Analysis of Particle Swarm Optimization and Genetic Algorithm based on Task Scheduling in Cloud Computing Environment
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 1
Abstract
Since the beginning of cloud computing technology, task scheduling problem has never been an easy work. Because of its NP-complete problem nature, a large number of task scheduling techniques have been suggested by different researchers to solve this complicated optimization problem. It is found worth to employ heuristics methods to get optimal or to arrive at near-optimal solutions. In this work, a combination of two heuristics algorithms was proposed: particle swarm optimization (PSO) and genetic algorithm (GA). Firstly, we list pros and cons of each algorithm and express its best interest to maximize the resource utilization. Secondly, we conduct a performance comparison approach based on two most critical objective functions of task scheduling problems which are execution time and computation cost of tasks in cloud computing. Thirdly, we compare our results with other existing heuristics algorithms from the literatures. The experimental results was examined with benchmark functions and results showed that the particle swarm optimization (PSO) performs better than genetic algorithm (GA) but they both present a similarity because of their population based search methods. The results also showed that the proposed hybrid models outperform the standard PSO and reduces dramatically the execution time and lower the processing cost on the computing resources.
Authors and Affiliations
Frederic Nzanywayingoma, Yang Yang
Keywords
Related Articles
- EP ID EP243015
- DOI 10.14569/IJACSA.2017.080104
- Views 109
- Downloads 0
Exploring Identifiers of Research Articles Related to Food and Disease using Artificial Intelligence
Currently hundreds of studies in the literature have shown the link between food and reducing the risk of chronic diseases. This study investigates the use of natural language processing and artificial intelligence techn...
A Survey on Opportunistic Routing
Opportunistic Routing (OR) is attracted much in the research field of multi-hop wireless networks because it is different from traditional routing protocols [such as: Distance Vector (DV) and Link State (LS)], that it ne...
Design and Implementation for Multi-Level Cell Flash Memory Storage Systems
The flash memory management functions of write coalescing, space management, logical-to-physical mapping, wear leveling, and garbage collection require significant on-going computation and data movement. MLC flash memory...
Inferring of Cognitive Skill Zones in Concept Space of Knowledge Assessment
In these research zones of the knowledge, the assessed domain is identified. Explicitly, these zones are known as Verified Skills, Derived Skills and Potential Skills. In detail, the Verified Skills Zone is the set of te...
A Comprehensive Comparative Analysis of Two Novel Underwater Routing Protocols
The most unmanned area of this planet is sheltered with water; that is roughly 71.9% of the total area of this planet. A large quantity of marine life is present in this area. That is the reason underwater research is bo...