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All Journal Mikailalsys Journal of Advanced Engineering International International Journal of Education, Management, and Technology
Atinuke, Aregbesola Taobat
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mechanical Engineering

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Computing Performance Optimization Through Parallelization: Techniques and Evaluation Akintayo, Taiwo Abdulahi; Olobo, Neibo Augustine; Atinuke, Aregbesola Taobat; AbdulKareem, Idayat Olaide
International Journal of Education, Management, and Technology Vol 2 No 3 (2024): International Journal of Education, Management, and Technology
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ijemt.v2i3.4210

Abstract

Parallelization has become a cornerstone technique for optimizing computing performance, especially in addressing the growing complexity and scale of modern computational tasks. By leveraging concurrent processing capabilities of multi-core processors, GPUs, and distributed systems, parallel computing enables the efficient execution of large-scale problems that would otherwise be computationally prohibitive. This paper explores various parallelization techniques, including data parallelism, task parallelism, pipeline parallelism, and the use of GPUs for massive parallel computations. We also examine the key performance evaluation metrics such as speedup, efficiency, Amdahl’s Law, scalability, and load balancing that are critical in assessing the effectiveness of parallelization strategies. Through case studies in scientific simulations, machine learning, and big data analytics, we demonstrate how these techniques can be applied to real-world problems, offering significant improvements in execution time and resource utilization. The paper concludes by discussing the trade-offs involved in parallel computing and suggesting future avenues for optimizing parallelization methods in the context of evolving hardware and software technologies.
Assessing the Cybersecurity Risks Associated with the Internet of Things (IoT) Devices Akintayo, Taiwo Abdulahi; Asolo, Emmanuel; Nnamani, Chinenye Cordelia; Felix, Omojola Ayogoke; Osaro, Chukwuemeka Chukwuma; Atinuke, Aregbesola Taobat
Mikailalsys Journal of Advanced Engineering International Vol 1 No 3 (2024): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v1i3.3862

Abstract

The rapid rise of the Internet of Things (IoT) in our daily lives has brought significant cybersecurity concerns to the forefront, emphasizing the need for both active and proactive measures. This research provides a comprehensive review of the literature on the cybersecurity challenges and threats faced by various IoT devices. It outlines proposed solutions and structural frameworks while also exploring different methods for detecting and identifying potential threats. Additionally, it highlights research gaps within the industrial and economic sectors of IoT applications. Our findings reveal that the main issues affecting IoT systems include cybercrime and privacy violations. While Artificial Intelligence holds great promise for enhancing cybersecurity, many attacks, particularly those focused on authentication and confidentiality, are still inadequately addressed by existing solutions. This indicates a pressing need for further research and practical testing of the recommended defenses.
Co-Authors AbdulKareem, Idayat Olaide Akintayo, Taiwo Abdulahi Asolo, Emmanuel Felix, Omojola Ayogoke Nnamani, Chinenye Cordelia Olobo, Neibo Augustine Osaro, Chukwuemeka Chukwuma