scholarly journals A Rule-based Approach for Effective Resource Provisioning in Hybrid Cloud Environment

2012 ◽  
pp. 128-133
Author(s):  
Rajkamal Kaur Grewal ◽  
Pushpendra Kumar Pateriya
Keyword(s):  
Resource Provisioning ◽  
Hybrid Cloud ◽  
Cloud Environment ◽  
Public Cloud ◽  
Private Cloud ◽  
Resource Manager ◽  
Rule Based ◽  
Heterogeneous Clouds ◽  
Rule Based Approach ◽  
The Cost

Resource provisioning is important issue in cloud computing and in the environment of heterogeneous clouds. The private cloud with confidentiality data configure according to users need. But the scalability of the private cloud limited. If the resources private clouds are busy in fulfilling other requests then new request cannot be fulfilled. The new requests are kept in waiting queue to process later. It take lot of delay to fulfill these requests and costly. In this paper Rule Based Resource Manager proposed for the Hybrid environment, which increase the scalability of private cloud on-demand and reduce the cost. Also set the time for public cloud and private cloud to fulfill the request and provide the services in time. The Evaluated the performance of Resource Manager on the basis of resource utilization and cost in hybrid cloud environment.

scholarly journals Data Placement for Privacy-Aware Applications over Big Data in Hybrid Clouds

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Xiaolong Xu ◽  
Xuan Zhao ◽  
Feng Ruan ◽  
Jie Zhang ◽  
Wei Tian ◽  
...  
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Data Placement ◽  
Cloud Services ◽  
Hybrid Cloud ◽  
Public Cloud ◽  
Private Cloud ◽  
The Public ◽  
Placement Method ◽  
The Cost

Nowadays, a large number of groups choose to deploy their applications to cloud platforms, especially for the big data era. Currently, the hybrid cloud is one of the most popular computing paradigms for holding the privacy-aware applications driven by the requirements of privacy protection and cost saving. However, it is still a challenge to realize data placement considering both the energy consumption in private cloud and the cost for renting the public cloud services. In view of this challenge, a cost and energy aware data placement method, named CEDP, for privacy-aware applications over big data in hybrid cloud is proposed. Technically, formalized analysis of cost, access time, and energy consumption is conducted in the hybrid cloud environment. Then a corresponding data placement method is designed to accomplish the cost saving for renting the public cloud services and energy savings for task execution within the private cloud platforms. Experimental evaluations validate the efficiency and effectiveness of our proposed method.

Hierarchical Scheduling Optimization Scheme in Hybrid Cloud Computing Environments

2015 ◽  
Vol 24 (08) ◽  
pp. 1550111 ◽  
Author(s):  
Chunlin Li ◽  
LaYuan Li
Keyword(s):  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Provider ◽  
Hybrid Cloud ◽  
Public Cloud ◽  
Private Cloud ◽  
Optimization Scheme ◽  
Scheduling Optimization ◽  
Hierarchical Scheduling ◽  
Cloud Users

The paper proposes hierarchical scheduling optimization scheme in hybrid cloud. Our proposed hierarchical scheduling takes advantage of the interaction of cloud users, private cloud and public cloud. For high level optimization in hybrid cloud, the objective of public cloud provider optimization is to maximize the revenue of providing virtual machines (VMs) and minimize the energy cost. The private cloud users' applications give the unique optimal payment to public cloud providers under deadline and cost constraint to maximize the satisfaction of private cloud user applications. The objective of low-level scheduling optimization is to minimize the cost and execution time of private cloud application. From the simulation results, the revenue, execution success ratio and resource utilization of our proposed hierarchical scheduling algorithm are better than other related works.

scholarly journals An optimization approach to capacity evaluation and investment decision of hybrid cloud: a corporate customer’s perspective

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
In Lee
Keyword(s):  
Cloud Computing ◽  
Investment Decision ◽  
Optimal Investment ◽  
Optimization Approach ◽  
Hybrid Cloud ◽  
Public Cloud ◽  
Private Cloud ◽  
Penalty Cost ◽  
Require Time ◽  
The Public

