{'fraction_non_alphanumeric': 0.01643835616438356, 'fraction_numerical': 0.0036529680365296802, 'mean_word_length': 5.122905027932961, '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}}
Assessing the Energy Consumption of 5G Wireless Edge Caching

Multi-access edge computing and caching (MEC) is regarded as one of the key technologies in fifth generation (5G) radio access networks to reduce network congestion and to improve user experience by bringing computing and storage resources closer to the end-users. However, deploying a large number of distributed MEC servers will consume a significant amount of network energy. Therefore, here we focus on the energy consumption of edge caching in 5G. We first introduce our proposed proactive caching (PC) algorithm for edge caching with Zipf request pattern, which could potentially improve the hit rate of user requests under the common deployment architectures of the edge caching in 5G. We then assess the energy consumption of the PC algorithm under different key factors and compare the energy consumption of the PC algorithm with that of traditional algorithms. The simulation results show that the trade-off of improving the hit rates using PC comes at the expense of additional energy consumption for network transmission.