A service broker for Intercloud computing

This thesis aims at assisting users in finding the most suitable Cloud resources taking into account their functional and non-functional SLA requirements. A key feature of the work is a Cloud service broker acting as mediator between consumers and Clouds. The research involves the implementation and evaluation of two SLA-aware match-making algorithms by use of a simulation environment. The work investigates also the optimal deployment of Multi-Cloud workflows on Intercloud environments

D-SPACE4Cloud: A Design Tool for Big Data Applications

The last years have seen a steep rise in data generation worldwide, with the development and widespread adoption of several software projects targeting the Big Data paradigm. Many companies currently engage in Big Data analytics as part of their core business activities, nonetheless there are no tools and techniques to support the design of the underlying hardware configuration backing such systems. In particular, the focus in this report is set on Cloud deployed clusters, which represent a cost-effective alternative to on premises installations. We propose a novel tool implementing a battery of optimization and prediction techniques integrated so as to efficiently assess several alternative resource configurations, in order to determine the minimum cost cluster deployment satisfying QoS constraints. Further, the experimental campaign conducted on real systems shows the validity and relevance of the proposed method

Intelligent Management of Virtualised Computer Based Workloads and Systems

Managing the complexity within virtualised IT infrastructure platforms is a common problem for many organisations today. Computer systems are often highly consolidated into a relatively small physical footprint compared with previous decades prior to late 2000s, so much thought, planning and control is necessary to effectively operate such systems within the enterprise computing space. With the development of private, hybrid and public cloud utility computing this has become even more relevant; this work examines how such cloud systems are using virtualisation technology and embedded software to leverage advantages, and it uses a fresh approach of developing and creating an Intelligent decision engine (expert system). Its aim is to help reduce the complexity of managing virtualised computer-based platforms, through tight integration, high-levels of automation to minimise human inputs, errors, and enforce standards and consistency, in order to achieve better management and control. The thesis investigates whether an expert system known as the Intelligent Decision Engine (IDE) could aid the management of virtualised computer-based platforms. Through conducting a series of mixed quantitative and qualitative experiments in the areas of research, the initial findings and evaluation are presented in detail, using repeatable and observable processes and provide detailed analysis on the recorded outputs. The results of the investigation establish the advantages of using the IDE (expert system) to achieve the goal of reducing the complexity of managing virtualised computer-based platforms. In each detailed area examined, it is demonstrated how using a global management approach in combination with VM provisioning, migration, failover, and system resource controls can create a powerful autonomous system