Name
Title | ||
|---|---|---|
An Energy-Efficient Task Scheduling Strategy Based on Improved Fireworks Algorithm in Heterogeneous Cloud |
Abstract | ||
|---|---|---|
With the development of cloud computing, energy consumption is getting bigger and bigger, and energy optimization has become one of the research focuses. Task scheduling is an efficient way to reduce the energy consumption of cloud. Most previous works ignored the heterogeneity of physical machines (PMs) configured with different CPUs and GPUs, which may result in high energy consumption in heterogeneous cloud. In this paper, an energy-efficient Task Scheduling Strategy based on Improved Fireworks Algorithm (TSS-IFWA) is proposed to reduce the energy consumption of the CPU/GPU heterogeneous cloud. First, a task scheduling model is constructed, in which the energy consumption of CPUs and GPUs are separately consid-ered. Then we obtain the task scheduling optimization problem of minimizing the energy consumption of heterogeneous cloud. Second, as traditional fireworks algorithm consumes massive computing resource and has a poor convergence performance, we improve a new calculation method of explosion amplitude of the fireworks algorithm. We also optimize the mutation strategy. Third, we utilize the improved fireworks algorithm to solve the task scheduling optimization problem. Specifically, the corre-sponding coding and decoding schemes of the fireworks algorithm are designed to initialize the fireworks individuals. We then obtain task scheduling results. Finally, TSS- IFWA is compared with traditional fireworks algorithm (FWA), round-robin algorithm (RR), and genetic algorithm (GA). The experimental results show that TSS- IFWA has a good performance in reducing energy consumption of heterogeneous cloud. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00052 | 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys) |
Keywords | DocType | ISBN |
Cloud computing,energy-efficient,task scheduling,fireworks algorithm,heterogeneous cloud | Conference | 978-1-6654-9458-8 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Zhao | 1 | 16 | 9.22 |
| Fanxin Meng | 2 | 0 | 0.34 |
| Nanzhi Feng | 3 | 0 | 0.34 |
| Quan Wang | 4 | 105 | 21.41 |
| Bo Wan | 5 | 0 | 0.68 |
| Wang Jing | 6 | 47 | 22.40 |