Title: An intelligent water drops-based approach for workflow scheduling with balanced resource utilisation in cloud computing
Authors: Mala Kalra; Sarbjeet Singh
Addresses: Department of Computer Science and Engineering, National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, India ' Department of Computer Science and Engineering, University Institute of Engineering and Technology (UIET), Panjab University, Chandigarh, India
Abstract: The problem of finding optimal solutions for scheduling scientific workflows in cloud environment has been thoroughly investigated using various nature-inspired algorithms. These solutions minimise the execution time of workflows, however may result in severe load imbalance among Virtual Machines (VMs) in cloud data centres. Cloud vendors desire the proper utilisation of all the VMs in the data centres to have efficient performance of overall system. Thus, load balancing of VMs becomes an important aspect while scheduling tasks in cloud environment. In this paper, we propose an approach based on Intelligent Water Drops (IWD) algorithm to minimise the execution time of workflows while balancing the resource utilisation of VMs in cloud computing environment. The proposed approach is compared with a variety of well-known heuristic and meta-heuristic techniques using three real-time scientific workflows, and experimental results show that the proposed algorithm performs better than these existing techniques in terms of makespan and load balancing.
Keywords: workflow scheduling; intelligent water drops algorithm; cloud environment; evolutionary computation; directed acyclic graphs; load balancing; balanced resource utilisation; optimisation techniques.
International Journal of Grid and Utility Computing, 2019 Vol.10 No.5, pp.528 - 544
Received: 20 Jun 2017
Accepted: 01 May 2018
Published online: 18 Jul 2019 *