Abstract
With the emergence of computation-intensive and delay-sensitive applications, such as face recognition, virtual reality, augmented reality, and Internet of Things (IoT) devices; Mobile Edge Computing (MEC) allows the IoT devices to offload their heavy computation tasks to nearby edge cloud network rather than to compute the tasks locally. Therefore, it helps to reduce the energy consumption and execution delay in the ground mobile users. Flying Unmanned Aerial Vehicles (UAVs) integrated with the MEC server play a key role in 5G and future wireless communication networks to provide spatial coverage and further computational services to the small, battery-powered and energy-constrained devices. The UAV-enabled MEC (U-MEC) system has flexible mobility and more computational capability compared to the terrestrial MEC network. They support line-of-sight (LoS) links with the users offloading their tasks to the UAVs. Hence, users can transmit more data without interference by mitigating small-scale fading and shadowing effects. UAVs resources and flight time are very limited due to size, weight, and power (SWaP) constraints. Therefore, energy-aware communication and computation resources are allocated in order to minimize energy consumption.In this paper, a brief survey on U-MEC networks is presented. It includes the brief introduction regarding UAVs and MEC technology. The basic terminologies and architectures used in U-MEC networks are also defined. Moreover, mobile edge computation offloading working, different access schemes used during computation offloading technique are explained. Resources that are needed to be optimized in U-MEC systems are depicted with different optimization problem, and solution types. Furthermore, to guide future work in this area of research, future research directions are outlined. At the end, challenges and open issues in this domain are also summarized.
Highlights
I NTERNET of Things (IoT) devices are characterized as resource-constrained devices due to the limited storage, computational, and energy resources as they haveVOLUME 4, 2016 small physical size
Unmanned Aerial Vehicles (UAVs)-enabled Mobile Edge Computing (MEC) system is an ineluctable trend in future wireless communications and is useful in 5G and beyond wireless communication. It is a contemporary concept of using UAVs as moving MEC servers, i.e., cellular base stations (BSs) or Wi-Fi access points, to improve the computation performance of mobile devices like latency, network congestion, energy efficiency, and quality of IoT services
UAV operates as a relay, which assists the users to offload their heavy computation tasks to the GBSs integrated with the MEC server
Summary
I NTERNET of Things (IoT) devices (for example, smart mobile devices, smart home appliances, sensors, monitoring devices, etc.) are characterized as resource-constrained devices due to the limited storage, computational, and energy resources as they have. IoT devices are used for computation-intensive applications like augmented reality (AR), virtual reality (VR), pattern recognition, monitoring, etc [1]. The aforementioned heavy tasks on-board eventually results in more energy consumption making the devices slow and latency prone. Muhammad Abrar et al.: Energy Efficient UAV-Enabled Mobile Edge Computing for IoT Devices: A Review. One of the main challenges is resource allocation (energy consumption minimization, computation efficiency maximization, computation bits maximization, cost minimization, completion time minimization, and etc.). The number of applications and volume of mobile traffic in IoT devices is increasing [2]
Sign-in/Register to view highlights & summary 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 callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
