A Lightweight Location-Aware Fog Framework (LAFF) for QoS in Internet of Things Paradigm
Joint Authors
Shiraz, Muhammad
Shaheen, Qaisar
Hashmi, Muhammad Usman
Mahmood, Danish
zhiyu, Zhu
Akhtar, Rizwan
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-16
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Telecommunications Engineering
Abstract EN
Realization of Internet of Things (IoT) has revolutionized the scope of connectivity and reachability ubiquitously.
Under the umbrella of IoT, every object which is smart enough to communicate with other object leads to the enormous data generation of varying sizes and nature.
Cloud computing (CC) employs centralized data centres for the provisioning of remote services and resources.
However, for the reason of being far away from client devices, CC has their own limitations especially for time and resource critical applications.
The remote and centralized characteristics of CC often result in creating bottle necks, being latent, and hence deteriorate the quality of service (QoS) in the provisioning of services.
Here, the concept of fog computing (FC) emerges that tends to leverage CC and end devices for data congestion and processing locally in a distributed and decentralized way.
However, addressing latency and bottleneck issues for time critical applications are still challenging.
In this work, a lightweight framework is proposed which employs the concept of fog head node that keeps track of other fog nodes in terms of user registrations and location awareness.
The proposed lightweight location-aware fog framework (LAFF) persistently satisfies QoS by providing an accurate location-aware algorithm.
A comparative analysis is also presented to analyse network usage, service time, latency, and RAM and CPU utilization.
The comparison results depicts that the LAFF reduces latency, network use, and service time by 11.01%, 7.51%, and 14.8%, respectively, in contrast to the state-of-the-art frameworks.
Moreover, considering RAM and CPU utilization, the proposed framework supersedes IFAM and TPFC targeting IoT applications.
The RAM consumption and CPU utilization are reduced by 8.41% and 16.23% as compared with IFAM and TPFC, respectively, making the framework lightweight.
Hence, the proposed LAFF improves QoS while accessing remote computational servers for the outsourced applications in fog computing.
American Psychological Association (APA)
Shaheen, Qaisar& Shiraz, Muhammad& Hashmi, Muhammad Usman& Mahmood, Danish& zhiyu, Zhu& Akhtar, Rizwan. 2020. A Lightweight Location-Aware Fog Framework (LAFF) for QoS in Internet of Things Paradigm. Mobile Information Systems،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1192562
Modern Language Association (MLA)
Shaheen, Qaisar…[et al.]. A Lightweight Location-Aware Fog Framework (LAFF) for QoS in Internet of Things Paradigm. Mobile Information Systems No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1192562
American Medical Association (AMA)
Shaheen, Qaisar& Shiraz, Muhammad& Hashmi, Muhammad Usman& Mahmood, Danish& zhiyu, Zhu& Akhtar, Rizwan. A Lightweight Location-Aware Fog Framework (LAFF) for QoS in Internet of Things Paradigm. Mobile Information Systems. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1192562
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1192562