Cloudbus Toolkit for Market-Oriented Cloud Computing

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of Cloud applications and deployment on private or public Clouds, in addition to supporting market-oriented resource management; (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party Cloud brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green Clouds; and (vi) pathways for future research.Comment: 21 pages, 6 figures, 2 tables, Conference pape

Addressing Security issues for Enterprises Migrating to HYBRID Cloud Computing Model

Although on premises deployment has been a reliable platform to deploy in house applications & production software’s like email, ERP, Web servers, database for long, but managing the datacenter, applications, & specially the upgrade path for the newer version of software was always a challenge for the enterprises. Today, considering the rapid growing market of cloud computing, many organizations are keen to adopt the cloud platform. Cloud computing technology drawn the attention of IT world and is now days changing the focus of enterprises too. DOI: 10.17762/ijritcc2321-8169.15062

Resources allocation and scheduling approaches for business process applications in Cloud contexts

International audienceIn the last years, the Cloud computing environment has emerged as new execution support of business process. However, despite the proven benefits of using Cloud to run business process, users lack guidance for choosing between multiple offerings while taking into account several objectives, which are often conflicting. On the other side, elastic computing, such as Amazon EC2, allows users to allocate and release compute resources (virtual machines) on-demand and pay only for what they use. Therefore, it is reasonable to assume that the number of virtual machines is infinite. This feature of Clouds has been called "illusion of infinite resources''. Moreover, including human resources in the business process execution process make the automated execution of workflow difficult, due to the fact that the number of human resources is finite. In this paper, we develop an allocation strategy for Cloud computing platform taking into account the above characteristics. More precisely, we propose three complementary bi-criterion approaches for resources allocation and scheduling of business process on distributed Cloud resources

Honey bee based trust management system for cloud computing

Cloud computing has been considered as the new computing paradigm that would offer computer resources over the Internet as service.With the widespread use of cloud, computing would become another utility similar to electricity, water, gas and telephony where the customer would be paying only for the services consumed contrary to the current practice of paying a monthly or annual fixed charge irrespective of use.For cloud computing to become accepted by everybody, several issues need to be resolved.One of the most important issues to be addressed is cloud security.Trust management is one of the important components of cloud security that requires special attention. In this paper, the authors propose the concept that honey bee algorithm which has been developed to solve complex optimization problems can be successfully used to address this issue.The authors have taken a closer look at the optimization problems that had been solved using the honey bee algorithm and the similarity between these problems and the cloud computing environment.Thus concluding that the honey bee algorithm could be successfully used to solve the trust management issue in cloud computing

Review of cloud computing in science, technology, and real life

This paper presents an overview of the general idea and history of cloud computing in theory. The objective of this review is to draw attention to preceding studies about cloud computing that have common characteristics with the theme of this paper. There were some points discussed in general, including the advantages of this technology, its subjects, security, and the effects of adopting cloud computing in an organization

Responsive Multi-objective Load Balancing Transformation Using Particle Swarm Optimization in Cloud Environment

Cloud computing is an emerging computing paradigm with a large collection of heterogeneous autonomous systems with flexible computational architecture which provides the customers with computing resources as a service over a network on their demand. A multi-objective nature is inherent in cloud resource scheduling, as the objectives of cloud providers, cloud users, and other stakeholders can be independent. Resource allocation among multiple clients has to be ensured as per service level agreements. Several techniques have been invented and tested by research community for generation of optimal schedules in cloud computing. To accomplish these goals and achieve high performance, it is important to design and develop a Responsive multi-objective load balancing Transformation algorithm (RMOLBT) based on abstraction in multi cloud environment. It is most challenging to schedule the tasks along with satisfying the user’s Quality of Service requirements. This paper proposes a  wide variety of task scheduling and resource utilization using Particle swarm Optimization (PSO) in cloud environment. The result obtained by RMOLBT was simulated by an open source cloudsim configured with test case specification. Finally, the results  demonstrate the suitability of the proposed scheme that will increase throughput, reduce waiting time, reduction in missed process considerably and balances load among the physical machines in a Data centre in multi cloud environment

QoS-aware Scientific Application Scheduling Algorithm in Cloud Environment

Many complex scientific applications are modeled in the form of workflows to carry out large-scale experiments. Because of complexity of scientific processes, scientific workflows need intensive computation and data requirements. Clouds make opportunity for scientific that need high performance computing infrastructure. So scientific can run their application on cloud by their desired QoS. We propose an algorithm that able scientific to select execute plan based on their preference QoS, like time and cost. Proposed algorithm ranks the tasks in workflow and then use UPFF function for select accurate resource, based on user’s QoS. We compared our proposed algorithm with the same work by several scenarios and results show proposed algorithm has better efficiency. Keywords Scientific application, Workflow scheduling, Cloud computin

Exploring Innovation Model and Evolution of Medical Cloud Service: A Case Study of Chung-Hwa Telecom in Taiwan

[[abstract]]"This study is a case study of Chung-Hwa Telecom. Based on a framework of cloud service, this study develops an innovation model of medical cloud services (MCS) and explores the evolution of the model. Through collecting the related secondary data of the case from 2002 to 2011 and in-depth interviews, this study has collected 274 events of service innovation. Each event is treated as an analysis unit. The findings are: 1) MCS innovations focus on CaaS, IaaS and PaaS, while SaaS and DaaS are insufficient; 2) MCS innovation evolution is from PaaS to IaaS; 3) The critical factors facilitating MCS concern infrastructure technology and network technology; 4) The quantity of both general and enterprise users served by MCS shows a U-type trend; the quantity of both government institutions and specific communities served by MCS shows an inverted U-type trend; the quantity of both education institutions and medical institutions served by MCS shows an increasing trend.