Perceptive VM Allocation in Cloud Data Centers for Effective Resource Management
- Title
- Perceptive VM Allocation in Cloud Data Centers for Effective Resource Management
- Creator
- Savitha S.; Salvi S.
- Description
- Virtual Machine allocation in cloud computing centers has become an important research area. Efficient VM allocation can reduce power consumption and average response time which can benefit both the end users as well as the cloud vendors. This work presents a perceptive priority aware VM allocation policy named P-PAVA algorithm, which takes into account the priority of an application along with its compute, memory and bandwidth requirement. The algorithm performs allocation of the applications based on the priority it gets using a machine learning based prediction model. Furthermore, to reduce the overhead of the allocation algorithm, parallelization is employed before assigning various workloads. To achieve this, the algorithm employs the First fit technique as a baseline for the requests allocation with a criteria as low priority. When compared to the state of the art algorithm for VM allocation for priority aware applications, P-PAVA performs better on several criteria such as average response time, execution time and power consumption. 2021 IEEE.
- Source
- 2021 6th International Conference for Convergence in Technology, I2CT 2021
- Date
- 2021-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Cloud Computing; Parallelization; Prediction Model; Resource Management; VM Allocation
- Coverage
- Savitha S., Christ University, Department of Computer Science Engineering, Bangalore, India; Salvi S., National Institute of Technology Karnataka, Department of Information Technology, Surathkal, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-172818876-8
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Savitha S.; Salvi S., “Perceptive VM Allocation in Cloud Data Centers for Effective Resource Management,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/20501.