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Abstract Modeling and predicting human mobility trajectories in urban areas is an essential task for various applications including transportation modeling, disaster management, and urban planning. The recent availability of large-scale human movement data collected from mobile devices has enabled the development of complex human mobility prediction models. However, human mobility prediction methods are often trained and tested on different datasets, due to the lack of open-source large-scale human mobility datasets amid privacy concerns, posing a challenge towards conducting transparent performance comparisons between methods. To this end, we created an open-source, anonymized, metropolitan scale, and longitudinal (75 days) dataset of 100,000 individuals’ human mobility trajectories, using mobile phone location data provided by Yahoo Japan Corporation (currently renamed to LY Corporation), named YJMob100K. The location pings are spatially and temporally discretized, and the metropolitan area is undisclosed to protect users’ privacy. The 90-day period is composed of 75 days of business-as-usual and 15 days during an emergency, to test human mobility predictability during both normal and anomalous situations.

Future smart cities are expected to provide intelligent services such as predictions, detections, and automation through digital twins. However, the creation of digital twins requires the processing of an enormous amount of data, thereby leading to an increase in mobile network traffic. This traffic is produced by applications in user devices and city services, which engage in local consumption at the city scale through sensor and camera devices using mobile networks. Such increased traffic can compromise the communication speed and stability. To alleviate this burden, traffic offloading becomes a crucial consideration in the beyond-5G era. This paper presents a scheme known as Area-Controlled Mobile Ad-Hoc Networking (AMoND). AMoND uses a hierarchical structure of a location layer and an ad-hoc layer to construct area-controlled mobile ad-hoc networks (MANETs) for mutual support of the digital twin and MANETs. AMoND effectively suppresses mobile network traffic by harnessing the digital twin to assist the MANETs during data collection for the digital twin construction. Importantly, the digital twin used in AMoND focuses on the management of node location information and does not need to reproduce the real space on a computer fully. AMoND is not dependent on a specific MANET protocol and can be used as an add-on. AMoND exhibits the ability to reduce traffic volumes by up to approximately 65%, while maintaining arrival rates that are comparable to existing MANET protocols under certain conditions.

In this paper, we propose a novel buffer-state-based relaying selection scheme in the context of cooperative cognitive radio networks (CRNs), supporting the primary and secondary networks. In the proposed scheme, both the effects of inter-network interference and fading are successfully suppressed by introducing a flexible link selection algorithm in the secondary network. More specifically, by relying on the broadcast nature of wireless communication channels between a source node and relay nodes in the secondary network, the associated source packet is shared among multiple relay nodes. This allows us to benefit from the additional degree of freedom. Furthermore, we consider the priority for link selection based on the buffer state of each relay node in the secondary network. This contributes to the avoidance of detrimental empty and full buffer states. Moreover, analytical bounds of the outage probability and the average packet delay are derived for the proposed scheme based on the Markov chain model, in order to verify the numerical results. The overhead required for a central coordinator of the secondary network to monitor channel state information and buffer states are also investigated. Our numerical results demonstrate that the proposed scheme achieves better outage and packet-delay performance than the conventional max-ratio-based scheme in the buffer-aided CRN.

It is a significant challenge for telecommunication network operators to immediately restore communication services in the disaster area. To quickly recover telecommunication services in the affected area, this paper proposes a wired and wireless network cooperation system. When the wired communication for leaf nodes of optical tree networks is disrupted, surviving leaf nodes relay packets to and from these nodes via wireless bypass routes. The advantages of the proposed method are promptness and high-throughput, which is achieved with single-hop wireless bypass routes backhauled by wired networks. The optimal routes for wireless links are calculated to maximize the expected throughput by solving a binary integer programming problem. The proposed system is cost effective, because it can be deployed with minimum additional functions for leaf nodes of optical networks. To overcome the limitation of the proposed approach that the distribution of leaf nodes is determined by the demand distribution, additional recovery nodes can be deployed to improve the expected throughput. The numerical simulations including a medium access control level simulation conducting carrier sense multiple access with collision avoidance behavior showed that the proposed method can achieve a higher throughput than an existing bypass routing method, irrespective of the topology of the wired networks.

