In this work, we consider a UAV-assisted cell in a single user scenario. We consider the Quality of Experience (QoE) performance metric calculating it as a function of the packet loss ratio. In order to acquire this metric, a radio-channel emulation system was developed and tested under different conditions. The system consists of two independent blocks, separately emulating connections between the User Equipment (UE) and unmanned aerial vehicle (UAV) and between the UAV and Base station (BS). In order to estimate scenario usage constraints, an analytical model was developed. The results show that, in the described scenario, cell coverage can be enhanced with minimal impact on QoE.
The monitoring of underwater aquatic habitats and pipeline leakages and disaster prevention are assisted by the construction of an underwater wireless sensor network (UWSN). The deployment of underwater sensors consumes energy and causes delay when transferring the gathered sensed data via multiple hops. The consumption of energy and delays are minimized by means of an autonomous unmanned vehicle (AUV). This work addresses the idea of reducing energy and delay by incorporating an AUVs-assisted, three-dimensional UWSN (3D-UWSN) called DEDG 3D-UWSN. Energy in the sensor nodes is saved by clustering and scheduling; on the other hand, the delay is minimized by the movement of the AUV and inter-cluster routing. In clustering, multi-objective spotted hyena optimization (MO-SHO) is applied for the selection of the best sensor for the cluster head, which is responsible for assigning sleep schedules for members. According to the total number of members, an equal half of the members is provided with sleep slots based on the energy and hop counts. The redundancy in the gathered data is eliminated by measuring the Hassanat distance. Then, the moving AUV is able to predict its movement by the di-factor actor–critic path prediction method. The mid-point among the four heads is determined so that the AUV can collect data from four heads at a time. In cases where the waiting time of the CH is exceeded, three-step, inter-cluster routing is executed. The three steps are the discovery of possible routes, ignoring the longest paths and validating the filtered path with a fuzzy–LeNet method. In this 3D-UWSN, the sensed data are not always normal, and, hence, a weighted method is presented to transfer emergency events by selecting forwarders. This work is implemented on Network Simulator version 3.26 to test the results. It achieves better efficiency in terms of data collection delay, end-to-end delay, AUV tour length, network lifetime, number of alive nodes and energy consumption.
Online video services are among the most popular ways of content consumption. Video hosting servers have a very high load every day, which we propose to reduce by migrating the application with the video content in demand to the local Multi-access Edge Computing (MEC) server of the target. This makes it possible to improve the quality of services (QoS) provided to users by reducing the transmission delay. Therefore, an architecture has been proposed that allows, at times of increased demand for the same video content, to migrate the video service application to the edge servers of the network operator. To evaluate the performance of this approach, a mathematical model was developed in the form of a queuing system. The results of the numerical experiment make it possible to optimize the time of using local MEC servers to provide video content.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.