{'fraction_non_alphanumeric': 0.015141955835962145, 'fraction_numerical': 0.0, 'mean_word_length': 5.171206225680934, '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}}
Diversity Routing to Improve Delay-Jitter Tradeoff in Uncertain Network Environments

In this paper we propose a novel approach to deliver better delay-jitter performance in dynamic networks. Dynamic networks experience rapid and unpredictable fluctuations and hence, a certain amount of uncertainty about the delay-performance of various network elements is unavoidable. This uncertainty makes it difficult for network operators to guarantee a certain quality of service (in terms of delay and jitter) to users. The uncertainty about the state of the network is often overlooked to simplify problem formulation, but we capture it by modeling the delay on various links as general and potentially correlated random processes. Within this framework, a user will request a certain delay-jitter performance guarantee from the network. After verifying the feasibility of the request, the network will respond to the user by specifying a set of routes as well as the proportion of traffic which should be sent through each one to achieve the desired quality of service. We propose to use mean-variance analysis as the basis for traffic distribution and route selection, and show that this technique can significantly reduce the end-to-end jitter because it accounts for the correlated nature of delay across different paths. The resulting traffic distribution is often non-uniform and the fractional flow on each path is the solution to a simple convex optimization problem. We conclude the paper by commenting on the potential application of this method to general transportation networks.