TY - JOUR
T1 - An efficient algorithm for data transmission certainty in IIoT sensing network
T2 - A priority-based approach
AU - Nalbant, Kemal Gökhan
AU - Almutairi, Sultan
AU - Alshehri, Asma Hassan
AU - Kemal, Hayle
AU - Alsuhibany, Suliman A.
AU - Choi, Bong Jun
N1 - Publisher Copyright:
Copyright: © 2024 Nalbant et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2024/7
Y1 - 2024/7
N2 - This paper proposes a novel cache replacement technique based on the notion of combining periodic popularity prediction with size caching. The popularity, size, and time updates characteristics are used to calculate the value of each cache item. When it comes to content replacement, the information with the least value is first eliminated. Simulation results show that the proposed method outperforms the current algorithms in terms of cache hit rate and delay. The hit rate of the proposed scheme is 15.3% higher than GDS, 17.3% higher than MPC, 20.1% higher than LRU, 22.3% higher than FIFO, and 24.8% higher than LFU when 350 different categories of information are present. In real-world industrial applications such as including supply chain management, smart manufacturing, automation energy optimization, intelligent logistics transportation, and e-healthcare applications, it offers a foundation for the selection of caching algorithms.
AB - This paper proposes a novel cache replacement technique based on the notion of combining periodic popularity prediction with size caching. The popularity, size, and time updates characteristics are used to calculate the value of each cache item. When it comes to content replacement, the information with the least value is first eliminated. Simulation results show that the proposed method outperforms the current algorithms in terms of cache hit rate and delay. The hit rate of the proposed scheme is 15.3% higher than GDS, 17.3% higher than MPC, 20.1% higher than LRU, 22.3% higher than FIFO, and 24.8% higher than LFU when 350 different categories of information are present. In real-world industrial applications such as including supply chain management, smart manufacturing, automation energy optimization, intelligent logistics transportation, and e-healthcare applications, it offers a foundation for the selection of caching algorithms.
UR - http://www.scopus.com/inward/record.url?scp=85198901081&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0305092
DO - 10.1371/journal.pone.0305092
M3 - Article
C2 - 39018273
AN - SCOPUS:85198901081
SN - 1932-6203
VL - 19
JO - PLoS ONE
JF - PLoS ONE
IS - 7 July
M1 - e0305092
ER -