Sungrae Cho

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Sungrae Cho is a professor with the school of computer science and engineering, Chung-Ang University (CAU), Seoul. Prior to joining CAU, he was an assistant professor with the department of computer sciences, Georgia Southern University, Statesboro, GA, USA, from 2003 to 2006, and a senior member of technical staff with the Samsung Advanced Institute of Technology (SAIT), Kiheung, South Korea, in 2003. From 1994 to 1996, he was a research staff member with electronics and telecommunications research institute (ETRI), Daejeon, South Korea. From 2012 to 2013, he held a visiting professorship with the national institute of standards and technology (NIST), Gaithersburg, MD, USA. He received the B.S. and M.S. degrees in electronics engineering from Korea University, Seoul, South Korea, in 1992 and 1994, respectively, and the Ph.D. degree in electrical and computer engineering from the Georgia Institute of Technology, Atlanta, GA, USA, in 2002.

His current research interests include wireless networking, ubiquitous computing, and ICT convergence. He was an editor of Ad Hoc Networks Journal (Elsevier) from 2012 to 2017. He has served numerous international conferences as an organizing committee chair, such as IEEE SECON, ICOIN, ICTC, ICUFN, TridentCom, and the IEEE MASS, and as a program committee member, such as IEEE ICC, MobiApps, SENSORNETS, and WINSYS.
Supervisors: Ian F. Akyildiz

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Frequency Resource Allocation and Interference Management in Mobile Edge Computing for an Internet of Things System

IEEE Internet of Things Journal, Jun 1, 2019

Internet of Things (IoT) systems are characterized by highly automated operating environments, wh... more Internet of Things (IoT) systems are characterized by highly automated operating environments, which comprise several IoT end devices (IDs) that generate vast amounts of data with strict real-time communication and high data rate requirements. Edge computing facilities are an alternative to traditional cloud computing and support massive data processing in IoT systems while reducing the burden on data centers. In this study, we consider an edge-based IoT system that comprises an Edge Server (ES), Edge Gateways (EGs), and IDs that communicate wirelessly. The EGs reduce the load on the ES by preprocessing data received from ID. However, it may not be possible for a few EGs to accommodate a sheer number of IDs, given the limited computing power and communication coverage of the EGs. Therefore, it is necessary for a few IDs to directly connect to the ES without the support of EGs. Thus, we propose a resource orchestration scheme between EGs and ES and/or among EGs based on a Lagrangian and the Karush−Kuhn−Tucker (KKT) condition. The scheme allocates optimal resources by considering the computing capacities of EGs and ES and manages interference among the EGs to maximize the efficiency of IoT systems. The performance evaluation indicates that the proposed scheme outperforms the existing schemes in terms of aggregate throughput, latency, data reception rate, and workload fairness among EGs by 42%, 59%, 37%, and 40%, respectively.

Sungrae Cho

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