Over the past decade, there has been a paradigm shift leading consumers and enterprises to the adoption of cloud computing services. Even though most cases are still in the early stages of transition, there has been a steady increase in the implementation of the pay-as-you-go or pay-as-you-grow models offered by cloud providers. Whether applied as an extension of virtual infrastructure, software, or platform as a service, many users are still challenged by the estimation of adequate resource allocation and the wide variations in pricing. Customers require a simple method of predicting future demand in terms of the number of nodes to be allocated in the cloud environment. In this paper, we review and discuss existing methodologies for estimating the demand for cloud nodes and their corresponding pricing policies. Based on our review, we propose a novel approach using the Hidden Markov Model to estimate the acquisition of cloud nodes.
Despite the multifaceted advantages of cloud computing,concerns about data leakage or abuse impedes its adoption for security-sensi tive tasks.Recent investigations have revealed that the risk of unauthorized data access is one of the biggest concerns of users of cloud-based services.Transparency and accountability for data managed in the cloud is necessary.Specifically,when using a cloudhost service,a user typically has to trust both the cloud service provider and cloud infrastructure provider to properly handling private data.This is a multi-party system.Three particular trust models can be used according to the credibility of these providers.This pa per describes techniques for preventing data leakage that can be used with these different models.
