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Robust Testing of Cloud Infrastructures

Currently much time is spent in setting up system tests, trying to understand exactly what is being tested, understanding errors that occur during tests, and verifying the test results. These issues can be especially difficult for distributed enterprise applications made up of a large number of software components that run on a collection of heterogeneous servers or cloud environments. Load generation for accurate simulation of complex user behaviour is a growing challenge when testing large-scale critical systems.

[ Energy Efficiency in Large Environments

Understanding organization-wide hardware utilization is currently a difficult challenge for industry. Current monitoring tools tend to focus on monitoring critical servers and databases and have not been designed to scale to manage entire IT infrastructures including desktops, laptops, servers, routers etc. This is an issue for many different domains (e.g. organizations with large IT infrastructures, cloud computing providers) where an understanding of how computer hardware is being utilized is essential for understanding business costs and future investment requirements. This research proposes to investigate, develop and deliver a solution to track utilization and efficiency of assets in heterogeneous environments.

Expert Tools for Root Cause Analysis

Enterprise applications typically can contain millions of objects and thousands of different types. A major issue in relation to these systems is that very often performance issues can occur during development and/or when the system is in production. These issues can lead to increased cost during the application development cycle and lost revenue in production. The aim of this research is to improve on current software tools that assist with monitoring, analysing and improving system performance.