As many industrial applications require real-time and reliability communication, a variety of routing graph construction schemes were proposed to satisfy the requirements in Industrial Wireless Sensor Networks (IWSNs). Each device transmits packet through a route which is designated based on the graph. However, as existing studies consider a network consists of static devices only, they cannot cope with the network changes by movement of mobile devices considered important in the recent industrial environment. Thus, the communication requirements cannot be guaranteed because the existing path is broken by the varying network topology. The communication failure could cause critical problems such as malfunctioning equipment. The problem is caused repeatedly by continuous movement of mobile devices, even if a new graph is reconstructed for responding the changed topology. To support mobile devices exploited in various industrial environments, we propose a Hierarchical Routing Graph Construction (HRGC). The HRGC is consisted of two phases for hierarchical graph construction: In first phase, a robust graph called skeleton graph consisting only of static devices is constructed. The skeleton graph is not affected by network topology changes and does not suffer from packet loss. In second phase, the mobile devices are grafted into the skeleton graph for seamless communication. Through the grafting process, the routes are established in advance for mobile device to communicate with nearby static devices in anywhere. The simulation results show that the packet delivery ratio is improved when the graph is constructed through the HRGC.

Internet of Things (IoT) is gaining great momentum for remote data collection in various smart applications. Recently, the proliferation of wireless sensors and the explosive increase in the number of mobile devices enable Mobile-Assisted Sensing (MAS) in which the mobile gateways collect data from the distributed sensors. Therefore, MAS collects data without additional overheads for building a static network infrastructure. Meanwhile, the connection between a sensor and a mobile gateway is generally considered unreliable due to the arbitrary mobility of mobile gateways. That is, the connection is unexpectedly terminated when the mobile gateway leaves the communication range of the sensor. Therefore, the existing studies have used frequent control messages for suppressing invalid data transmission after the end of the connection. Thus, the conservative flow control degrades data throughput because the control messages occupy a large part of the connection. However, the connection can be reliable according to the condition of the mobile gateway. In this paper, an adaptive flow control (AFC) scheme is proposed for enhancing data throughput using the movement information of mobile gateways. AFC exploits the movement information for estimating the reliability of the connection. Estimating that the connection is reliable, the control messages are hardly emitted during data transmission thereby the connection contains more data. Consequently, AFC enhances the data throughput by reducing control overheads without degrading reliability.

Mobile Cyber-Physical Systems (MCPS) have extended the application domains by exploiting the advantages of Cyber-Physical Systems (CPS) through the mobile devices. The cooperation of various mobile equipment and workers based on the MCPS further improved efficiency and productivity in the industry. To support this cooperation of groups of workers (hereafter referred to as the Mobile Sink Groups), data should be delivered to appropriate groups of workers in a timely manner. Traditionally, the data dissemination for MSG relies on flooding-based geocasting into the movable area of the group due to frequent movements of each group member. However, the flooding-based data dissemination could not be directly applied to real-time data delivery that demands the required time deadline and the end-to-end delivery distance, because the flooding could not define the end-to-end distance and progress to each member in a group. This paper proposes a real-time data delivery mechanism for supporting MSG in time-critical applications. In our mechanism, a ring-based modeling and data transfer scheme on a virtual grid in the ring for group mobility provides the end-to-end distance and the progress to forward real-time data to each member. Simulation results show our mechanism is superior to the existing ones in terms of real-time communication for MSG.

Industrial IoT (IIoT) is key to achieving automation in manufacturing and logistics industries. Recently, there have been ongoing efforts to realize automation by deploying mobile devices such as Automated Guided Vehicles (AGVs) in industrial processes, along with sensors and actuators. Industrial Wireless Sensor Networks (IWSN) are essential foundational technologies for implementing IIoT, providing communication methods based on redundancy policies, such as scheduling with pre-designed multiple routing paths and fixed redundant resource allocation, to meet strict industrial requirements like real-time, reliability, and energy efficiency. However, existing IWSNs are vulnerable to frequent location changes of equipment such as AGVs and variations in network environments. Especially, the waste of redundant resources that are not utilized for communication leads to issues of resource efficiency and scalability limitations due to limited wireless resources. To address these challenges, this paper proposes a resource reallocation and scheduling update scheme that identifies and reallocates unutilized redundant resources by employing the Multi-Armed Bandit (MAB) algorithm - one of the representative reinforcement learning techniques focused on reward optimization - in IWSN environment where mobile and fixed devices are deployed together. This approach improves the performance of industrial networks while maintaining compatibility with existing industrial network systems, supporting reliability and real-time processing. The experimental performance evaluation shows that the proposed scheme improves network performance in terms of resource efficiency, scalability, energy efficiency, and mobility support compared to the typical resource allocation and scheduling schemes.

Multipath routing protocol, which is one of the typical schemes to improve end-to-end transmission success ratio in Wireless Sensor Networks (WSNs), exploits two or more paths. However, collisions and interference might occur when each path is adjacent. To prevent this problem, they construct node- or link-disjointed paths. Although the paths could prevent the above-mentioned problem, it still has an issue in the area of time delay. To exploit the disjointed paths, pre-path construction is required. In addition, a lot of time is incurred to recover the whole path when the part of the path is damaged. This phenomenon adversely affects the end-to-end transmission success ratio and transmission time. To alleviate this problem, we propose a cluster-disjoint multipath routing protocol. The proposed scheme divides the whole network into grid clusters of a certain size in the network initialization phase. Each sensor could transmit packets through the pre-constructed cluster structure without the path construction phase. Also, even if any node fails, it could be easily replaced by other nodes within the cluster region. The simulation results show that the proposed scheme has an advantage in terms of transmission delay and end-to-end transmission success ratio compared to existing multipath routing protocols.

Vehicular clouds are considered an attractive approach to provide various services such as safety and entertainment applications by sharing resources between vehicles. Due to the free mobility of vehicles, vehicular clouds need to reconstruct by replacing leaving member vehicles with new member vehicles. When multiple member vehicles leave a vehicular cloud at different times, the design of an efficient member vehicle replacement scheme is a very challenging issue on determining the replacement timing. However, the research on the replacement of multiple member vehicles has little interest and is still in its infancy. Therefore, we propose three schemes to replace multiple member vehicles in vehicular clouds at three different replacement timings: MIN, MAX, and AVG. The MIN scheme replaces all of leaving member vehicles at the leaving time of the first leaving member vehicle, while the MAX scheme replaces all of leaving member vehicles at the leaving time of the last leaving member. The AVG scheme replaces all leaving member vehicles at the average time of their leaving times as a compromise between the Min and Max schemes. First, we determine the first leaving time, the last leaving time, and the average leaving time for each scheme by calculating the distance between a cloud requester vehicle and its member vehicles. Next, we choose replacement member vehicles to minimize the wasted resource at the replacement timing in each scheme. Last, we provide the process for releasing the resource of the leaving member vehicles and allocating the resource of the replacement member vehicles in each scheme. Through simulation results conducted in various environments, we compare and evaluate the performance of our three schemes in terms of the success ratio of the cloud maintenance and the amount of the wasted resources.