UAV‐IoT collaboration: Energy and time‐saving task scheduling scheme

Abstract

SummaryUAVs are capable of providing significant potential to IoT devices through sensors, cameras, GPS systems, and so forth. Therefore, the smart UAV‐IoT collaborative system has become a current hot research topic. However, other concerns require in‐depth investigation and study, such as resource allocation, security, privacy preservation, trajectory optimization, intelligent decision‐making, energy harvesting, and so forth. Here, we suggest a task‐scheduling method that splits IoT devices into distinct clusters based on physical proximity and saves time and energy. Cluster heads can apply an auto regressive moving average (ARMA) model to predict intelligently the timestamp of the arrival of the next task and associated estimated payments. Based on the overall expected payment, a cluster head can smartly advise the UAV about its time of next arrival. According to the findings of the simulation, the proposed ETTS algorithm significantly outperforms Task TSIE and TDMA‐WS in terms of energy use (67%) and delays (36%).

Multi‐UAV path planning utilizing the PGA algorithm for terrestrial IoT sensor network under ISAC framework

“…The Dijkstra algorithm 8 specializes in determining the shortest path through graph nodes. As one of the most widely adopted search algorithms for route planning, the search algorithm 9 bolsters performance by integrating heuristics to navigate the search process, particularly in two-dimensional scenarios. Recent progress has expanded the utility of these techniques to encompass three-dimensional (3D) geographical environments.…”

“…The ETTS algorithm is proposed for UAV task scheduling, with an emphasis on efficient energy utilization and reduced latency in IoT systems via clustering, ARMA model predictions, and multi-objective optimization. 9 This technique is proposed for optimizing job scheduling for UAVs in IoT systems, with a focus on energy efficiency and minimizing delays. Investigates the revolutionary influence of UAVs and the IoT, offering green UAV-based fog computing for energy-efficient data computation and communication in crucial applications.…”

Customized Millimeter Wave Channel Model for Enhancement of Next-Generation UAV-Aided Internet of Things Networks

“…Advanced optimization techniques, such as genetic algorithms, have been suggested to enhance energy efficiency by controlling the UAV trajectory [ 16 ]. The role of UAVs in IoTs exceeds the communication part to include a computational enhancement by enabling mobile edge computing to offload tasks from IoT devices and optimize the management of energy and time resources [ 17 , 18 ]. Non-orthogonal multiple access (NOMA) techniques, along with UAV networks, have been proposed for ultra-reliable low-latency communication (URLLC) applications [ 9 ].…”

UAV-Based Secure Data Communication: Multilevel Authentication Perspective

“…UAV technology has a wide range of applications, including film-making, animal monitoring, infrastructure inspection, agriculture, airspace control, exploration, and conservation. UAVs are also being utilized in global logistics for on-demand delivery and long-distance transportation [6]. The Internet of UAVs (IoUAV) is a network that connects unmanned aerial vehicles used for complex missions.…”