Rights statement: This is the peer reviewed version of the following article: Khan, OA, Malik, SUR, Baig, FM, et al. A cache-based approach toward improved scheduling in fog computing. Softw: Pract Exper. 2021; 51: 2360– 2372. https://doi.org/10.1002/spe.2824 which has been published in final form at https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2824 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
Accepted author manuscript, 1.19 MB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - A cache-based approach toward improved scheduling in fog computing
AU - Khan, O.A.
AU - Malik, S.U.R.
AU - Baig, F.M.
AU - Islam, S.U.
AU - Pervaiz, H.
AU - Malik, H.
AU - Ahmed, S.H.
N1 - This is the peer reviewed version of the following article: Khan, OA, Malik, SUR, Baig, FM, et al. A cache-based approach toward improved scheduling in fog computing. Softw: Pract Exper. 2021; 51: 2360– 2372. https://doi.org/10.1002/spe.2824 which has been published in final form at https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2824 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
PY - 2021/12/31
Y1 - 2021/12/31
N2 - Fog computing is a promising technique to reduce the latency and power consumption issues of the Internet of Things (IoT) ecosystem by enabling storage and computational resource close to the end-user devices with additional benefits such as improved execution time and processing. However, with an increase in IoT devices, the resource allocation and job scheduling became a complicated and cumbersome task due to limited and heterogeneous resources along with the locality restriction in such computing environment. Therefore, this paper proposes a cache-based approach for efficient resource allocation in fog computing environment, while maintaining the quality of service. The proposed algorithm is realized using iFogSim simulator and a comprehensive comparison is presented with the traditional First Come First Served and Shortest Job First policies. The performance evaluation revealed that with the proposed scheme the execution time, latency, processing delays and power consumption decreased by 38%, 11.1%, 6%, and 17.8%, respectively, as compared to those of the traditional schemes.
AB - Fog computing is a promising technique to reduce the latency and power consumption issues of the Internet of Things (IoT) ecosystem by enabling storage and computational resource close to the end-user devices with additional benefits such as improved execution time and processing. However, with an increase in IoT devices, the resource allocation and job scheduling became a complicated and cumbersome task due to limited and heterogeneous resources along with the locality restriction in such computing environment. Therefore, this paper proposes a cache-based approach for efficient resource allocation in fog computing environment, while maintaining the quality of service. The proposed algorithm is realized using iFogSim simulator and a comprehensive comparison is presented with the traditional First Come First Served and Shortest Job First policies. The performance evaluation revealed that with the proposed scheme the execution time, latency, processing delays and power consumption decreased by 38%, 11.1%, 6%, and 17.8%, respectively, as compared to those of the traditional schemes.
KW - cache
KW - cloud computing
KW - fog computing
KW - IoT
KW - job scheduling
KW - QoE
KW - QoS
KW - Electric power utilization
KW - Fog
KW - Green computing
KW - Internet of things
KW - Quality of service
KW - Resource allocation
KW - Scheduling
KW - Comprehensive comparisons
KW - Computational resources
KW - Computing environments
KW - Efficient resource allocation
KW - First come first served
KW - Heterogeneous resources
KW - Internet of thing (IOT)
KW - Processing delay
KW - Fog computing
U2 - 10.1002/spe.2824
DO - 10.1002/spe.2824
M3 - Journal article
VL - 51
SP - 2360
EP - 2372
JO - Software: Practice and Experience
JF - Software: Practice and Experience
SN - 0038-0644
IS - 12
ER -