Utilisation of analogous climate locations to produce resilient biodiversity plantings for infrastructure developments

Developers have an obligation to biodiversity when considering the impact their development may have on the environment, with some choosing to go beyond the legal requirement for planning consent. Climate change projections over the 21st century indicate a climate warming and thus the species selected for habitat creation need to be able to withstand the pressures associated with these forecasts. A process is therefore required to identify resilient plantings for sites subject to climate change. Local government ecologists were consulted on their views on the use of plants of non-native provenance or how they consider resilience to climate change as part of their planting recommendations. There are mixed attitudes towards non-native species, but with studies already showing the impact climate change is having on biodiversity, action needs to be taken to limit further biodiversity loss, particularly given the heavily fragmented landscape preventing natural migration. A methodology has been developed to provide planners and developers with recommendations for plant species that are currently adapted to the climate the UK will experience in the future. A climate matching technique, that employs a GIS, allows the identification of European locations that currently experience the predicted level of climate change at a given UK location. Once an appropriate location has been selected, the plant species present in this area are then investigated for suitability for planting in the UK. The methodology was trialled at one site, Eastern Quarry in Kent, and suitable climate matched locations included areas in north-western France. Through the acquisition of plant species data via site visits and online published material, a species list was created, which considered original habitat design, but with added resilience to climate change.

Dynamic decision-making based on NFR for managing software variability and configuration selection

Due to dynamic variability, identifying the specific conditions under which non-functional requirements (NFRs) are satisfied may be only possible at runtime. Therefore, it is necessary to consider the dynamic treatment of relevant information during the requirements specifications. The associated data can be gathered by monitoring the execution of the application and its underlying environment to support reasoning about how the current application configuration is fulfilling the established requirements. This paper presents a dynamic decision-making infrastructure to support both NFRs representation and monitoring, and to reason about the degree of satisfaction of NFRs during runtime. The infrastructure is composed of: (i) an extended feature model aligned with a domain-specific language for representing NFRs to be monitored at runtime; (ii) a monitoring infrastructure to continuously assess NFRs at runtime; and (iii) a exible decision-making process to select the best available configuration based on the satisfaction degree of the NRFs. The evaluation of the approach has shown that it is able to choose application configurations that well fit user NFRs based on runtime information. The evaluation also revealed that the proposed infrastructure provided consistent indicators regarding the best application configurations that fit user NFRs. Finally, a benefit of our approach is that it allows us to quantify the level of satisfaction with respect to NFRs specification.

CloudMPL:a domain specific language for describing management policies for an autonomic cloud infrastructure

To benefit from the advantages that Cloud Computing brings to the IT industry, management policies must be implemented as a part of the operation of the Cloud. Among others, for example, the specification of policies can be used for the management of energy to reduce the cost of running the IT system or also for security policies while handling privacy issues of users. As cloud platforms are large, manual enforcement of policies is not scalable. Hence, autonomic approaches for management policies have recently received a considerable attention. These approaches allow specification of rules that are executed via rule-engines. The process of rules creation starts by the interpretation of the policies drafted by high-rank managers. Then, technical IT staff translate such policies to operational activities to implement them. Such process can start from a textual declarative description and after numerous steps terminates in a set of rules to be executed on a rule engine. To simplify the steps and to bridge the considerable gap between the declarative policies and executable rules, we propose a domain-specific language called CloudMPL. We also design a method of automated transformation of the rules captured in CloudMPL to the popular rule-engine Drools. As the policies are changed over time, code generation will reduce the time required for the implementation of the policies. In addition, using a declarative language for writing the specifications is expected to make the authoring of rules easier. We demonstrate the use of the CloudMPL language into a running example extracted from a management energy consumption case study.