Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation

One of the challenges of deploying multitenant cloud-hosted services that are designed to use (or be integrated with) several components is how to implement the required degree of isolation between the components when there is a change in the workload. Achieving the highest degree of isolation implies deploying a component exclusively for one tenant; which leads to high resource consumption and running cost per component. A low degree of isolation allows sharing of resources which could possibly reduce cost, but with known limitations of performance and security interference. This paper presents a model-based algorithm together with four variants of a metaheuristic that can be used with it, to provide near-optimal solutions for deploying components of a cloud-hosted application in a way that guarantees multitenancy isolation. When the workload changes, the model based algorithm solves an open multiclass QN model to determine the average number of requests that can access the components and then uses a metaheuristic to provide near-optimal solutions for deploying the components. Performance evaluation showed that the obtained solutions had low variability and percent deviation when compared to the reference/optimal solution. We also provide recommendations and best practice guidelines for deploying components in a way that guarantees the required degree of isolation

Emerging Trends of Cloud Computing

Cloud computing is Internet based system development in which large number of computing resources are provided as a service over the internet to users. The concept of cloud computing incorporates infrastructure of web, software as a service (SaaS), Web 2.0 and other emerging technologies, and has attracted more and more attention from industry and research community. We describe about the construction of a cloud computing platform. Specifically, we design a GFS(Global Foundation Service) compatible file system with variable chunk size to facilitate massive data processing, and introduce some implementation enhancement on Map Reduce to improve the system throughput. We also discuss some practical issues for system implementation

Kresge Foundation 2010-2011 Annual Report

Contains an introduction to Kresge's strategy; board chair's letter; president's letter; foundation timeline; program information; grant summary, including geographic distribution; grants lists; financial summary; and lists of board members and staff

Foundations and Technological Landscape of Cloud Computing

The cloud computing paradigm has brought the benefits of utility computing to a global scale. It has gained paramount attention in recent years. Companies are seriously considering to adopt this new paradigm and expecting to receive significant benefits. In fact, the concept of cloud computing is not a revolution in terms of technology; it has been established based on the solid ground of virtualization, distributed system, and web services. To comprehend cloud computing, its foundations and technological landscape need to be adequately understood. This paper provides a comprehensive review on the building blocks of cloud computing and relevant technological aspects. It focuses on four key areas including architecture, virtualization, data management, and security issues

Software-as-a Service Model: Elaborating Client-Side Adoption Factors

Software-as-a-Service (SaaS) is emerging as a viable outsourcing option for clients interested in paying for the right to access through the network a standardized set of business software functions. SaaS model largely replaced the Application Service Providers (ASPs)-based model, by creating an architecture that that provides no mechanisms for customizing the software on the vendor side; all customization is done on the client side through standardized interfaces. The fact that vendors are not making any client-specific investments makes this outsourcing model quite intriguing. In this paper we investigate client’s side determinants of adopting the SaaS model. We draw on economic, strategic management, and IS theories to develop a theoretical framework. In it, we develop a more elaborate view of uncertainty as some types uncertainty increase the propensity to adopt SaaS, while other types do the opposite. Finally, we integrate the role of the internal enterprise IT architecture into our model