Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Heuristics for Efficient Resource Allocation in Cloud Computing

View through CrossRef
The resource allocation in cloud computing determines the allocation of computer and network resources of service providers to service requests of users for meeting user service requirements. It is not scalable to solve the resource allocation problem as an optimization problem to obtain the optimal solution in real time. This paper presents the development and testing of heuristics for the efficient resource allocation to obtain near-optimal solutions in a scalable manner. We first define the resource allocation problem as a Mixed Integer rogramming (MIP) optimization problem and obtain the optimal solutions for various resource-service problem types. Based on the analysis of the optimal solutions, we design heuristics for the efficient resource allocation. Then we evaluate the performance of the resource allocation heuristics using various resource-service problem types and different numbers of service requests and resources. The results show the comparable performance of the heuristics to the optimal solutions. The resource allocation heuristics also demonstrate the better computational efficiency and thus scalability than solving the MIP problems to obtain the optimal solutions. Keywords: Resource allocation; Clouds computing; Heuristics; Mixed integer programming
Title: Heuristics for Efficient Resource Allocation in Cloud Computing
Description:
The resource allocation in cloud computing determines the allocation of computer and network resources of service providers to service requests of users for meeting user service requirements.
It is not scalable to solve the resource allocation problem as an optimization problem to obtain the optimal solution in real time.
This paper presents the development and testing of heuristics for the efficient resource allocation to obtain near-optimal solutions in a scalable manner.
We first define the resource allocation problem as a Mixed Integer rogramming (MIP) optimization problem and obtain the optimal solutions for various resource-service problem types.
Based on the analysis of the optimal solutions, we design heuristics for the efficient resource allocation.
Then we evaluate the performance of the resource allocation heuristics using various resource-service problem types and different numbers of service requests and resources.
The results show the comparable performance of the heuristics to the optimal solutions.
The resource allocation heuristics also demonstrate the better computational efficiency and thus scalability than solving the MIP problems to obtain the optimal solutions.
Keywords: Resource allocation; Clouds computing; Heuristics; Mixed integer programming.

Related Results

THE IMPACT OF CLOUD COMPUTING ON CONSTRUCTION PROJECT DELIVERY ABUJA NIGERIA
THE IMPACT OF CLOUD COMPUTING ON CONSTRUCTION PROJECT DELIVERY ABUJA NIGERIA
Cloud computing is the delivery of computing services, such as storage, processing power, and software applications, via the internet. Cloud computing offers various advantages and...
Leveraging Artificial Intelligence for smart cloud migration, reducing cost and enhancing efficiency
Leveraging Artificial Intelligence for smart cloud migration, reducing cost and enhancing efficiency
Cloud computing has become a critical component of modern IT infrastructure, offering businesses scalability, flexibility, and cost efficiency. Unoptimized cloud migration strategi...
Energy‐aware cross‐layer resource allocation in mobile cloud
Energy‐aware cross‐layer resource allocation in mobile cloud
SummaryThis paper proposed an energy‐aware cross‐layer mobile cloud resource allocation approach. In this paper, a hybrid cloud architecture is adopted for provisioning mobile serv...
Advanced computational model for energy-efficient resource allocation in cloud computing environments
Advanced computational model for energy-efficient resource allocation in cloud computing environments
Cloud computing uses resource allocation techniques to maximize compute efficiency while preserving energy usage. Energy-efficient models reduce environmental exposure while mainta...
Is cloud computing a game-changer for SME financial performance? Unveiling the mediating role of organizational agility through PLS-SEM
Is cloud computing a game-changer for SME financial performance? Unveiling the mediating role of organizational agility through PLS-SEM
PurposeCloud computing services are game-changing in empowering organizations to drive innovation and unlock new growth opportunities. Accordingly, this study aims to examine the d...
Resource Scheduling in Cloud Computing Based on a Hybridized Whale Optimization Algorithm
Resource Scheduling in Cloud Computing Based on a Hybridized Whale Optimization Algorithm
The cloud computing paradigm, as a novel computing resources delivery platform, has significantly impacted society with the concept of on-demand resource utilization through virtua...
Leveraging Design Heuristics for Multi-Objective Metamaterial Design Optimization
Leveraging Design Heuristics for Multi-Objective Metamaterial Design Optimization
Abstract Design optimization of metamaterials and other complex systems often relies on the use of computationally expensive models. This makes it challenging to use...
Assessing the Environmental Sustainability of Cloud Computing: A Life Cycle Assessment Approach
Assessing the Environmental Sustainability of Cloud Computing: A Life Cycle Assessment Approach
Cloud computing has emerged as a popular technology platform that allows businesses to store, access, and process data and applications over the internet. This technology has the p...

Back to Top