Haneul Ko

Recently, there has been an increasing interest in operating long-term evolution (LTE) in unlicensed bands (i.e., LTE-U). However, since LTE and wireless local area networks (WLANs) are designed to operate in different bands, they have no coexistence mechanism, which leads to significant performance degradation. In particular, since LTE does not sense channel vacancy prior to transmissions, the LTE interference severely affects the WLAN operation. To address this problem, we propose a fair liste

In a vehicle-to-grid (V2G) system, electric vehicles (EVs) can be efficiently used as power consumers and suppliers to achieve microgrid (MG) autonomy. Since EVs can act as energy transporters among different regions (i.e., MGs), it is an important issue to decide where and when EVs are charged or discharged to achieve the optimal performance in a V2G system. In this paper, we propose a mobility-aware V2G control algorithm (MACA) that considers the mobility of EVs, states of charge of EVs, and t

A novel concept of the edge cloud has recently been introduced to reduce transmission costs in mobile cloud computing services. Heterogeneous networks with diverse radio access networks will be pervasive in the future. In this paper, we propose a spatial and temporal computation offloading decision algorithm (ST-CODA) in edge cloud-enabled heterogeneous networks. In ST-CODA, a mobile device decides where and when to process tasks by means of a Markov decision process with the consideration of th

In federated learning (FL), if the participating mobile devices have low computing power and poor wireless channel conditions and/or they do not have sufficient data for various classes, a long convergence time is required to achieve the desired model accuracy. To address this problem, we first formulate a constrained Markov decision process (CMDP) problem that aims to minimize the average time of rounds while maintaining the numbers of trained data and trained data classes above certain numbers

In battery swapping environments, electric vehicles (EVs) can play roles as battery providers as well as consumers. In this paper, we propose an optimal battery charging algorithm (OBCA) where a battery swapping station (BSS) charges batteries in its storage with the consideration of the profile of the electricity price and the arrival rates of EVs. To maximize the net profit of BSS while maintaining the battery changing probability above a certain level (i.e., maintaining high quality of servic

Serverless architecture enables various intelligent applications to be run without managing infrastructure. In this architecture, the computing cost is generally proportional to the number of requested stateless functions and this number can affect the task completion time and, thus, it is prominent to decide an appropriate number of requested stateless functions. In this article, we propose a latency-guaranteed and energy-efficient task offloading (LETO) system where an Internet of Things (IoT)

In task offloading systems, it is imperative to guarantee that an offloaded task is completed within a pre-specified deadline. In this paper, we propose a distributed device-to-device (D2D) offloading system (DDOS) in which a task owner opportunistically broadcasts an offloading request that includes its mobility level and task completion deadline. After receiving the request, mobile devices in the vicinity of the task owner employ a constraint stochastic game to decide, in a distributed manner,

In mobile crowdsensing (MCS), a participant selection strategy should be carefully designed to guarantee sufficient coverage and avoid unnecessary energy consumption. In this paper, we propose a coverage-guaranteed and energy-efficient participant selection (CG-EEPS) strategy, in which the MCS server determines participants based on the data usage profile and mobility level of mobile devices. In addition, CG-EEPS adopts a piggyback approach of sensory data for energy-efficient transmissions. To

In environmental monitoring systems, unnecessary transmissions can occur when an Internet of Things (IoT) device transmits its data without any consideration on neighbors' transmissions. In this paper, we propose a neighbor-aware energy-efficient monitoring system (NA-EEMS) for energy harvesting IoT devices. In NA-EEMS, to exploit spatial correlation among IoT devices, geographically proximate IoT devices transmit their sensed data in a distributed manner by means of a constraint stochastic game

Recently, the interest in operating long term evolution (LTE) in unlicensed bands (i.e., LTE-U) has increased. However, since LTE does not sense for channel vacancy prior to transmissions, whereas a wireless local area network (WLAN) is based on carrier sensing multiple access, LTE interference severely degrades the performance of WLAN. To maximize the LTE throughput while maintaining fairness between LTE and WLAN, we formulate a joint optimization problem of channel selection and frame scheduli

In the delayed WiFi offloading, since data are downloaded only through WiFi networks before a predefined delay timer expires, the performance of the delayed WiFi offloading is affected by the delay timer value. To assess the performance of the delayed WiFi offloading, we develop analytical models for the expected saving monetary cost and download completion time. Based on these analytical models, the optimal delay timer is derived to maximally save the monetary cost while maintaining the outage

To provide an accurate environmental map (EM) while avoiding unnecessary transmissions of Internet of Things (IoT) devices, we propose a spatiotemporal correlation-based environmental monitoring system (ST-EMS). In ST-EMS, IoT devices decide whether to transmit the sensed data to an IoT gateway (GW) or not by considering the temporal correlation in the sensed data and energy level. Through a Markov decision process (MDP) formulation, the optimal policy is obtained and it is proved that the optim

The computation offloading, where Internet of Things (IoT) devices transfers their task to an external cloud, has several advantages such as low energy consumption of IoT devices and fast response time. To maximize these advantages, IoT devices can exploit the nearest edge cloud. However, frequent offloadings to the nearest edge cloud can cause a location privacy vulnerability due to the proximity of the edge cloud from IoT devices, which is a critical issue in smart city IoT applications. To ad

Long-term evolution (LTE)/LTE-advanced (LTE-A) networks have recently introduced a data packet forwarding scheme between evolved node Bs (eNBs) to reduce the signaling overhead and the delay incurred in the data path switching scheme, which is a baseline handover scheme in LTE/LTE-A networks. Even with the data packet forwarding scheme, if the length of the forwarding chain is set inappropriately, the data packet forwarding scheme suffers from the degraded throughput. To attain the optimal hando