Group Based Resource Management and Pricing Model in Cloud Computing

Cloud computing utilizes large scale computing infrastructure that has been radically changing the ITlandscape enabling remote access to computing resources with low service cost, high scalability ,availability and accessibility. Serving tasks from multiple users where the tasks are of differentcharacteristics with variation in the requirement of computing power may cause under or over utilizationof resources.Therefore maintaining such mega-scale datacenter requires efficient resource managementprocedure to increase resource utilization. However, while maintaining efficiency in service provisioning itis necessary to ensure the maximization of profit for the cloud providers. Most of the current researchworks aims at how providers can offer efficient service provisioning to the user and improving systemperformance. There are comparatively fewer specific works regarding resource management which alsodeals with the economic section that considers profit maximization for the provider. In this paper werepresent a model that deals with both efficient resource utilization and pricing of the resources. The jointresource management model combines the work of user assignment, task scheduling and load balancingon the fact of CPU power endorsement. We propose four algorithms respectively for user assignment, taskscheduling, load balancing and pricing that works on group based resources offering reduction in taskexecution time(56.3%),activated physical machines(41.44%),provisioning cost(23%) . The cost iscalculated over a time interval involving the number of served customer at this time and the amount ofresources used within this time.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-08
DOI
https://doi.org/10.5281/zenodo.17291200
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Group Based Resource Management and Pricing Model in Cloud Computing

Zenodo (CERN European Organization for Nuclear Research)
Cell Image Analysis Techniques
article

Group Based Resource Management and Pricing Model in Cloud Computing

article en

Abstract

Cloud computing utilizes large scale computing infrastructure that has been radically changing the ITlandscape enabling remote access to computing resources with low service cost, high scalability ,availability and accessibility. Serving tasks from multiple users where the tasks are of differentcharacteristics with variation in the requirement of computing power may cause under or over utilizationof resources.Therefore maintaining such mega-scale datacenter requires efficient resource managementprocedure to increase resource utilization. However, while maintaining efficiency in service provisioning itis necessary to ensure the maximization of profit for the cloud providers. Most of the current researchworks aims at how providers can offer efficient service provisioning to the user and improving systemperformance. There are comparatively fewer specific works regarding resource management which alsodeals with the economic section that considers profit maximization for the provider. In this paper werepresent a model that deals with both efficient resource utilization and pricing of the resources. The jointresource management model combines the work of user assignment, task scheduling and load balancingon the fact of CPU power endorsement. We propose four algorithms respectively for user assignment, taskscheduling, load balancing and pricing that works on group based resources offering reduction in taskexecution time(56.3%),activated physical machines(41.44%),provisioning cost(23%) . The cost iscalculated over a time interval involving the number of served customer at this time and the amount ofresources used within this time.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Openalex Percentile: Top 31%
Cell Image Analysis Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Group Based Resource Management and Pricing Model in Cloud Computing · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS