PMID- 37420641
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20230710
LR  - 20230718
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 23
IP  - 12
DP  - 2023 Jun 9
TI  - Heterogeneous Algorithm for Efficient-Path Detection and Congestion Avoidance for 
      a Vehicular-Management System.
LID - 10.3390/s23125471 [doi]
LID - 5471
AB  - Finding reliable and efficient routes is a persistent problem in megacities. To 
      address this problem, several algorithms have been proposed. However, there are 
      still areas of research that require attention. Many traffic-related problems can 
      be resolved with the help of smart cities that incorporate the Internet of 
      Vehicles (IoV). On the other hand, due to rapid increases in the population and 
      automobiles, traffic congestion has become a serious concern. This paper presents 
      a heterogeneous algorithm called ant-colony optimization with pheromone termite 
      (ACO-PT), which combines two state-of-the-art algorithms, pheromone termite (PT) 
      and ant-colony optimization (ACO), to address efficient routing to improve energy 
      efficiency, increase throughput, and shorten end-to-end latency. The ACO-PT 
      algorithm seeks to provide an effective shortest path from a source to a 
      destination for drivers in urban areas. Vehicle congestion is a severe issue in 
      urban areas. To address this issue, a congestion-avoidance module is added to 
      handle potential overcrowding. Automatic vehicle detection has also been a 
      challenging issue in vehicle management. To address this issue, an 
      automatic-vehicle-detection (AVD) module is employed with ACO-PT. The 
      effectiveness of the proposed ACO-PT algorithm is demonstrated experimentally 
      using network simulator-3 (NS-3) and Simulation of Urban Mobility (SUMO). Our 
      proposed algorithm is compared with three cutting-edge algorithms. The results 
      demonstrate that the proposed ACO-PT algorithm is superior to earlier algorithms 
      in terms of energy usage, end-to-end delay, and throughput.
FAU - Noussaiba, Melaouene
AU  - Noussaiba M
AD  - Team of Information Research and Indexing Documents, Texts and Multimedia, 
      ENSIAS, Mohammad V University, Rabat BP 713, Morocco.
FAU - Razaque, Abdul
AU  - Razaque A
AUID- ORCID: 0000-0003-0409-3526
AD  - School of Computing, Gachon University South Korea, Seongnam-si 13120, Republic 
      of Korea.
FAU - Rahal, Romadi
AU  - Rahal R
AD  - Team of Information Research and Indexing Documents, Texts and Multimedia, 
      ENSIAS, Mohammad V University, Rabat BP 713, Morocco.
LA  - eng
PT  - Journal Article
DEP - 20230609
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
RN  - 0 (Pheromones)
SB  - IM
MH  - *Algorithms
MH  - Computer Simulation
MH  - Cities
MH  - *Internet
MH  - Pheromones
PMC - PMC10303816
OTO - NOTNLM
OT  - ant-colony optimization
OT  - congestion avoidance
OT  - end-to-end delay
OT  - energy consumption
OT  - pheromone termite
COIS- The authors declare no conflict of interest.
EDAT- 2023/07/08 10:42
MHDA- 2023/07/10 06:42
PMCR- 2023/06/09
CRDT- 2023/07/08 01:10
PHST- 2023/03/10 00:00 [received]
PHST- 2023/05/11 00:00 [revised]
PHST- 2023/05/29 00:00 [accepted]
PHST- 2023/07/10 06:42 [medline]
PHST- 2023/07/08 10:42 [pubmed]
PHST- 2023/07/08 01:10 [entrez]
PHST- 2023/06/09 00:00 [pmc-release]
AID - s23125471 [pii]
AID - sensors-23-05471 [pii]
AID - 10.3390/s23125471 [doi]
PST - epublish
SO  - Sensors (Basel). 2023 Jun 9;23(12):5471. doi: 10.3390/s23125471.