Efficient resource allocation and management by using load balanced multi-dimensional bin packing heuristic in cloud data centers

Resource optimization is becoming a prime factor in the progress of Internet-based technology, Cloud Computing. A resource management model is highly required in cloud data center paradigms to utilize available resources effectively. Bin-Packing problem is an applicable combinatorial optimization fo...

Full description

Saved in:
Bibliographic Details
Published in:The Journal of supercomputing 2023-02, Vol.79 (2), p.1398-1425
Main Authors: Nehra, P., Kesswani, Nishtha
Format: Article
Language:English
Subjects:
Algorithms
Cloud computing
Combinatorial analysis
Compilers
Computer Science
Data analysis
Data centers
Energy consumption
Heuristic
Interpreters
Load balancing
Optimization
Outliers (statistics)
Processor Architectures
Programming Languages
Resource allocation
Resource management
Resource utilization
Virtual environments
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Resource optimization is becoming a prime factor in the progress of Internet-based technology, Cloud Computing. A resource management model is highly required in cloud data center paradigms to utilize available resources effectively. Bin-Packing problem is an applicable combinatorial optimization for Virtual Machine (VM) to Physical Machine (PM) allocation to minimize the required PMs. In this paper, we have proposed an efficient resource allocation and management algorithm in two phases. During the first phase, a Load Balanced Multi-Dimensional Bin-Packing (LBMBP) heuristic for Virtual Machine (VM) to Physical Machine (PMs or host) allocation is introduced, considering multidimensional resources: CPU, RAM, and Network Bandwidth. In the Second Phase, to perform VM migration, a mechanism to detect overloaded and underloaded hosts based on outliers has been described. The proposed work illustrated the simulation results using CloudSim Plus Simulator and observed a reduction in the number of active PMs. Energy consumption and the number of migrations with improved resource utilization.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-022-04707-w