Effective Mobility Identification in Mobile Fog Environment with the Internet of Things

Effective Mobility Identification in Mobile Fog Environment with the Internet of Things

Mobility

Location

Migration

Fog nodes

IoT

Fog extends the cloud to be closer to the end devices so that it acts on IoT data within a millisecond. Almost 60% of data can be analyzed that is physically near to the IoT data. This proximity has various advantages, including reduced latency, which improves the user experience. However, because the distance to a fog service may vary as a user moves from one location to another, user mobility may restrict such benefits in practice. A fog service migration is based on a mitigation approach that allows the service to always be close enough to a user. Quality of Service is decreased because of the mobility of the user’s location.   Predicting the future location in advance improves the efficiency of service provisioning. In this work, a dynamic mobility model is proposed to find the user location in advance. This experiment was carried out by LuST mobility data set collected by Luxembourg Simulation of Urban Mobility (SUMO) Traffic (LuST). This result is give better accuracy of location prediction up to 98.87% when compared with existing methods.

D, Deepa

Jothi K R

International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 15 (2022); pp. 157-171

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2022-08-17

Copyright (c) 2022 Jothi K R, Deepa

https://creativecommons.org/licenses/by/4.0

application/pdf

eng

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion

Peer-reviewed Article