A Cost-Aware Mechanism for Optimized Resource Provisioning in Cloud Computing

by   Safiye Ghasemi, et al.

Due to the recent wide use of computational resources in cloud computing, new resource provisioning challenges have been emerged. Resource provisioning techniques must keep total costs to a minimum while meeting the requirements of the requests. According to widely usage of cloud services, it seems more challenging to develop effective schemes for provisioning services cost-effectively; we have proposed a novel learning based resource provisioning approach that achieves cost-reduction guarantees of demands. The contributions of our optimized resource provisioning (ORP) approach are as follows. Firstly, it is designed to provide a cost-effective method to efficiently handle the provisioning of requested applications; while most of the existing models allow only workflows in general which cares about the dependencies of the tasks, ORP performs based on services of which applications comprised and cares about their efficient provisioning totally. Secondly, it is a learning automata-based approach which selects the most proper resources for hosting each service of the demanded application; our approach considers both cost and service requirements together for deploying applications. Thirdly, a comprehensive evaluation is performed for three typical workloads: data-intensive, process-intensive and normal applications. The experimental results show that our method adapts most of the requirements efficiently, and furthermore the resulting performance meets our design goals.


page 5

page 10


DeepScaler: Holistic Autoscaling for Microservices Based on Spatiotemporal GNN with Adaptive Graph Learning

Autoscaling functions provide the foundation for achieving elasticity in...

FaasKeeper: a Blueprint for Serverless Services

FaaS (Function-as-a-Service) brought a fundamental shift into cloud comp...

Cloud Resource Optimization for Processing Multiple Streams of Visual Data

Hundreds of millions of network cameras have been installed throughout t...

Digital Twin-Empowered Network Planning for Multi-Tier Computing

In this paper, we design a resource management scheme to support statefu...

FECBench: A Holistic Interference-aware Approach for Application Performance Modeling

Services hosted in multi-tenant cloud platforms often encounter performa...

Cost-effective BlackWater Raft on Highly Unreliable Nodes at Scale Out

The Raft algorithm maintains strong consistency across data replicas in ...

Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources

Applications that fuse machine learning and simulation can benefit from ...

Please sign up or login with your details

Forgot password? Click here to reset