{'fraction_non_alphanumeric': 0.022871664548919948, 'fraction_numerical': 0.0, 'mean_word_length': 5.350806451612903, '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}}
On the Performance and Cost of Cloud-Assisted Multi-path Bulk Data Transfer

Since the Internet is an aggregation of multiple ASes (Autonomous Systems), congestion control and utilization are not globally optimized. For example, it is not uncommon that a direct shortest route with low latency delivers less bandwidth than an alternative, long and roundabout route. Previous research has shown that geospatially distributed computing instances in commercial clouds offer users an opportunity to deploy relay points to detour potentially congested ASes, and as a means to diversify paths to increase overall bandwidth and reliability. Such opportunity comes with a cost, as cloud-routed paths incur cost of not only provisioning of computing resources, but also for additional traffic to/from Internet. Well-established protocols, such as TCP, were created based on assumption of single end-point to end-point transfer; nonetheless, current computing devices have multiple end-points, and the increasing availability of overlay networks allows multiplexing multiple virtual network flows into a single physical network interface. In this paper, we empirically evaluate the extent to which using cloud paths to transfer data in parallel with the default Internet path can improve the end-to-end bandwidth in bulk data transfers. In our evaluation, we consider single-stream and multi-stream TCP transfers across one or more paths. Moreover, we suggest an application level design pattern that takes advantage of this improved aggregate bandwidth to reduce data transfer times.