A Multi-objective Optimization Scheduling Algorithm in Cloud Computing

  • Madhu Bala MyneniEmail author
  • Siva Abhishek Sirivella
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 127)


Task scheduling plays a major role in cloud computing that creates a direct impact on performance issues and reduces the system load. In this paper, a novel task scheduling algorithm has proposed for the optimization of multi-objective problem in the cloud environment. It addresses a model to define the demand of resources by a job. It gives a relationship between the resources and costs within a project. The scheduling of multi-objective problem is optimized with the use of ant colony optimization algorithm. The evaluation of the cost and performance of the task has two major constraints considered as makespan and budget’s cost. The two considered constraints will make the algorithm to achieve the optimal result within time and enhance the quality of performance of the system considered. This method is very powerful than other methods with single objectives considered such as makespan, utilization of resources, violation of deadline rate and cost.


Cloud computing Task Resources Ant colony algorithm Pheromone Fitness function 


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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.Institute of Aeronautical EngineeringDundigal, HyderabadIndia

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