Task scheduling is a non-deterministic polynomial-time hard (NP-hard) optimisation problem, thus applying metaheuristics is important. In this paper, we employ glowworm swarm optimisation (GSO) to solve the task scheduling problem in cloud computing to minimise the total execution cost of tasks while keeping the total completion time within the deadline. Simulation results show that GSO based task scheduling (GSOTS) algorithm outperforms shortest task first (STF), largest task first (LTF) and particle swarm optimisation (PSO) algorithms in reducing the total completion time and the cost of executing tasks.
- cloud computing
- resource management
- glowworm swarm optimisation (GSO)
- task scheduling
Alboaneen, D. A., Tianfield, H., & Zhang, Y. (2017). Glowworm swarm optimisation based task scheduling for cloud computing. In Proceedings of the 2nd International Conference on Internet of things and Cloud Computing  ACM. https://doi.org/10.1145/3018896.3036395