Year: 2020
Type: article
Abstract: The advent of the Internet-of-Things (IoT) has led to a rapid growth in data generation. The amount of computation resources required to process the massive data generated by IoT devices, along with the new intelligent use and applications of IoT data such as smart city that can be computation intensive and delay sensitive, have caused an increase in demand for locally available resources at network edge for computation offloading. To address this issue, we have proposed the concept of opportunistic fog radio access network (OF-RAN), which extends the computation capacity of existing fog-RAN (F-RAN) by establishing virtual fog access points (v-FAP) opportunistically using resourceful user devices that participate as service nodes. In this article, we develop an analytical model to evaluate the offloading performance of three RAN architectures: the traditional cloud radio access network (C-RAN), the existing F-RAN, and the proposed OF-RAN. The performances are analyzed in terms of their energy consumption, completion delay, and failure rate, under the effect of varying scenarios.
Source: IEEE Access
Institution: Auckland University of Technology
Language: English
Topic: IoT and Edge/Fog Computing
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,750
OpenAlex ID: W3110763574