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Community-based “Piggy-back Network” utilizing Local Fixed & Mobile Resources supported by Heterogeneous Wireless & AI-based Mobility Prediction
"شبکه Piggy-back" مستقر در جامعه با استفاده از منابع محلی ثابت و موبایل پشتیبانی شده توسط بی سیم ناهمگن و پیش بینی تحرک مبتنی بر هوش مصنوعی-2020 This paper proposes a concept to construct a
community-based cross-industrial data/contents delivery platform
named “Piggy-back network,” which utilizes alreadyexisting
local fixed and mobile resources in a smart city. These
fixed and mobile resources are assumed to equip store-carryforwarding-
based (SCF-based) wireless data sharing functions,
i.e., a short-range but extremely high-speed millimeter-wave
device, a mid/long-range but low-speed microwave device, and
data storage buffer. It is discussed that the data delivery
performance of such SCF-based platform could exceed the one
when using wired/wireless infrastructure directly, and it will
be significantly improved if an AI-based mobility prediction
engine recommends the human drivers or the driving controllers
of future automated driving vehicles to detour and/or stop by
some specific locations. It is theoretically shown that the mobile
resources can potentially deliver high-volume data with shorter
time than using wired/wireless network infrastructures under
some conditions. The real commercial mobilities’ trajectory data
obtained experimentally in the city of Kakogawa, Japan, are
analyzed and the potential of the data delivery performance is
estimated. Index Terms: Piggy-back network | community-based cross-industrial data/contents delivery platform | Store-Carry- Forwarding | Opportunistic Network | AI-based mobility prediction |
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