Dao Nhu Ngoc
  Junwook Lee
   The growth in IoT is explosive, impressive-and unsustainable under current architectural approaches. Many IoT deployments face challenges related to latency, network bandwidth, reliability and security, which cannot be addressed in cloud-only models. Fog computing adds a hierarchy of elements between the cloud and endpoint devices, and between devices and gateways, to meet these challenges in a high performance, open and interoperable way. Fog networking consists of a control plane and a data plane. For example, on the data plane, fog computing enables computing services to reside at the edge of the network as opposed to servers in a data-center. Compared to cloud computing, fog computing emphasizes proximity to end-users and client objectives, dense geographical distribution and local resource pooling, latency reduction for quality of service (QoS) and edge analytics/stream mining, resulting in superior user-experience[5] and redundancy in case of failure. Fog networking supports the Internet of Things (IoT) concept, in which most of the devices used by humans on a daily basis will be connected to each other. Examples include phones, wearable health monitoring devices, connected vehicle and augmented reality using devices such as the Google Glass.
빅데이터/IoT 시대를 위한 mmWave 대역 무선 포그 네트워크 자원관리 핵심 기술 연구 (Research on Resource Management of mmWave based Fog Radio Access Network for Big Data/IoT) , NRF, 2017.4.01~2020.3.30
엣지 클라우드와 인터넷 클라우드 연동 지원 할당 최적화 기법 연구(A Study on the Optimization for Edge Cloud and Internet Cloud Interworking) , ETRI, 2017.03.01~2017.11.30
이준욱, 나웅수, 엄재현, 박경준, 김남규, 정서현, 조성래 "포그 컴퓨팅 : 컨셉, 역할(A Survey of Fog Computing: Concepts, Role)," 한국통신학회 하계학술종합발표회, 제주도, June 2016.