{'fraction_non_alphanumeric': 0.017363851617995266, 'fraction_numerical': 0.0, 'mean_word_length': 5.125603864734299, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Towards Design-time Simulation Support for Energy-aware Cloud Application Development

Cloud application deployment is becoming increasingly popular for the removal of upfront hardware costs, the pay-per-use cost model and their ability to scale. However, deploying software on the Cloud carries both opportunities and threats regarding energy efficiency. In order to help Cloud application developers learn and reason about the energy consumption of their application on the server-side, we have developed a framework centred on a UML profile for relating energy goals, requirements and associated KPI metrics to application design and deployment elements. Our previous work has focused on the use of such a framework to carry out our run-time experiments in order to select the best approach. In this paper, we explore the feasibility of a complementary approach for providing support at design time based on finer grained deployment models, the specification of Cloud and energy adaptation policies and the use of a discrete event simulator for reasoning on key performance indicators such as energy but also overall performance, delay and costs. The goal is to support the Cloud developer in pre-selecting the best trade-off that can be further tuned at run-time.