Kyung Hee University · Medicine
Professor Nway Nway's research lab specializes in integrated space-air-ground communication and computing systems, focusing on energy-efficient resource allocation, task offloading, and network optimization in beyond-5G and integrated networks. The lab explores multi-access edge computing (MEC) with unmanned aerial vehicles (UAVs) and low Earth orbit (LEO) satellites, aiming to minimize delay and energy consumption for IoT and mobile devices. Key research directions include UAV trajectory and altitude optimization, interference management, and joint computation and communication resource allocation in hybrid terrestrial and non-terrestrial networks.
Figures are computed from collected data and may differ slightly.
Unmanned aerial vehicle (UAV)-assisted multi-access edge computing (MEC) has become one promising solution for energy-constrained devices to run the applications with high computation demand and stringent delay requirement in beyond 5G era. In this work, we study a multi-UAV-assisted two-stage MEC system in which UAVs provide the computing and relaying services to the mobile devices. Due to the limited computing resources, each UAV executes only a portion of the offloaded tasks from its associat
In this paper, we study an energy-efficient multi- UAV-assisted multi-access edge computing (MEC) system in which unmanned aerial vehicles (UAVs) equipped with MEC servers offer computing services to the mobile devices. In particular, the mobile devices offload a portion of their computationintensive and delay-sensitive tasks to the UAVs to minimize local computing energy consumption. However, the coupling constraints of limited energy budget at UAVs and task completion deadlines make it difficu
In this paper, the total transmit power of Unmanned Aerial Vehicles (UAVs) which are deployed as aerial base stations is minimized by adjusting the altitudes of different UAVs. We assume that the UAVs adopt the frequency division multiple access (FDMA) technique to serve ground users that are distributed in a certain geographical area. For the given two-dimensional locations of UAVs and the distribution of ground users, we find the optimal altitude of each UAV so that it covers all the ground us
Space-aerial-assisted multi-access edge computing (SA-MEC) has recently been a promising solution to offer the ubiquitous communication and computing services to the resource-constrained internet of things (IoT) devices. Particularly, low earth orbit satellites (LEOSats) and unmanned aerial vehicles (UAVs) having the computing resources onboard assist those devices to compute their generated tasks with the minimum delay under the energy budget. However, due to the existence of inter-cell interfe
Integrating terrestrial and non-terrestrial networks has emerged as a promising paradigm to fulfill the constantly growing demand for connectivity, low transmission delay, and quality of services (QoS). This integration brings together the strengths of the reliability of terrestrial networks, broad coverage and service continuity of non-terrestrial networks like low earth orbit satellites (LEOSats), etc. In this work, we study a data service maximization problem in space-air-ground integrated ne
Integrated terrestrial-nonterrestrial networks have recently gained much attention because they can bridge the gap between the conventional terrestrial infrastructure and nonterrestrial networks. In addition to seamless connectivity, such networks can offer edge computing services to the users with real-time data processing demand. In this article, an integrated terrestrial-nonterrestrial network with multiaccess edge computing (ITNT-MEC) system is considered in which the aerial users (AUEs) sha
Low earth orbit (LEO) satellites and high altitude platforms (HAPs) have recently gained popularity due to its seamless connectivity and global coverage. The aerial network comprising high altitude platforms (HAPs) collects the generated data of the ground internet of things (IoT) devices and then transmits the aggregated data to the terrestrial data processing center via the LEO satellites. However, LEO satellites are generally orbiting with high speed and their visibility times are limited acc
Cannabis is the most commonly used additive drug after alcohol and tobacco. There has been literature proving the relationship between cannabis use and elevated troponin from myocardial infarction, with many mechanisms explaining them. However, limited data are available on elevated troponin due to cannabis-induced high myocardial oxygen demand due to vasospasm. We present a case of a 21-year-old female presenting with chest pain after cannabis abuse. She exhibited a steep rise in troponin with
Due to the COVID-19 epidemic, every country announced the lockdown, travel restrictions, social distancing, curfew and stop gathering the people to prevent the spreading virus. The national government of Myanmar announced this policy in the month start of April 2020. Because of that policy, all of the business industry has to change its operation method. This study aims to know about the impact and challenges of work from home or anywhere and this method can be adapted in the hospitality industr
This paper investigates a novel network architecture – the 6G integrated terrestrial-non-terrestrial network (ITNTN) with multi-access edge computing (ITNT-MEC). This system aims to bridge the connectivity gap between terrestrial infrastructure and non-terrestrial networks while offering real-time data processing through edge computing. We consider a scenario where aerial user equipments (AUEs) share resources of terrestrial base stations (TBSs) with terrestrial UEs (TUEs). We formulate an optim
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