Multi-objective workflow scheduling scheme: a multi-criteria decision making approach

Scheduling large workflows that are faced in many business as well as scientific domains such as economy, bioinformatics, astronomy and geophysics is an important area of research in the field of cloud computing. Many studies have been made to develop efficient algorithms for workflow scheduling that deal with multiple objectives. In the recent years, multi-criteria decision making (MCDM) methods have become popular for solving such multi-objective problems in various areas like risk management, climate change, renewable energy and so on. Particularly, the MCDM method called technique for order of preference by similarity to ideal solution (TOPSIS) has drawn extensive attention due to its easy understanding, fast and simple calculation. In this paper, we present a workflow scheduling algorithm in cloud environment based on TOPSIS that integrates entropy weight method (EWM). The proposed algorithm aims at minimizing makespan, cost, and energy consumption and maximizing the reliability. The algorithm is tested on various benchmark scientific workflows. The simulation results are compared with that of the related algorithms. The comparisons show that the proposed algorithm performs remarkably well in terms of cost and energy consumption while maintaining the other parameters within considerable limits.

Automated summary

This paper presents a cloud-based workflow scheduling algorithm based on TOPSIS, integrated with the EWM method. The algorithm aims to minimize cost and energy consumption while maximizing reliability, and has been tested on various benchmark scientific workflows, showing remarkable performance in terms of cost and energy consumption.