Decentralized and Revised Content-Centric Networking-Based Service Deployment and Discovery Platform in Mobile Edge Computing for IoT Devices
- Authors
- Tien-Dung Nguyen; Huh, Eui-Nam; Jo, Minho
- Issue Date
- 6월-2019
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Cloud; fog; Internet of Things (IoT); mobile edge computing (MEC); offloading; service deployment; service discovery
- Citation
- IEEE INTERNET OF THINGS JOURNAL, v.6, no.3, pp.4162 - 4175
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE INTERNET OF THINGS JOURNAL
- Volume
- 6
- Number
- 3
- Start Page
- 4162
- End Page
- 4175
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/65298
- DOI
- 10.1109/JIOT.2018.2875489
- ISSN
- 2327-4662
- Abstract
- Mobile edge computing (MEC) is used to offload services (tasks) from cloud computing in order to deliver those services to mobile Internet of Things (IoT) devices near mobile edge nodes. However, even though there are advantages to MEC, we face many significant problems, such as how a service provider (SP) deploys requested services efficiently on a destination MEC node, and how to discover existing services in neighboring MEC nodes to save edge resources. In this paper, we present a decentralized and revised content-centric networking (CCN)-based MEC service deployment/discovery protocol and platform. We organized a gateway in every area according to a three-tiered hierarchical MEC network topology to reduce computing overhead at the centralized controller. We revised CCN to introduce a protocol to help SP deploy their service on MEC node and assist MEC node discover services in neighboring nodes. By using our proposed protocol, MEC nodes can deploy or discover the requested service instances in the proximity of IoT devices to reduce transmission delay. We also present a mathematical model to calculate the round trip time to guarantee quality of service. Numerical experiments measure the performance of our proposed method with various mobile ha device services. The results show that the proposed service deployment protocol and platform reduce the average service delay by up to 50% compared to legacy cloud. In addition, the proposed method outperforms the legacy protocol of the MEC environment in service discovery time.
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Collections - Graduate School > Department of Computer and Information Science > 1. Journal Articles
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