The concept of moving cell in cellular systems has been discussed for 5G group mobility where rapidly moving platforms such as trains carry a large number of user terminals. It has been considered to employ wireless backhaul for moving cell, the problem of which is its limited and unstable bandwidth. To realize high bandwidth with wireless backhaul, a large number of base stations (BSs) are required along the railway. Therefore, this paper proposes the concept of optically backhauled moving network (OBMN) for local trains to efficiently provide backhaul links for local trains. In the OBMN, an autonomous BS (ABS) is set on the top of a train and is connected to a gateway via optical backhaul. While the user terminals onboard move, the ABS set on the train always satisfies the moving demands through high-bandwidth optical backhaul. The effectiveness of the proposed architecture and scheduling was confirmed by examining two case studies in the suburban and urban areas in Tokyo. The number of required BSs and deployment cost are reduced by half with the proposed OBMN compared with the existing static deployment.

We propose an animal-to-animal data sharing mechanism that employs wildlife-borne sensing devices to expand the size of monitoring areas in which electricity, information, and road infrastructures are either limited or nonexistent. With the proposed approach, monitoring information can be collected from remote areas in a safe and cost-effective manner. To substantially prolong the life of a sensor node, the proposed mechanism activates the communication capabilities only when there is a plurality of animals; otherwise, the sensor node remains in a sleep state. This study aimed to achieve three objectives. First, we intend to obtain knowledge based on the actual field operations within the Fukushima exclusion zone. Second, we attempt to realize an objective evaluation of the power supply and work base that is required to properly evaluate the proposed mechanism. Third, we intend to acquire data to support wildlife research, which is the objective of both our present (and future) research.

Ring aggregation networks are often employed by network carriers because of their efficiency and high fault tolerance. A fairness scheme is required in ring aggregation to achieve per-flow throughput fairness and bufferbloat avoidance, because frames are forwarded along multiple ring nodes. N Rate N + 1 Color Marking (NRN + 1CM) was proposed to achieve fairness in ring aggregation networks consisting of Layer-2 Switches (SWs). With NRN + 1CM, frames are selectively discarded based on color and the frame-dropping threshold. To avoid the accumulation of a queuing delay, frames are discarded at upstream nodes in advance through the notification process for the frame-dropping threshold. However, in the previous works, NRN + 1CM was assumed to be employed in a logical daisy chain topology linked to one Edge Router (ER). The currently available threshold notification process of NRN + 1CM cannot be employed for ring networks with multiple ERs. Therefore, this paper proposes a method for applying NRN + 1CM to a ring aggregation network with multiple ERs. With the proposed algorithm, an SW dynamically selects the dropping threshold to send in order to avoid excess frame discarding. The performance of the proposed scheme was confirmed through computer simulations.

Underwater communication is a very challenging topic. Protocols used in terrestrial sensor networks cannot be directly applied in the underwater world. High-bit error rate and large propagation delay make the design of transport protocols especially awkward. ARQ-based reliable transport schemes are not appropriate in underwater environments due to large propagation delay, low communication bandwidth, and high error probability. Thus, we focus on redundancy-based transport schemes in this paper. We first investigate three schemes that employ redundancy mechanisms at the bit and/or packet level to increase the reliability in a direct link scenario. Then, we show that the broadcast property of the underwater channel allows us to extend those schemes to a case with node cooperative communication. Based on our analysis, an adaptive redundancy transport protocol (ARRTP) for underwater sensor networks is proposed. We suggest an architecture for implementation. For two kinds of topologies, namely, regular and random, we show that ARRTP presents a better transmission success probability and energy efficiency tradeoff for single- and multihop transmissions. We also offer an integrated case study to show that ARRTP is not only supplying reliability but also has some positive effect in guiding the deployment of underwater sensor nodes.