PMID- 36298078
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20221030
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 22
IP  - 20
DP  - 2022 Oct 12
TI  - A Hybrid Intelligent Simulation System for Building IoT Networks: Performance 
      Comparison of Different Router Replacement Methods for WMNs Considering Stadium 
      Distribution of IoT Devices.
LID - 10.3390/s22207727 [doi]
LID - 7727
AB  - As the Internet of Things (IoT) devices and applications proliferate, it becomes 
      increasingly important to design robust networks that can continue to meet user 
      demands at a high level. Wireless local area networks (WLANs) can be a good 
      choice as IoT infrastructure when high throughput is required. On the other hand, 
      wireless mesh networks (WMNs), which are WLANs with mesh topology following the 
      IEEE802.11s standard, have many advantages compared to conventional WLANs. 
      Nevertheless, there are some problems that need solutions. One of them is the 
      node placement problem. In this work, we propose and implement a hybrid 
      intelligent system that solves this problem by determining the position of mesh 
      nodes by maximizing the mesh connectivity and the coverage of IoT devices. The 
      system is based on particle swarm optimization (PSO), simulated annealing (SA), 
      and distributed genetic algorithm (DGA). We compare the performance of three 
      router replacement methods: constriction method (CM), random inertia weight 
      method (RIWM), and rational decrement of Vmax method (RDVM). The simulation 
      results show that RIWM achieves better performance compared to CM and RDVM 
      because it achieves the highest connectivity while covering more clients than the 
      other two methods.
FAU - Barolli, Admir
AU  - Barolli A
AD  - Department of Information Technology, Aleksander Moisiu University of Durres, 
      L.1, Rruga e Currilave, 2001 Durres, Albania.
FAU - Sakamoto, Shinji
AU  - Sakamoto S
AUID- ORCID: 0000-0002-4103-8828
AD  - Department of Information and Computer Science, Kanazawa Institute of Technology 
      (KIT), 7-1 Ohgigaoka, Nonoichi 921-8501, Japan.
FAU - Bylykbashi, Kevin
AU  - Bylykbashi K
AUID- ORCID: 0000-0002-5674-4629
AD  - Department of Information and Communication Engineering, Fukuoka Institute of 
      Technology (FIT), 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka 811-0295, Japan.
FAU - Barolli, Leonard
AU  - Barolli L
AUID- ORCID: 0000-0001-9069-0460
AD  - Department of Information and Communication Engineering, Fukuoka Institute of 
      Technology (FIT), 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka 811-0295, Japan.
LA  - eng
PT  - Journal Article
DEP - 20221012
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
PMC - PMC9612208
OTO - NOTNLM
OT  - Internet of Things
OT  - distributed genetic algorithm
OT  - particle swarm optimization
OT  - simulated annealing
OT  - wireless mesh networks
COIS- The authors declare no conflict of interest.
EDAT- 2022/10/28 06:00
MHDA- 2022/10/28 06:01
PMCR- 2022/10/12
CRDT- 2022/10/27 01:54
PHST- 2022/09/09 00:00 [received]
PHST- 2022/10/04 00:00 [revised]
PHST- 2022/10/08 00:00 [accepted]
PHST- 2022/10/27 01:54 [entrez]
PHST- 2022/10/28 06:00 [pubmed]
PHST- 2022/10/28 06:01 [medline]
PHST- 2022/10/12 00:00 [pmc-release]
AID - s22207727 [pii]
AID - sensors-22-07727 [pii]
AID - 10.3390/s22207727 [doi]
PST - epublish
SO  - Sensors (Basel). 2022 Oct 12;22(20):7727. doi: 10.3390/s22207727.