A Review on Task Scheduling in Cloud Computing using parallel Genetic Algorithm
- Resource Type
- Conference
- Authors
- Bharot, Nitesh; Shukla, Shalini
- Source
- 2020 International Conference on Computing and Information Technology (ICCIT-1441) Computing and Information Technology (ICCIT-1441), 2020 International Conference on. :1-4 Sep, 2020
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Robotics and Control Systems
Signal Processing and Analysis
Genetic algorithms
Cloud computing
Task analysis
Load management
Processor scheduling
Rail to rail inputs
Sociology
Task scheduling
Load balancing
Genetic algorithm
Max-Min algorithm
Min-Min algorithm
- Language
This Cloud computing (CC) infrastructure has many issues including scheduling, budgeting & load balancing (LB). Among them, the biggest challenge for load balancing is a cloud platform. In task scheduling environment generally, the occurrence of load imbalance tends to uncertainty and complexity. Cloud computing is growing Internet-based computing platform & innovative that is emerging & one of its biggest tasks. The goal is to use resources efficiently & decrease resource consumption in the cloud environment. This can be achieved by increasing the LB rate when selecting the best resources for low work failure rates with low lead times. This paper discusses load balancing based on advanced genetic algorithms in the cloud computing platform.