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  1. 1
    Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model

    Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model by Jasim, Ahmed Abdulhadi, Idris, Mohd Yamani Idna, Azzuhri, Saaidal Razalli, Issa, Noor Riyadh, Noor, Noorzaily Mohamed, Kakarla, Jagadeesh, Amiri, Iraj Sadegh

    Published 2019
    “…Wireless sensor networks (WSNs) consist of a large number of sensor nodes that are distributed to capture the information about an area of interest. …”
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  2. 2
    Multi-objective optimization for integrated task scheduling and load balancing in fog computing for IoT applications

    Multi-objective optimization for integrated task scheduling and load balancing in fog computing for IoT applications by Rafique, Majid

    Published 2025
    “…By using a task scheduling and offloading method, the FOCS algorithm arranges data according to size and sends it to the appropriate fog nodes. …”
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  3. 3
    Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti

    Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

    Published 2022
    “…The most significant classifier algorithms to distinguish a pothole defect is Maximum likelihood with 29 over 40 band combination win rate. …”
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  4. 4
    Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution

    Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution by Nokhanji, Nooshin

    Published 2014
    “…The main and definitive target of routing protocols in Wireless Sensor Networks (WSN) is passing data from the sensor nodes to the sink in most energy efficient manner besides considering the accuracy of data. …”
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  5. 5
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Saleh Ahmed,, Ali Mohammed, Ali Majeed Alhammadi, Nafea, Ahmad Khalaf, Bashar, A. Mostafa, Salama

    Published 2023
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  6. 6
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Ahmed, Ali Mohammed Saleh, Majeed Alhammadi, Nafea Ali, Ahmad Khalaf, Bashar, A. Mostafa, Salama

    Published 2023
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  7. 7
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Saleh Ahmed, Ali Mohammed, Ali Majeed Alhammadi, Nafea, Ahmad Khalaf, Bashar, A. Mostafa, Salama

    Published 2023
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  8. 8
    A scheduled activity energy aware distributed clustering algorithm for wireless sensor networks with nonuniform node distribution

    A scheduled activity energy aware distributed clustering algorithm for wireless sensor networks with nonuniform node distribution by Nokhanji, Nooshin, Mohd Hanapi, Zurina, Subramaniam, Shamala, Mohamed, Mohamad Afendee

    Published 2014
    “…However, due to the nonuniform node distribution, there is a redundancy in sensed and transmitted data in dense area. …”
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  9. 9
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Firas Mohammed Aswad, Firas Mohammed Aswad, Ali Mohammed Saleh Ahmed, Ali Mohammed Saleh Ahmed, Nafea Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

    Published 2023
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  10. 10
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Ahmed, Ali Mohammed Saleh, Ali Majeed Alhammadi, Nafea, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

    Published 2023
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  11. 11
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Firas Mohammed Aswad, Firas Mohammed Aswad, Ali Mohammed Saleh Ahmed, Ali Mohammed Saleh Ahmed, Nafea Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

    Published 2023
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  12. 12
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Firas Mohammed Aswad, Firas Mohammed Aswad, Ali Mohammed Saleh Ahmed, Ali Mohammed Saleh Ahmed, Nafea Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

    Published 2022
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  13. 13
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Mohammed Saleh Ahmed, Ali, Ali Majeed Alhammadi,, Nafea, Ahmad Khalaf, Bashar, Mostafa, Salama A.

    Published 2023
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  14. 14
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Ahmed, Ali Mohammed Saleh, Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Khalaf, Bashar Ahmad, Mostafa, Salama A.

    Published 2023
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  15. 15
    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks

    Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Firas Mohammed Aswad, Firas Mohammed Aswad, Ali Mohammed Saleh Ahmed, Ali Mohammed Saleh Ahmed, Nafea Ali Majeed Alhammadi, Nafea Ali Majeed Alhammadi, Bashar Ahmad Khalaf, Bashar Ahmad Khalaf, Salama A. Mostafa, Salama A. Mostafa

    Published 2023
    “…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. …”
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  16. 16
    Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper

    Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper by Qadori, Huthiafa Q., Ahmad Zukarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

    Published 2017
    “…Recently, wireless sensor networks have employed the concept of mobile agent to reduce energy consumption and obtain effective data gathering. …”
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  17. 17
    Efficient k-coverage scheduling algorithms for wireless sensor networks / Ahmed Abdullah Saleh Al-Shalabi

    Efficient k-coverage scheduling algorithms for wireless sensor networks / Ahmed Abdullah Saleh Al-Shalabi by Saleh Al-Shalabi, Abdullah

    Published 2014
    “…An efficient k-coverage algorithm for sensors with fixed sensing range (Maximum Layers Scheduling algorithm - MLS) is demonstrated. …”
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  18. 18
    A spawn mobile agent itinerary planning approach for energy-efficient data gathering in wireless sensor networks

    A spawn mobile agent itinerary planning approach for energy-efficient data gathering in wireless sensor networks by Q. Qadori, Huthiafa, Ahmad Zulkarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

    Published 2017
    “…Moreover, each distributed MA has to carry the processing code (data aggregation code) to collect the sensory data and return back to the sink with the accumulated data. …”
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  19. 19
    An Improved Distributed Scheduling Algorithm for Wireless Sensor Networks

    An Improved Distributed Scheduling Algorithm for Wireless Sensor Networks by Sheikh, Muhammad Aman, Drieberg , Micheal, Zain Ali, Noohul Basheer

    Published 2012
    “…Simulation results show that the IDSA significantly outperforms a representative distributed random slot assignment algorithm (DRAND).…”
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  20. 20
    Machine learning in botda fibre sensor for distributed temperature measurement

    Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

    Published 2023
    “…To make the sensor more reliable, temperature data must be collected over the length of the cable, or distributed data rather than point data. …”
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