A Novel Model Based on Window-Pass Preferences for Data Emergency Aware Scheduling in Computer Networks-Reference-Cited by-同舟云学术

A Novel Model Based on Window-Pass Preferences for Data Emergency Aware Scheduling in Computer Networks

Published:2022-11 Issue:11 Volume:18 Page:7880-7888
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Jemmali Mahdi¹^ORCID,Denden Mohsen²^ORCID,Boulila Wadii³^ORCID,Srivastava Gautam⁴^ORCID,Jhaveri Rutvij H.⁵^ORCID,Gadekallu Thippa Reddy⁶^ORCID

Affiliation:

1. Department of Computer Science and Information, College of Science Al-Zulfi, Majmaah University, Majmaah, Saudi Arabia

2. Department of Computer and Information Technologies, College of Telecommunication and Information Riyadh CTI, Technical and Vocational Training Corporation, TVTC Riyadh, Saudi Arabia

3. Robotics and Internet-of-Things Laboratory, Prince Sultan University, Riyadh, Saudi Arabia

4. Department of Mathematics & Computer Science, Brandon University, Brandon, MB, Canada

5. Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar, India

6. Department of Information Technology, Vellore Institute of Technology, Vellore, India

Funder

Deanship of Scientific Research at Majmaah University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/9895125/09709129.pdf?arnumber=9709129

Reference28 articles.

1. Wireless HART stack using multiprocessor technique with laxity algorithm

2. Standalone noise and anomaly detection in wireless sensor networks: A novel time‐series and adaptive Bayesian‐network‐based approach

3. A Precise Synchronization Method for Future Wireless TSN Networks

4. Resource scheduling for infrastructure as a service (IaaS) in cloud computing: Challenges and opportunities

5. An Appraisal of Meta-Heuristic Resource Allocation Techniques for IaaS Cloud

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