{'fraction_non_alphanumeric': 0.02096569250317662, 'fraction_numerical': 0.0, 'mean_word_length': 5.673728813559322, '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}}
Offloading Schemes in Mobile Edge Computing for Ultra-Reliable Low Latency Communications

The ultra-reliable low latency communications (uRLLC) in the fifth generation mobile communication system aims to support diverse emerging applications with strict requirements of latency and reliability. Mobile edge computing (MEC) is considered as a promising solution to reduce the latency of computation-intensive tasks leveraging powerful computing units at short distance. The state-of-art work on task offloading to MEC mainly focuses on the tradeoff between latency and energy consumption, rather than reliability. In this paper, the tradeoff between the latency and reliability in task offloading to MEC is studied. A framework is provided, where user equipment partitions a task into sub-tasks and offloads them to multiple nearby edge nodes (ENs) in sequence. In this framework, we formulate an optimization problem to jointly minimize the latency and offloading failure probability. Since the formulated problem is nonconvex, we design three algorithms based on heuristic search, reformulation linearization technique and semi-definite relaxation, respectively, and solve the problem through optimizing EN candidates selection, offloading ordering and task allocation. Compared with the previous work, the numerical simulation results show that the proposed algorithms strike a good balance between the latency and reliability in uRLLC. Among them, the Heuristic Algorithm achieves the best performance in terms of the latency and reliability with the minimal complexity.