Abstract While the rapid growth of cloud computing is driven by the surge of big data, the Internet of Things, and social media applications, an evaluation and investment decision for cloud computing has been challenging for corporate managers due to a lack of proper decision models. This paper attempts to identify critical variables for making a cloud capacity decision from a corporate customer’s perspective and develops a base mathematical model to aid in a hybrid cloud investment decision under probabilistic computing demands. The identification of the critical variables provides a means by which a corporate customer can effectively evaluate various cloud capacity investment opportunities. Critical variables included in this model are an actual computing demand, the amount of private cloud capacity purchased, the purchase cost of the private cloud capacity, the price of the public cloud, and the default downtime loss/penalty cost. Extending the base model developed, this paper also takes into consideration the interoperability cost incurred in cloud bursting to the public cloud and derives the optimal investment. The interoperable cloud systems require time and investment by the users and/or cloud providers and there exists a diminishing return on the investment. Hence, the relationship between the interoperable cloud investment and return on investment is also investigated.

Dynamic Service Provisioning and Selection for Satisfying Cloud Applications and Cloud Providers in Hybrid Cloud

2017 ◽  
Vol 26 (04) ◽  
pp. 1750005 ◽  
Author(s):  
Xu Lijun ◽  
Li Chunlin
Keyword(s):  
Resource Constraints ◽  
Cloud Model ◽  
Cloud Service ◽  
Cloud Provider ◽  
Service Provisioning ◽  
Hybrid Cloud ◽  
Public Cloud ◽  
Private Cloud ◽  
Cloud Users ◽  
Cloud User

The paper presents a hybrid cloud service provisioning and selection optimization scheme, and proposes a hybrid cloud model which consists of hybrid cloud users, private cloud and public cloud. This scheme aims to effectively provide cloud service and allocate cloud resources, such that the system utility can be maximized subject to public cloud resource constraints and hybrid cloud users constraints. The paper makes use of a utility-driven approach to solve interaction among private cloud user, hybrid cloud service provider and public cloud provider in hybrid cloud environment. The paper presents hybrid cloud service provisioning and selection algorithm in hybrid cloud. The hybrid cloud market consists of hybrid cloud user agent, hybrid cloud service agent and hybrid cloud agent, which represent the interests of different roles. The experiments are designed to compare the performance of proposed algorithm with the other related work.

Separating Monitoring from Control in SDN to Mitigate DDoS Attacks in Hybrid Clouds

2020 ◽  
Vol 10 (3) ◽  
pp. 382-394
Author(s):  
Tarek S. Sobh
Keyword(s):  
Denial Of Service ◽  
Attack Detection ◽  
Hybrid Cloud ◽  
Cloud Environment ◽  
Public Cloud ◽  
Ddos Attacks ◽  
Traffic Pattern ◽  
Proposed Model ◽  
Communication Time ◽  
Secure Networks

Background & Objective: Detecting and mitigating Distributed Denial of Service (DDoS) attacks is a serious problem. In addition, new features and network deployments such as Software- Defined Networking (SDN) may open the door for new threats that did not previously exist. : Recent publications and patent are reviewed to find new techniques developed for integrating different mechanisms to secure networks against DDoS. Methods: This work presents a simple model for integrating different mechanisms to secure both SDN and legacy network in a hybrid cloud environment, it is called FocusON. It aims at mitigating DDoS attacks of a victim network. In addition, separating network monitoring from its control aims at mitigating DDoS attacks of a victim network. Traffic pattern analysis is apart from attack detection mechanism that gives a conceptual representation of a specific kind of DDoS attacks. DDoS detection is a completely automated process. Once called, for the reaction, the active response will be taken against the real IP source of the attacker. : The communication time overhead was tested in order to evaluate the remote server response time in case of deploying our proposed model mechanisms and without our proposed model. : Here we introduce a response mechanism that consists of an analysis of event logs, traffic patterns, and IP traceback. The proposed model categorizes the underlying network according to the location into a victim network and the source of attack (public cloud). Results & Conclusion:: The proposed model implemented in a hybrid cloud environment using the network of SDN and legacy network. The experimental setup was built using our network lab connected to the Amazon public cloud.

