{'fraction_non_alphanumeric': 0.018224573780129337, 'fraction_numerical': 0.0, 'mean_word_length': 5.211678832116788, '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}}
Towards Balancing Energy Savings and Performance for Volunteer Computing through Virtualized Approach

Computational grids consist of distributed environments where partner institutions offer hosts along with computational resources that can be used by all members of the grid. When an application needs to run in such environment, it allocates a portion of hosts necessary for its executions. Traditionally, the workload imposed on computational grids has a characteristic of being bag-of-tasks (BoT). It means that multiple replicas are submitted to different hosts, and when a response is processed, such replicas are either ignored or released. On resource allocation, as the grid is distributed among different participants, only idle resources can be leased by a new application. However, due to the behavior of BoTs, many allocated resources do not use their resources in their entirety. Another important fact is that only fully idle hosts can be added to the grid pool, and used only at these times. From the above, this paper proposes an approach that uses underutilized resource slice of grid hosts through virtualization, adjusting the use of grid applications to the leftover resources from daily hosts usage. It allows grid applications to run, even when hosts are in use, as long as there is an idle slice of resources, and their use does not interfere with the host’s current running. To evaluate this approach, we performed an empirical evaluation of a virtualized server running applications concurrently with a virtualized grid application. The results have showed that our scheme could accelerate the performance of grid applications without impacting on higher energy consumption.