{'fraction_non_alphanumeric': 0.017412935323383085, 'fraction_numerical': 0.009950248756218905, 'mean_word_length': 5.221649484536083, '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}}
Holistic network selection using dynamic weights to achieve personalized ABC

Network selection technique will be one of the deciding factors in determining the success of 4G network. This is because even though the 4G network technologies such as IEEE 802.16m and LTE-A is capable of providing 4G performance, the benefits that these technologies extol will not trickle down to the mobile nodes (MN) involved if the network selection method is inefficient. High speed MNs will be a feature of 4G networks as these networks are capable of supporting MNs that move at a speed of up to 250km/hr. Therefore, a network selection mechanism that takes into account MN's mobility scenario is absolutely necessary. Network communication environment that is heterogeneous, whereby MNs with multiple interfaces can connect to is also becoming the norm. This means network selection method that can provide personalized Always Best Connected (ABC) is vital in maximizing the potential of heterogeneous candidate networks (CN) in fulfilling user's needs. This paper discusses how this can be attained using a network selection methodology that encompasses dynamic weights and detailed user requirement data collection.