Orchestration and Management of Adaptive IoT-centric Distributed Applications.

Edge Computing IoT-centric workflows Knowledge-driven business processes Service orchestration

Journal

IEEE internet of things journal
ISSN: 2327-4662
Titre abrégé: IEEE Internet Things J
Pays: United States
ID NLM: 101704157

Informations de publication

Date de publication:
Feb 2024
Historique:
pmc-release: 01 02 2025
medline: 29 1 2024
pubmed: 29 1 2024
entrez: 29 1 2024
Statut: ppublish

Résumé

Current Internet of Things (IoT) devices provide a diverse range of functionalities, ranging from measurement and dissemination of sensory data observation, to computation services for real-time data stream processing. In extreme situations such as emergencies, a significant benefit of IoT devices is that they can help gain a more complete situational understanding of the environment. However, this requires the ability to utilize IoT resources while taking into account location, battery life, and other constraints of the underlying edge and IoT devices. A dynamic approach is proposed for orchestration and management of distributed workflow applications using services available in cloud data centers, deployed on servers, or IoT devices at the network edge. Our proposed approach is specifically designed for knowledge-driven business process workflows that are adaptive, interactive, evolvable and emergent. A comprehensive empirical evaluation shows that the proposed approach is effective and resilient to situational changes.

Identifiants

pubmed: 38283301
doi: 10.1109/jiot.2023.3306238
pmc: PMC10810342
doi:

Types de publication

Journal Article

Langues

eng

Pagination

3779-3791

Auteurs

Sehrish Amjad (S)

Department of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.

Ahmed Akhtar (A)

Department of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.

Muhammad Ali (M)

Department of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.

Ayesha Afzal (A)

Department of Computer Science, Air University, Pakistan.

Basit Shafiq (B)

Department of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.

Jaideep Vaidya (J)

Rutgers University, Newark, NJ 07102.

Shafay Shamail (S)

Department of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan.

Omer Rana (O)

School of Computer Science & Informatics, Cardiff University, Cardiff, UK.

Classifications MeSH