{'fraction_non_alphanumeric': 0.018842530282637954, 'fraction_numerical': 0.0, 'mean_word_length': 5.2521008403361344, '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}}
Maximizing utility of sensor-mission assignment with uncertain demands

A sensor network is usually required to support multiple missions to be accomplished simultaneously. Since missions might compete for the exclusive usage of the same sensing resource we need to assign individual sensors to missions. Missions are characterized by an uncertain demand for sensing resource capabilities. We model this assignment problem by introducing the Sensor Utility Maximization (SUM) model. SUM is NP-Complete and is a special case of the well known Generalized Assignment Problem (GAP). We compare a pre-existing algorithm developed for GAP with a new greedy algorithm which offers the best trade-off between quality of solution and computation cost.