Piggy-back Network to enable Beyond5G Society supported by Autonomous Mobilities: Concept, Key technologies &amp; Prototyping on a Service Robot Platform

Shoji, Yozo; Nakauchi, Kiyohide; Watanabe, Yoshito; Hasegawa, So; Hasegawa, Mikio

doi:10.1109/wpmc52694.2021.9700426

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…(2) [6,7] analyzed the actual data of vehicles traversing urban areas and showed that an average effective throughput of 94 Mbps could be achieved if the data rate between mobilities was 200 Mbps.…”

Section: Piggyback Networkmentioning

confidence: 99%

“…We consider UAVs as carriers that physically deliver data. The concept of "Piggyback Network", which entrusts the distribution of data to mobility, has been proposed [6,7]. This network utilizes Store-Carry-Forward (SCF) routing among autonomous mobilities equipped with a device that enables high-speed communication by high-frequency radio, such as mmW.…”

Section: Introductionmentioning

confidence: 99%

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UAV data delivery and routing optimization in Piggyback Network

Hasegawa

Kuwata

et al. 2023

NOLTA

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The Piggyback Network has been proposed as one of the technologies to enable Beyond 5G society. The Piggyback Network provides a high-speed data transfer system with frequency radio, such as millimeter-wave (mmW) links and Store-Carry-Forward (SCF) based communication among multiple autonomous mobilities. Communicating with mmW enables high-speed and large-capacity data transfers. Autonomous mobilities include service robots, cars, and unmanned aerial vehicles (UAV). Simple calculations demonstrated the end-to-end throughput performance when a single mobility unit transfers a single piece of data. This paper considers expansion to handle multiple mobilities and data. To realize this data transfer system, we require data delivery assignment to autonomous mobility and route optimization. We propose local search algorithm for minimizing cost value based on the total time required for data to be delivered to the destination. This paper evaluates the data transfer performance of the Piggyback Network by UAVs in a large-scale field. If multiple data and delivery routes are appropriately assigned to multiple mobilities that can communicate at 10 Gbps and move at 100 km/h, the Piggyback Network can transfer 100 GB of data within approximately 2 min, which corresponds to a throughput of approximately 3000 Mbps. If the data size is 1000 GB and mobilities can move at 10 Gbps, data transfer is completed in approximately 4 min, which achieves approximately 30000 Mbps, faster than 5G and long term evolution (LTE) networks.

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Section: Piggyback Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

UAV data delivery and routing optimization in Piggyback Network

Hasegawa

Kuwata

et al. 2023

NOLTA

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“…A Piggyback network has been proposed as a data distribution platform based on a store-carry-forward (SCF) mechanism consisting of working mobilities, such as delivery trucks and serving robots [1]. This scheme has the potential to achieve higher throughput than existing infrastructurebased data transfers when transferring extremely large-scale data by equipping the mobilities with high-speed wireless communication such as millimeter waves or terahertz links.…”

Section: Introductionmentioning

confidence: 99%

Game Theory Approach for Autonomous Mobility-Assisted Piggyback Network with mm-Wave Links

Yamamoto,

Hasegawa,

Shoji

et al. 2024

IEICE Commun. Express

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A Piggyback network, which is a store-carry-forward network organized by working mobilities of delivery trucks and serving robots, realizes a large-scale data distribution platform. However, when the working mobilities participate in the Piggyback network, the data carrying and forwarding tasks influence their original tasks, resulting in additional transfer costs necessitating appropriate data transfer management. This study proposes a data-transfer management scheme in the Piggyback network. We have developed an algorithm based on the Stackelberg game to balance the end-to-end throughput and the cost required by working mobilities for each data delivery, and we have formulated a rule for the users to select the best mobility based on the balanced throughput and costs. The simulation results show that the proposed method maximizes the utility and achieves a high average throughput of the entire network.

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