Zagazig University Digital Repository
Home
Thesis & Publications
All Contents
Publications
Thesis
Graduation Projects
Research Area
Research Area Reports
Search by Research Area
Universities Thesis
ACADEMIC Links
ACADEMIC RESEARCH
Zagazig University Authors
Africa Research Statistics
Google Scholar
Research Gate
Researcher ID
CrossRef
IEGA: An improved elitism-based genetic algorithm for task scheduling problem in fog computing
Faculty
Computer Science
Year:
2021
Type of Publication:
ZU Hosted
Pages:
4592-4631
Authors:
Mohammed Abdel Basset Metwally Attia
Staff Zu Site
Abstract In Staff Site
Journal:
International Journal of Intelligent Systems WILEY
Volume:
36
Keywords :
IEGA: , improved elitism-based genetic algorithm , task
Abstract:
Modern information technology, such as the internet of things (IoT) provides a real-time experience into how a system is performing and has been used in diversified areas spanning from machines, supply chain, and logistics to smart cities. IoT captures the changes in surrounding environments based on collections of distributed sensors and then sends the data to a fog computing (FC) layer for analysis and subsequent response. The speed of decision in such a process relies on there being minimal delay, which requires efficient distribution of tasks among the fog nodes. Since the utility of FC relies on the efficiency of this task scheduling task, improvements are always being sought in the speed of response. Here, we suggest an improved elitism genetic algorithm (IEGA) for overcoming the task scheduling problem for FC to enhance the quality of services to users of IoT devices. The improvements offered by IEGA stem from two main phases: first, the mutation rate and crossover rate are manipulated to help the algorithms in exploring most of the combinations that may form the near-optimal permutation; and a second phase mutates a number of solutions based on a certain probability to avoid becoming trapped in local minima and to find a better solution. IEGA is compared with five recent robust optimization algorithms in addition to EGA in terms of makespan, flow time, fitness function, carbon dioxide emission rate, and energy consumption. IEGA is shown to be superior to all other algorithms in all respects.
Author Related Publications
Mohammed Abdel Basset Metwally Attia, "Discrete greedy flower pollination algorithm for spherical traveling salesman problem", Springer, 2019
More
Mohammed Abdel Basset Metwally Attia, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", Natural Sciences Publishing Cor., 2014
More
Mohammed Abdel Basset Metwally Attia, "A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems", Springer London, 2021
More
Mohammed Abdel Basset Metwally Attia, "An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection", Pergamon, 2021
More
Mohammed Abdel Basset Metwally Attia, "An efficient teaching-learning-based optimization algorithm for parameters identification of photovoltaic models: Analysis and validations", Pergamon, 2021
More
Department Related Publications
Heba Zaki Mohamed Abdallah Elfiqi, "A computational linguistic approach for the identification of translator stylometry using Arabic-English text", IEEE, 2011
More
Heba Zaki Mohamed Abdallah Elfiqi, "Measuring Complexity of Mouse Brain Morphological Changes Using GeoEntropy", AIP Publishing, 2009
More
Mohammed Abdel Basset Metwally Attia, "Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm", Computational Intelligence and Neuroscience, 2016
More
Mohammed Abdel Basset Metwally Attia, "Solving systems of nonlinear equations via conjugate direction flower pollination algorithm", inderscience, 2017
More
Mustafa Khamis Baz Ramadan, "An Efficient method for choosing most suitable cloud storage provider reducing top security risks based on multi-criteria neutrosophic decision making", An Efficient method for choosing most suitable cloud storage provider reducing top security risks based on multi-criteria neutrosophic decision making, 2017
More
جامعة المنصورة
جامعة الاسكندرية
جامعة القاهرة
جامعة سوهاج
جامعة الفيوم
جامعة بنها
جامعة دمياط
جامعة بورسعيد
جامعة حلوان
جامعة السويس
شراقوة
جامعة المنيا
جامعة دمنهور
جامعة المنوفية
جامعة أسوان
جامعة جنوب الوادى
جامعة قناة السويس
جامعة عين شمس
جامعة أسيوط
جامعة كفر الشيخ
جامعة السادات
جامعة طنطا
جامعة بنى سويف