{'fraction_non_alphanumeric': 0.021121039805036556, 'fraction_numerical': 0.0, 'mean_word_length': 5.65945945945946, '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}}
Optimal energy allocation for remote state estimate under Denial‐of‐Service attack

This paper considers an energy-constrained sensor power allocation problem for remote estimation under Denial-of-Service attack. Due to power constraints, the sensor needs to make a decision on how much power it should employ to optimise the state estimation performance under Denial-of-Servic attacks without using real-time acknowledgment information. Different from the existing works concerning non-zero power value with discrete values or one power value, the authors consider the multilevel continuous-valued energy allocation policy containing zero power value in this work. By analysing the effects on performance index under different energy allocation policies, an optimal off-line power scheduling policy with non-decreasing structure is derived. To obtain the optimal power scheduling sequences, the authors formulate the problem as non-linear programming after analysing the probability distribution of the estimation error covariance matrix. Moreover, the two power values energy allocation policy is investigated as a special case. At last, simulation examples are presented to verify the effectiveness of their theoretical results.