Holistic cloud computing environmental quantification and behavioural analysis

Cloud computing has been characterized to be large-scale multi-tenant systems that are able to dynamically scale-up and scale-down computational resources to consumers with diverse Quality-of-Service requirements. In recent years, a number of dependability and resource management approaches have been proposed for Cloud computing datacenters. However, there is still a lack of real-world Cloud datasets that analyse and extensively model Cloud computing characteristics and quantify their effect on system dimensions such as resource utilization, user behavioural patterns and failure characteristics. This results in two research problems: First, without the holistic analysis of real-world systems Cloud characteristics, their dimensions cannot be quantified resulting in inaccurate research assumptions of Cloud system behaviour. Second, simulated parameters used in state-of-the-art Cloud mechanisms currently rely on theoretical values which do not accurately represent real Cloud systems, as important parameters such as failure times and energy-waste have not been quantified using empirical data. This presents a large gap in terms of practicality and effectiveness between developing and evaluating mechanisms within simulated and real Cloud systems. This thesis presents a comprehensive method and empirical analysis of large-scale production Cloud computing environments in order to quantify system characteristics in terms of consumer submission and resource request patterns, workload behaviour, server utilization and failures. Furthermore, this work identifies areas of operational inefficiency within the system, as well as quantifies the amount of energy waste created due to failures. We discover that 4-10% of all server computation is wasted due to Termination Events, and that failures contribute to approximately 11% of the total datacenter energy waste. These analyses of empirical data enables researchers and Cloud providers an enhanced understanding of real Cloud behaviour and supports system assumptions and provides parameters that can be used to develop and validate the effectiveness of future energy-efficient and dependability mechanisms

A comparative study of transaction management services in multidatabase heterogeneous systems

Multidatabases are being actively researched as a relatively new area in which many aspects are not yet fully understood. This area of transaction management in multidatabase systems still has many unresolved problems. The problem areas which this dissertation addresses are classification of multidatabase systems, global concurrency control, correctness criterion in a multidatabase environment, global deadlock detection, atomic commitment and crash recovery. A core group of research addressing these problems was identified and studied. The dissertation contributes to the multidatabase transaction management topic by introducing an alternative classification method for such multiple database systems; assessing existing research into transaction management schemes and based on this assessment, proposes a transaction processing model founded on the optimal properties of transaction management identified during the course of this research.ComputingM. Sc. (Computer Science