Query processing over secure perturbed data over hybrid cloud

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sridhar Reddy Vulapula ◽  
Srinivas Malladi
Keyword(s):  
Design Methodology ◽  
Hybrid Cloud ◽  
Public Cloud ◽  
Private Cloud ◽  
Sensitive Data ◽  
Public And Private ◽  
Content Type ◽  
Hybrid Clouds ◽  
Efficient Retrieval ◽  
Private And Public

PurposeHybrid cloud composing of public and private cloud is seen as a solution for storage of health care data characterized by many private and sensitive data. In many hybrid cloud-based solutions, the data are perturbed and kept in public cloud, and the perturbation credentials are kept in private cloud.Design/methodology/approachHybrid cloud is a model combing private and public cloud. Security for the data is enforced using this distribution in hybrid clouds. However, these mechanisms are not efficient for range query and retrieval of data from cloud. In this work, a secure and efficient retrieval solution combining K-mean clustering, geometric perturbation and R-Tree indexing is proposed for hybrid clouds.FindingsCompared to existing solution, the proposed indexing on perturbed data is able to achieve 33% reduced retrieval time. The security of indexes as measured using variance of differences was 66% more than existing solutions.Originality/valueThis study is an attempt for efficient retrieval of data with range queries using R-Tree indexing approach.

Cost Evaluation on Building and Operating Cloud Platform

2013 ◽  
Vol 5 (2) ◽  
pp. 43-53 ◽  
Author(s):  
Yue-Shan Chang ◽  
Yi-Kang Lee ◽  
Tong-Ying Juang ◽  
Jing-Shyang Yen
Keyword(s):  
Net Present Value ◽  
Cost Model ◽  
Cost Evaluation ◽  
Public Cloud ◽  
Private Cloud ◽  
Public And Private ◽  
Purchasing Cost ◽  
Computing Platform ◽  
Cost Issue ◽  
The Cost

Cost issue always is one of most important issue for enterprise in building their IT platform. With the advance of various cloud environments, enterprise’s IT executive may have different consideration in constructing their IT platform. For example, constructing an own cloud environment or renting a computing platform from cloud providers. This paper the authors, based on the Net Present Value in Finance field, propose a cost model for evaluating the tradeoff between building a self-own computing platform and renting one from public provider. The cost evaluation formulas are derived based on some cost factor, such as human salary, platform purchasing cost, energy consuming, maintenance fee, and cooling cost, for evaluating required cost on building and operating of both public and private clouds. Based on the cost model, the authors applied a well-known public cloud instance, e.g. Chunghwa Telecom’s HiCloud platform in Taiwan, to compute renting cost, and make a comparison with the derived cost of private cloud for a variety of enterprises’ settings. According to the experiments, different size of enterprises could have different options in building private cloud or renting from public cloud to make optimum cost saving.

A Private Cloud-Based Smart Learning Environment Using Moodle for Universities

2019 ◽  
pp. 188-202 ◽  
Author(s):  
T. S. Pradeep Kumar
Keyword(s):  
Learning Environment ◽  
Learning Curve ◽  
Management System ◽  
Educational Institutions ◽  
Cloud Environment ◽  
Public Cloud ◽  
Private Cloud ◽  
Smart Learning Environment ◽  
The Public ◽  
Smart Learning

Moodle is an open source learning management system that helps universities host the courses online through standalone or a in a private cloud environment that helps the educational institutions grow exponentially with all the facilities Moodle can offer. This chapter identifies the feasibility of a university to host their courses in Moodle which runs under a private cloud environment. This chapter explains various difficulties incurred by the public cloud and other standalone servers. This chapter also analyzes various metrics towards smarter learning methodologies and observes that the learning curve of the users is considerably increasing, and hence, such models are suitable for universities with several thousands of users. This chapter proposes a method to deploy Moodle for a smarter learning environment in universities of huge strength.

Sign in / Sign up

Export Citation Format

Share Document