TY - JOUR
T1 - Artificial intelligence-enabled distributed energy conservative model for mobile internet of things using software-defined network
AU - Haseeb, Khalid
AU - Islam, Naveed
AU - Ahmed, Imran
AU - Hassan, Mohammad Mehedi
AU - Jeon, Gwanggil
N1 - Publisher Copyright:
© 2022 John Wiley & Sons Ltd.
PY - 2022
Y1 - 2022
N2 - The Internet of things (IoT) is an emerging technology for many smart applications due to its efficient resource utilization, scalability, and fast interaction with the physical world. Software-defined network (SDN), on the other hand, provides dynamic services for controlling and managing real-time systems. However, collected data are sent to a central location, which requires balancing energy resources with redundant channels to maximize the availability of smart functions. Furthermore, the IoT network faces numerous security vulnerabilities as a result of its open communication space, including malicious messages and privacy concerns. Thus, this paper presents a distributed and artificial intelligence-based energy-efficient model for IoT-SDN architecture, which aims to improve data aggregation and power distribution. It also provides security and authentication for smart communication systems. First, the proposed model introduces the heuristic evaluation using artificial intelligence and decreases the power consumption for sensor nodes in a real-time system. Moreover, it optimizes the paradigm of distributed processing and efficiently increases the green energy technology with nominal management costs using the mobile edges. Second, the aggregated data of the environment is secured using a centralized controller to attain the most trustworthy data availability. The experimental results show a comparative analysis of the proposed model in terms of energy efficiency, packet drop ratio, and waiting time by 22%, 23%, 40%, and 49% as compared to existing studies.
AB - The Internet of things (IoT) is an emerging technology for many smart applications due to its efficient resource utilization, scalability, and fast interaction with the physical world. Software-defined network (SDN), on the other hand, provides dynamic services for controlling and managing real-time systems. However, collected data are sent to a central location, which requires balancing energy resources with redundant channels to maximize the availability of smart functions. Furthermore, the IoT network faces numerous security vulnerabilities as a result of its open communication space, including malicious messages and privacy concerns. Thus, this paper presents a distributed and artificial intelligence-based energy-efficient model for IoT-SDN architecture, which aims to improve data aggregation and power distribution. It also provides security and authentication for smart communication systems. First, the proposed model introduces the heuristic evaluation using artificial intelligence and decreases the power consumption for sensor nodes in a real-time system. Moreover, it optimizes the paradigm of distributed processing and efficiently increases the green energy technology with nominal management costs using the mobile edges. Second, the aggregated data of the environment is secured using a centralized controller to attain the most trustworthy data availability. The experimental results show a comparative analysis of the proposed model in terms of energy efficiency, packet drop ratio, and waiting time by 22%, 23%, 40%, and 49% as compared to existing studies.
KW - Internet of things
KW - artificial intelligence
KW - energy management
KW - smart systems
KW - software-defined network
UR - http://www.scopus.com/inward/record.url?scp=85134237052&partnerID=8YFLogxK
U2 - 10.1002/dac.5295
DO - 10.1002/dac.5295
M3 - Article
AN - SCOPUS:85134237052
SN - 1074-5351
JO - International Journal of Communication Systems
JF - International Journal of Communication Systems
ER -