Version 1
: Received: 3 April 2024 / Approved: 4 April 2024 / Online: 4 April 2024 (05:59:39 CEST)
How to cite:
Khalil, A.; Zeddini, B. Cross-Layer Optimization for Enhanced IoT Connectivity: A Novel Routing Protocol for Opportunistic Networks. Preprints2024, 2024040342. https://doi.org/10.20944/preprints202404.0342.v1
Khalil, A.; Zeddini, B. Cross-Layer Optimization for Enhanced IoT Connectivity: A Novel Routing Protocol for Opportunistic Networks. Preprints 2024, 2024040342. https://doi.org/10.20944/preprints202404.0342.v1
Khalil, A.; Zeddini, B. Cross-Layer Optimization for Enhanced IoT Connectivity: A Novel Routing Protocol for Opportunistic Networks. Preprints2024, 2024040342. https://doi.org/10.20944/preprints202404.0342.v1
APA Style
Khalil, A., & Zeddini, B. (2024). Cross-Layer Optimization for Enhanced IoT Connectivity: A Novel Routing Protocol for Opportunistic Networks. Preprints. https://doi.org/10.20944/preprints202404.0342.v1
Chicago/Turabian Style
Khalil, A. and Besma Zeddini. 2024 "Cross-Layer Optimization for Enhanced IoT Connectivity: A Novel Routing Protocol for Opportunistic Networks" Preprints. https://doi.org/10.20944/preprints202404.0342.v1
Abstract
Opportunistic networks, an evolution of mobile Ad Hoc networks (MANETs), offer decentralized communication without relying on preinstalled infrastructure, enabling nodes to route packets through different mobile nodes dynamically. However, due to the absence of complete paths and rapidly changing connectivity, routing in opportunistic networks presents unique challenges. This paper proposes a novel probabilistic routing model for opportunistic networks, leveraging nodes' meeting probabilities to route packets towards their destinations. The model dynamically builds routes based on the likelihood of encountering the destination node, considering factors such as last meeting time and acknowledgment tables to manage network overload. Additionally, an efficient message detection scheme is introduced to alleviate high overhead by selectively deleting messages from buffers during congestion. Furthermore, the proposed model incorporates cross-layer optimization techniques, integrating optimization strategies across multiple protocol layers to maximize energy efficiency, adaptability, and message delivery reliability. Through extensive simulations, the effectiveness of the proposed model is demonstrated, showing improved message delivery probability while maintaining reasonable overhead and latency. This research contributes to the advancement of opportunistic networks, particularly in enhancing connectivity and efficiency for Internet of Things (IoT) applications deployed in challenging environments.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
