Private Cloud Users Research Articles

Energy-Efficient Resource Allocation and Migration in Private Cloud Data Centre

The level of difficulty that can be envisioned in a cloud data center will not grow with convention. As a result, all hosts should have a standard and pervasive collection of memory and communication characteristics in order to lower ownership costs and operate virtual machine instances. This solution includes fundamental foundations and integrated component basics that will allow an IT or federal agency to embrace cloud computing domestically via private virtual cloud data centers. These private cloud data centers would later be developed to purchase and develop IT services on the outside. They are well aware of the obstacles to cloud computing’s acceptance, including concerns about credibility, privacy, interoperability, and marketplaces. In addition, this procedure describes critical standards and collaborations to address these issues. Ultimately, it offers a coherent response to deploying safe data centers using cloud computing services from both a technological and an IT strategic standpoint. To foster creativity, invention, learning, and enterprise, a private data center and cloud computing must be established to combine the activities of different research teams. In the framework of energy-efficient distribution of resources in private cloud data center architecture, we focus on system structure investigations. On the other hand, we want to equip private cloud providers with the current design and performance analysis for energy-efficient resource allocation. The methodology should be adaptable enough to support a wide range of computing systems, as well as on-demand and extensive resource providing approaches, cloud environment scheduling, and bridging the gap between private cloud users and a complete image of offers.

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

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.

A preemptive truthful VMs allocation online mechanism in private cloud

During the last decade, cloud-technology has presented considerable opportunities for high-performance computing (HPC). In addition, technical computing data centers have been able to maximize their return on investment (ROI). HPC system managers can leverage the benefits of a cloud model for their traditional HPC environments to improve scalability, simplify service access, accelerate collaboration or funding, enable pay-for-use, and improve efficiency. Many HPC clouds assume the form of private Infrastructure as a Service (IaaS). In practice, private cloud users may strategically misreport task values in order to achieve a high profit, and thus cloud providers cannot simply maximize the sum of allocated users’ value, which is called social welfare. For this reason, designing a mechanism that reveals the truthful value of users with a concern for both random arrival tasks and maximizing social welfare is necessary. In this study, a model of an online mechanism for virtual machines allocation is built, a preemptive online mechanism is proposed, the truthfulness is proved, a competitive ratio is given, and several simulations are conducted using real tasks from a data center. The total values and completed tasks are compared to the online and offline allocations, respectively, according to different capacity. The simulations reveal that our mechanism is more efficient than the offline mechanism.

Hierarchical Scheduling Optimization Scheme in Hybrid Cloud Computing Environments

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.

Implementation of searchable symmetric encryption for privacy-preserving keyword search on cloud storage

AbstractEnsuring the cloud data security is a major concern for corporate cloud subscribers and in some cases for the private cloud users. Confidentiality of the stored data can be managed by encrypting the data at the client side before outsourcing it to the remote cloud storage server. However, once the data is encrypted, it will limit server’s capability for keyword search since the data is encrypted and server simply cannot make a plaintext keyword search on encrypted data. But again we need the keyword search functionality for efficient retrieval of data. To maintain user’s data confidentiality, the keyword search functionality should be able to perform over encrypted cloud data and additionally it should not leak any information about the searched keyword or the retrieved document. This is known as privacy preserving keyword search. This paper aims to study privacy preserving keyword search over encrypted cloud data. Also, we present our implementation of a privacy preserving data storage and retrieval system in cloud computing. For our implementation, we have chosen one of the symmetric key primitives due to its efficiency in mobile environments. The implemented scheme enables a user to store data securely in the cloud by encrypting it before outsourcing and also provides user capability to search over the encrypted data without revealing any information about the data or the query.

Efficient Market Strategy Based Optimal Scheduling in Hybrid Cloud Environments

Hybrid cloud is a combination of a private cloud combined with the use of public cloud services where one or several touch points exist between the environments. Depending on utilization, data center cost and the costs of the cloud provider, an efficient scheduling policy has to decide whether or not moving from private cloud to public cloud is profitable. The paper proposes a market based hybrid cloud optimal scheduling optimization in hybrid cloud. The hybrid cloud marketplace is a virtual place where one or more public cloud providers and private cloud users meet to negotiate simultaneously. The scheduling optimization is conducted by hybrid cloud local scheduling and hybrid cloud global scheduling. For the global scheduling, the hybrid cloud system implements the allocation of public cloud resources to the private cloud application groups; the private cloud application group coordinates the deployments of all private cloud applications that consume the allocation of public cloud resources. For the local scheduling, the private cloud local level adjusts the cloud resource usages to optimize the utility of single private cloud application. In the simulations, compared with other related algorithm, our proposed market based hybrid cloud optimal scheduling algorithms achieve the better performance in terms of QoS satisfaction rate and allocation efficiency.