{'fraction_non_alphanumeric': 0.011884550084889643, 'fraction_numerical': 0.0, 'mean_word_length': 5.304812834224599, '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': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Cloud virtual machine scheduling : Identifying issues in modelling the cloud virtual machine instantiation

Cloud computing provides an efficient and flexible mean for various services to meet the diverse and escalating needs of IT end-users. It offers novel functionalities including the utilisation of remote services in addition to the virtualization technology. The last one offers an efficient method to harness the cloud power by fragmenting a cloud physical host in small manageable virtual portions. As a norm, the virtualized parts are generated by the cloud provider administrator through the hypervisor based on a generic need for various services. However, several obstacles arise from this generalised and static approach. In this paper we study and propose a model for instantiating dynamically virtual machines in relation to the current jobs submission input. Following, we simulate a virtualised cloud environment in order to evaluate the model's dynamic-ness by measuring the correlation and analogy of virtual machines to hosts for certain job variations. This will allow us to measure the deviation of the execution time of various VMs instantiations per job