine learning have been highlighted and an analysis of some machine learning techniques applied so far, for improving the Hadoop performance is presented. Then, a promising machine learning technique using deep learning algorithm is proposed for Hadoop system performance improvement.
Adaptive 3D ray tracing approach for indoor radio signal prediction at 3.5 GHz Mohd Nazeri Kamaruddin; Tan Kim Geok; Omar Abdul Aziz; Tharek Abd Rahman; Ferdous Hossain; Azlan Abdul Aziz
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1617-1625

Abstract

This paper explained an adaptive ray tracing technique in modelling indoor radio wave propagation. As compared with conventional ray tracing approach, the presented ray tracing approach offers an optimized method to trace the travelling radio signal by introducing flexibility and adaptive features in ray launching algorithm in modelling the radio wave for indoor scenarios. The simulation result was compared with measurements data for verification. By analyzing the results, the proposed adaptive technique showed a better improvement in simulation time, power level and coverage in modelling the radio wave propagation for indoor scenario and may benefit in the development of signal propagation simulators for future technologies.
Challenges and prospects in the 6G-enabled Internet of Things ecosystem Mina Asaduzaman; Ferdous Hossain; Tan Kim Geok
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i4.pp1927-1943

Abstract

The exponential growth of the Internet of Things (IoT) applications is revealing critical limitations in current fifth generation networks (5G), especially with respect to scalability, latency, energy efficiency and intelligent resource management. These concerns make sixth-generation (6G) communication systems a near-future solution to facilitate intelligent, autonomous, and sustainable IoT ecosystems by amalgamating artificial intelligence (AI), terahertz (THz) communication, edge intelligence, semantic communication, and ultra-reliable low-latency communication (URLLC). But the research environment regarding 6G enabled IoT is still fragmented with the non-existence of a common analytical framework. In this paper, we present a structured survey and taxonomy based analytical framework for the 6G enabled IoT ecosystem. It classifies the recent works into enabling technologies, intelligent architectures, emerging applications, deployment challenges and future research directions. The requisite advancements in technologies needed for future IoT infrastructures are also highlighted through a comparison of 5G and 6G capabilities. The results of the analysis indicate that 6G can contribute to a substantial improvement of IoT performance in smart cities, healthcare, industrial automation and control applications (manufacturing science), autonomous transportation and precision agriculture. However, issues concerning cybersecurity, interoperability, sustainability, spectrum management and infrastructure cost still remain. This study is expected to enable the development of secure, scalable, intelligent and sustainable next-generation IoT systems based on collaborative edge computing.
Co-Authors Aziza Sultana Azlan Abdul Aziz CK Ho J. Hossen Jesmeen M. Z. H. Md. Armanur Rahman Mina Asaduzaman Mohd Nazeri Kamaruddin Omar Abdul Aziz Tan Kim Geok Tharek Abd Rahman Venkataseshaiah C