A demand-based approach to optimal resource allocation for network services with Quality of Service (QoS) requirements

2006 ◽  
Author(s):  
Athanassios Androutsos ◽  
Theodore Apostolopoulos
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Network Services ◽  
Optimal Resource Allocation ◽  
Optimal Resource

scholarly journals QoS Based Optimal Resource Allocation and Workload Balancing for Fog Enabled IoT

2021 ◽  
Vol 11 (1) ◽  
pp. 262-274
Author(s):  
Adnan Khalid ◽  
Qurat ul Ain ◽  
Awais Qasim ◽  
Zeeshan Aziz
Keyword(s):  
Resource Allocation ◽  
Quick Response ◽  
End User ◽  
Optimal Resource Allocation ◽  
Workload Balancing ◽  
Data Profiling ◽  
Optimal Resource ◽  
Quality Of Service Parameters ◽  
Cloud Network

Abstract This paper is aimed at efficiently distributing workload between the Fog Layer and the Cloud Network and then optimizing resource allocation in cloud networks to ensure better utilization and quick response time of the resources available to the end user. We have employed a Dead-line aware scheme to migrate the data between cloud and Fog networks based on data profiling and then used K-Means clustering and Service-request prediction model to allocate the resources efficiently to all requests. To substantiate our model, we have used iFogSim, which is an extension of the CloudSim simulator. The results clearly show that when an optimized network is used the Quality of Service parameters exhibit better efficiency and output.

scholarly journals Iaas: Qos based Automated User Requirement Identification for Optimal Resource Allocation in Multi Cloud

2018 ◽  
Vol 7 (3.34) ◽  
pp. 210
Author(s):  
K S.Guruprakash ◽  
Syed Fiaz.A.S ◽  
S Sankar
Keyword(s):  
Resource Allocation ◽  
Service Provider ◽  
Cost Effective ◽  
Cloud Service ◽  
Optimal Resource Allocation ◽  
User Requirement ◽  
Usage Patterns ◽  
Optimal Resource ◽  
Multi Cloud

Resource allocation and optimization is one of the important characteristics in cloud computing environment. An vital goal of any cloud service provider is to allocate cost effective and optimized resource packages to the consumers that meet the QOS (Quality of Service) requirements.  Though the various set of cloud resources are available, selecting an appropriate resource to the consumers based on their requirements is a tedious task for any providers. Many researchers have already discussed different algorithms for finding the optimal resources to the consumers. However there is a challenge in selecting exact resources that meet QoS Parameters such as performance, availability, reliability and so on. This paper proposes an effective method for optimal resource allocation in multi cloud environment.  This approach takes an input, set of QOS parameter value for each user and select the suitable package that matches the QOS value. This paper provides an effective resource allocation solution to IaaS (Infrastructure as a Service) provider based on consumers usage patterns.

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