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Borhanuddin Mohd Ali
Researcher at Universiti Putra Malaysia
Publications - 283
Citations - 1560
Borhanuddin Mohd Ali is an academic researcher from Universiti Putra Malaysia. The author has contributed to research in topics: Handover & Quality of service. The author has an hindex of 17, co-authored 280 publications receiving 1433 citations. Previous affiliations of Borhanuddin Mohd Ali include MIMOS.
Papers
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Review: Mobility management for IP-based next generation mobile networks: Review, challenge and perspective
TL;DR: In this paper, the authors present IPv6 features to support mobile systems and survey the mobility management services along with their techniques, strategies and protocol categories, and elaborate upon the classification and comparison among various mobility management protocols.
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A novel cell-selection optimization handover for long-term evolution (LTE) macrocellusing fuzzy TOPSIS
Yaseein Soubhi Hussein,Borhanuddin Mohd Ali,Mohd Fadlee A. Rasid,Aduwati Sali,Ali Mohammed Mansoor +4 more
TL;DR: A novel method called fuzzy multiple-criteria cell selection (FMCCS), which uses an integrated fuzzy technique for order preference by using similarity to ideal solution on S-criterion, availability of resource blocks (RBs), and uplink signal-to-interference-plus-noise ratio, is proposed in this paper.
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Comparative study of high-speed Linux TCP variants over high-BDP networks
TL;DR: The results reveal that, CUBIC and YeAH overcome the other high-speed TCP variants in different cases of buffer size, however, they still require more improvement to extend their ability to fully utilize the high- speed bandwidths, especially when the applied buffer is close to or less than the BDP of the link.
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An Adaptive Delayed Acknowledgment Strategy to Improve TCP Performance in Multi-hop Wireless Networks
TL;DR: This work proposes a new TCP receiver with an adaptive delayed ACK strategy to improve TCP performance in multi-hop wireless networks and demonstrates that the strategy can improve UDP performance significantly.
Journal ArticleDOI
An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks
I. Mustapha,I. Mustapha,Borhanuddin Mohd Ali,Mohd Fadlee A. Rasid,Aduwati Sali,Hafizal Mohamad +5 more
TL;DR: Performance comparisons of the proposed reinforcement learning-based spectrum-aware clustering algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error, complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach.