A P2P multi-path routing algorithm based on Skyline operator for data aggregation in IoMT environments.

Data routing Distributed systems Healthcare Internet of Medical Things Routing metrics Skyline Wireless sensor networks

Journal

PeerJ. Computer science
ISSN: 2376-5992
Titre abrégé: PeerJ Comput Sci
Pays: United States
ID NLM: 101660598

Informations de publication

Date de publication:
2023
Historique:
received: 15 05 2023
accepted: 15 10 2023
medline: 11 12 2023
pubmed: 11 12 2023
entrez: 11 12 2023
Statut: epublish

Résumé

The integration of Internet of Things (IoT) technologies, particularly the Internet of Medical Things (IoMT), with wireless sensor networks (WSNs) has revolutionized the healthcare industry. However, despite the undeniable benefits of WSNs, their limited communication capabilities and network congestion have emerged as critical challenges in the context of healthcare applications. This research addresses these challenges through a dynamic and on-demand route-finding protocol called P2P-IoMT, based on LOADng for point-to-point routing in IoMT. To reduce congestion, dynamic composite routing metrics allow nodes to select the optimal parent based on the application requirements during the routing discovery phase. Nodes running the proposed routing protocol use the multi-criteria decision-making Skyline technique for parent selection. Experimental evaluation results show that P2P-IoMT protocol outperforms its best rivals in the literature in terms of residual network energy and packet delivery ratio. The network lifetime is extended by 4% while achieving a comparable packet delivery ratio and communication delay compared to LRRE. These performances are offered on top of the dynamic path selection and configurable route metrics capabilities of P2P-IoMT.

Identifiants

pubmed: 38077549
doi: 10.7717/peerj-cs.1682
pii: cs-1682
pmc: PMC10702938
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e1682

Informations de copyright

©2023 Kertiou et al.

Déclaration de conflit d'intérêts

The authors declare there are no competing interests.

Références

Sensors (Basel). 2015 Sep 11;15(9):22970-3003
pubmed: 26378539
Sensors (Basel). 2018 Jan 26;18(2):
pubmed: 29373499
Sensors (Basel). 2019 Jan 03;19(1):
pubmed: 30609865
Sensors (Basel). 2019 May 09;19(9):
pubmed: 31075837

Auteurs

Ismail Kertiou (I)

LIAP Laboratory, University of El Oued, El Oued, Algeria.

Abdelkader Laouid (A)

LIAP Laboratory, University of El Oued, El Oued, Algeria.

Benharzallah Saber (B)

Computer Science, University of Batna 2, Batna, Algeria.

Mohammad Hammoudeh (M)

Information and Computer Science Department, King Fahad University of Petroleum and Minerals, Dahran, Saudi Arabia.

Muath Alshaikh (M)

Computer Science Department, College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia.

Classifications MeSH