Abstract
The space-air-ground (SAG) network boosts the application for the imperfect ground infrastructure in Internet of remote things (IoRT) networks. Considering the limited battery life of IoRT devices and the difficulty of replacement, unmanned aerial vehicle (UAV) is deployed in SAG networks to assist wireless power transmission (WPT) in order to achieve sustainable device operation and enhanced computational capability. In this article, a three-layer SAG network is proposed to serve IoRT devices. Given the intricate and unpredictable environment of the IoRT SAG network, the tasks need to be timely processed by the IoRT devices without prior knowledge, which remains an ongoing challenge on available resources management. Thus, an online resource scheduling scheme that jointly optimizes CPU cycle frequency, power control and UAV trajectory planning is developed. We aim to maximize the long-term time-averaged total system computation rate while satisfying network stability and sustainability. The studied problem is a nonlinear stochastic optimization problem, which is decoupled into three sub-problems by leveraging Lyapunov optimization. Furthermore, we propose an online algorithm, namely JCPUI, to obtain the optimal CPU cycle frequency, power control, and UAV trajectory planning. Besides, performance analysis is provided for the proposed JCPUI, which elaborates that the control parameter V affects the trade-off of the total system computation rate and system stability. Simulation results validate the theoretical analysis and demonstrate the effectiveness of JCPUI.
Highlights
W ITH the increasing demands of network, 5th generation (5G) mobile networks must provide traditional operators with flexible and elastic network services, and meet the needs of various vertical industries [1]
The system performance obtained by the proposed JCPUI algorithm significantly outperforms other baseline schemes under certain circumstances
Under the partial computing offloading mode, the computing tasks of each Internet of remote things (IoRT) device can be divided into local computing and offloading to the unmanned aerial vehicle (UAV) and the low earth orbit (LEO)
Summary
W ITH the increasing demands of network, 5th generation (5G) mobile networks must provide traditional operators with flexible and elastic network services, and meet the needs of various vertical industries [1]. We propose an online algorithm that jointly optimizes CPU cycle frequency, power control, and UAV trajectory planning to maximize the long-term total system computation rate while ensuring the stability and sustainable development of the system network. The studied IoRT network is faced with the challenge of time and space constraints as well as the various service requirements To this end, we propose a wireless powered SAG IoRT network architecture, where the UAV enables edge computing, and the satellite provides realtime online cloud computing to provide seamless IoRT services. In order to maximize the computing performance of the longterm network system, a stochastic resource management scheme that jointly optimizes CPU cycle frequency, power control, and UAV trajectory planning is proposed. We proposed a joint CPU cycle frequency, power control and UAV trajectory planning stochastic resource management scheme, named JCPUI, in an online way to effectively optimize the total system computation rate.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
