چکیده مقاله
Task placement plays a vital role in enhancing the efficiency and performance of fog and edge computing systems This paper proposes an advanced approach to task placement in iFogSim using the Particle Swarm Optimization PSO algorithm, a robust metaheuristic inspired by the social behavior of swarms The PSO based framework dynamically optimizes the allocation of tasks to heterogeneous resources, aiming to minimize execution latency and maximize resource utilization By addressing the challenges of workload variability and resource constraints, the proposed method achieves superior performance compared to traditional scheduling techniques Experimental evaluations validate the effectiveness of the PSO algorithm, highlighting its potential for improving resource management in IoT enabled smart ecosystems
کلیدواژهها
نویسندگان
Mohammad Mahdi Ghaseminya
PhD Student in Computer Science, Department of Computer Science, Yazd University, Yazd, Iran, ۸۹۱۵۸۱۸۴۱۱
Seyed Abolfazl Shahzadeh Fazeli
Associate Professor in Computer Science, Department of Computer Science, Yazd University, Yazd, Iran, ۸۹۱۵۸۱۸۴۱۱
Najme Heydarnezhad
Master's degree in Computer Science, Department of Computer Science, Yazd University, Yazd, Iran, ۸۹۱۵۸۱۸۴۱۱
شیوه ارجاع
Ghaseminya, Mohammad Mahdi and Shahzadeh Fazeli, Seyed Abolfazl and Heydarnezhad, Najme,1403,Enhancing Task Placement in iFogSim Using Metaheuristic Algorithms: An Innovative Approach,3nd International Conference and 8th National Conference on Computers, information technology and applications of artificial intelligence,Ahvaz
ارائهشده در
مجموعه مقالات سومین کنفرانس بین المللی و هشتمین کنفرانس ملی کامپیوتر، فناوری اطلاعات و کاربردهای هوش مصنوعی30 بهمن 1403 · اهواز