scholarly journals Semantic Cloud Resource Recommendation Using Cluster Analysis in Hybrid Cloud Computing Environment

2015 ◽  
Vol 4 (9) ◽  
pp. 283-288 ◽  
Author(s):  
Younsun Ahn ◽  
Yoonhee Kim
Keyword(s):  
Cluster Analysis ◽  
Cloud Computing ◽  
Hybrid Cloud ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Cloud Resource

Resource scheduling strategy for uncertain factors in mobile cloud computing

2021 ◽  
pp. 1-6
Author(s):  
Ying Chen
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Computing Environment ◽  
Mobile Terminals ◽  
Cloud Computing Environment ◽  
Resource Allocation Algorithm ◽  
Cloud Resource ◽  
Resource Environment

At present, resource configuration of mobile cloud computing has received extensive attention from the outside world. Most of the similar resource scheduling configuration fails to comprehensively consider the dynamics of mobile terminals and the difference in user requested resources. Therefore, considering uncertainty in paging scheduling under mobile cloud resource environment from the perspective of consumers has become the key to solving the problem of resource allocation in the mobile cloud computing environment. This paper proposes an adaptive matching resource allocation algorithm based on uncertain factors under mobile cloud computing environment. Uncertain factors of the mobile terminal are derived via QoS attribute, and then user information and load characteristics of the user requested resources are analyzed through CLIQUE similarity matching. Afterwards, based on the mapping between similarity and resources, resource paging allocation can be carried out based on adaptive matching resource allocation algorithm. From the perspective of consumers, dynamics of mobile terminals and uncertainty of paging scheduling in the mobile cloud resource environment under different user requested resources can be considered to allow minimized delay and optimized paging strategies.

Analysis and Implementation of Kerberos Protocol in Hybrid Cloud Computing Environments

2021 ◽  
Vol 39 (1B) ◽  
pp. 41-52
Author(s):  
Turkan A. Khaleel
Keyword(s):  
Cloud Computing ◽  
Hybrid Cloud ◽  
Computing Environment ◽  
Network Efficiency ◽  
Cloud Computing Environment ◽  
Computing Services ◽  
Efficient Performance ◽  
Wide Range ◽  
Before And After ◽  
Cloud Computing Services

The concept of cloud computing has recently changed how hardware, software, and information are handled. However, security challenges and credibility requirements have never changed and may have increased. Protecting cloud computing and providing security for its resources and users is one of the critical challenges. As a result, most users are afraid to use their resources, because many security problems must be met. For example, authentication and reliability are major security constraints and must be provided in a cloud computing environment. There is a wide range of authentication protocols in use, but the researcher has recommended the Kerberos protocol to represent and test it in a complex environment such as a mixed cloud environment. A model has been developed to implement Kerberos authentication in a hybrid cloud computing environment to securely access the cloud computing services provided. This model is represented using the OPNET Modeler 14.5 simulation system. The network efficiency was measured before and after the hacker. Findings presented in this research are supporting the ability of the Kerberos protocol to prevent illegal access to cloud computing services, whether from within the private cloud or the public cloud. While maintaining the efficient performance of the network.

scholarly journals An Optimal Resource Provisioning Algorithm for Cloud Computing Environment

2017 ◽  
Vol 10 (2) ◽  
pp. 371-384
Author(s):  
Shivangi Nigam ◽  
Abhishek Bajpai
Keyword(s):  
Cloud Computing ◽  
Resource Provisioning ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Cloud Resource ◽  
Optimal Resource ◽  
Decision Alternatives ◽  
Hierarchy Process ◽  
Cloud Users ◽  
Cloud Resources

Resource Provisioning in a Cloud Computing Environment ensures flexible and dynamic access of the cloud resources to the end users. The Multi-Objective Decision Making approach considers assigning priorities to the decision alternatives in the environment. Each alternative represents a cloud resource defined in terms of various characteristics termed as decision criteria. The provisioning objectives refer to the heterogeneous requirements of the cloud users. This research study proposes a Resource Interest Score Evaluation Optimal Resource Provisioning (RISE-ORP) algorithm which uses Analytical Hierarchy Process (AHP) and Ant Colony Optimization (ACO) as a unified MOMD approach to design an optimal resource provisioning system. It uses AHP as a method to rank the cloud resources for provisioning. The ACO is used to examine the cloud resources for which resource traits best satisfy the provisioning. The performance of this approach is analyzed using CloudSim. The experimental results show that our approach offers improvement in the performance of previously used AHP approach for resource provisioning.

Applications integration in a hybrid cloud computing environment: modelling and platform

2013 ◽  
Vol 7 (3) ◽  
pp. 237-271 ◽  
Author(s):  
Qing Li ◽  
Ze-yuan Wang ◽  
Wei-hua Li ◽  
Jun Li ◽  
Cheng Wang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Hybrid Cloud ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Applications Integration ◽  
Environment Modelling

scholarly journals AVAILABILITY EVALUATION OF DIFFERENT PLANNING AND SCHEDULING ALGORITHMS IN HYBRID CLOUD SYSTEM

2020 ◽  
Vol 3 (4) ◽  
pp. 47-59
Author(s):  
Ahmed A. Hamed ◽  
Rabah A. Ahmed
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Hybrid Cloud ◽  
Computing Environment ◽  
Planning And Scheduling ◽  
Cloud Computing Environment ◽  
Individual Level ◽  
The Individual

The importance of hybrid cloud computing has become a reality in recent years for large and medium enterprises and even at the individual level, which increases the need for many improvements in its availability level. One of the most important things that affects availability is the task scheduling process. Task scheduling is subject to many scheduling algorithms and these algorithms differ in terms of performance and purpose, the most important aspects being improved by using an appropriate scheduling algorithm is the total execution time(makespane) and also the success rate and downtime live migration. Because working on a cloud computing environment is costly and complex, we have simulated a hybrid cloud environment using reliable and accurate simulation and used Directed acyclic graph(DAG) as a workflow application. In this paper we will compare scheduling and planning algorithms for cloud computing environment by implementing a framework using (workflowsim) based on (cloudsim) simulator in order to choose the best algorithm to verify the possibility of improving availability.

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