{'fraction_non_alphanumeric': 0.01762632197414806, 'fraction_numerical': 0.0, 'mean_word_length': 4.916666666666667, '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}}
Lossy Node Identification in Wireless Sensor Network

In a sensor network, the nodes that have a packet loss rate greater than a given threshold are called lossy nodes. Lossy nodes adversely affect network performance and collectively cause breakdown of network service in many cases. In this paper, we propose a new and simple approach to identify the lossy nodes from passive end-to-end measurements. Specifically, we consider the case of identifying lossy nodes during the aggregation of data from a collection of the sensor nodes to a sink node. The proposed method is based on the hamming distance of sequences on receipt/loss of aggregated data between each pair of parent-child node. With prior knowledge of the reverse data aggregation topology, our approach can identify all lossy nodes effectively. Finally, we validate the proposed approach