CIC-SIoT: Clean-Slate Information-Centric Software-Defined Content Discovery and Distribution for Internet of Things

The rapid expansion of the Internet of Things (IoT) introduces critical challenges in scalability, mobility, and security, particularly in large-scale deployments. While information-centric networking (ICN) addresses these by enhancing content mobility, multipath support, and edge-embedded caching with inherent security features, it faces limitations in handling large heterogeneous environments due to its in-network caching and content-based forwarding strategies. Software-defined networking (SDN) complements ICN by employing a centralized controller to intelligently orchestrate content caching and forwarding, yet struggles with the efficient allocation and acquisition of content across expansive IoT systems. In response to these challenges, we propose CIC-SIoT, a novel information-centric SDN (IC-SDN) solution, designed to optimize the ICN-IoT framework. Our solution incorporates specialized algorithms for controllers, consumers, producers, and ICN nodes. These algorithms improve content forwarding decisions by moving beyond the traditional reliance on the forwarding information base (FIB) and instead utilizing the pending interest table (PIT) to efficiently manage and distribute content. Validated through ndnSIM and MATLAB simulations, CIC-SIoT achieves substantial performance enhancements, including an 80% increase in throughput, a 34% reduction in latency, and a 25% savings in bandwidth. Additionally, it reduces packet loss by 67% and communication overhead by 66%, compared to existing solutions. These results underscore the framework’s ability to significantly improve the efficiency and scalability of content distribution in IoT environments, highlighting its robustness and adaptability in addressing the complex dynamics of modern networked systems.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-08-12
DOI
https://doi.org/10.1109/jiot.2024.3441814
Citations
6
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
6.31

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article

CIC-SIoT: Clean-Slate Information-Centric Software-Defined Content Discovery and Distribution for Internet of Things

Zohaib Latif, Qiang Qu, Md Monjurul Karim, Sujit Biswas et al.
6 citations
IEEE Internet of Things Journal
Scientific Computing and Data Management
6.31
article

CIC-SIoT: Clean-Slate Information-Centric Software-Defined Content Discovery and Distribution for Internet of Things

Zohaib Latif, Qiang Qu, Md Monjurul Karim, Sujit Biswas, Kashif Sharif, Fan Li
article en
6 citations

Abstract

The rapid expansion of the Internet of Things (IoT) introduces critical challenges in scalability, mobility, and security, particularly in large-scale deployments. While information-centric networking (ICN) addresses these by enhancing content mobility, multipath support, and edge-embedded caching with inherent security features, it faces limitations in handling large heterogeneous environments due to its in-network caching and content-based forwarding strategies. Software-defined networking (SDN) complements ICN by employing a centralized controller to intelligently orchestrate content caching and forwarding, yet struggles with the efficient allocation and acquisition of content across expansive IoT systems. In response to these challenges, we propose CIC-SIoT, a novel information-centric SDN (IC-SDN) solution, designed to optimize the ICN-IoT framework. Our solution incorporates specialized algorithms for controllers, consumers, producers, and ICN nodes. These algorithms improve content forwarding decisions by moving beyond the traditional reliance on the forwarding information base (FIB) and instead utilizing the pending interest table (PIT) to efficiently manage and distribute content. Validated through ndnSIM and MATLAB simulations, CIC-SIoT achieves substantial performance enhancements, including an 80% increase in throughput, a 34% reduction in latency, and a 25% savings in bandwidth. Additionally, it reduces packet loss by 67% and communication overhead by 66%, compared to existing solutions. These results underscore the framework’s ability to significantly improve the efficiency and scalability of content distribution in IoT environments, highlighting its robustness and adaptability in addressing the complex dynamics of modern networked systems.

IEEE Internet of Things JournalVol. 11(22)
University of London (GB), Beijing Institute of Technology (CN), City, University of London (GB), Chinese Academy of Sciences (CN), Shenzhen Institutes of Advanced Technology (CN), Nazarbayev University (KZ)
National Natural Science Foundation of China
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Scientific Computing and Data Management
6.31
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