{'fraction_non_alphanumeric': 0.018983807928531545, 'fraction_numerical': 0.0, 'mean_word_length': 5.711610486891386, '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': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Interference-Aware Multisource Transmission in Multiradio and Multichannel Wireless Network

A node can provide a file to other nodes after downloading the file or data from the Internet. When more than one node have obtained the same file, this is considered a multisource transmission, in which all these nodes can act as candidate providers (sources) and transmit the file to a new request node (destination) together. In cases where there is negligible or no interference, multisource transmission can improve the download throughput because of parallel transmissions through multiple paths. However, this improvement is not guaranteed due to wireless interference among different paths. Wireless interference can be alleviated by the multiradio and multichannel technique. Because the source and multipath routing selections interact with channel assignment, the multisource transmission problem with multiradio and multichannel presents a significant challenge. In this paper, we propose a distributed joint source, routing, and channel selection scheme. The source selection issue can be concurrently solved via multipath finding. There are three sub-algorithms in our scheme, namely, interference-aware routing algorithm, channel assignment algorithm, and local routing adjustment algorithm. The interference-aware routing algorithm is used to find paths sequentially and is jointly executed with the channel assignment algorithm. After finding a new path, the local routing adjustment algorithm may be executed to locally adjust the selected paths so as to further reduce wireless interference. Extensive simulations have been conducted to demonstrate that our algorithms can effectively improve the network aggregate throughput, as well as reduce delay and packet loss probability.