HFFO‐ACRP: Hybrid Fruit Fly Optimization‐Ant Colony Routing Protocol
ABSTRACT As a key technology in ocean exploration, underwater wireless sensor networks (UWSNs) are persistently constrained by challenges stemming from limited node energy, namely short network lifespan and low transmission efficiency. Existing routing protocols often fall into local optima due to t...
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| Vydané v: | Transactions on emerging telecommunications technologies Ročník 36; číslo 10 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Chichester, UK
John Wiley & Sons, Ltd
01.10.2025
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| ISSN: | 2161-3915, 2161-3915 |
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| Abstract | ABSTRACT
As a key technology in ocean exploration, underwater wireless sensor networks (UWSNs) are persistently constrained by challenges stemming from limited node energy, namely short network lifespan and low transmission efficiency. Existing routing protocols often fall into local optima due to their inability to effectively balance global exploration and local exploitation. To address these issues, this study proposes a hybrid optimization routing protocol, HFFO‐ACRP (hybrid fruit fly optimization‐ant colony routing protocol). Its core innovation lies in a synergistic division of labor: the fruit fly optimization algorithm (FOA) performs a global search to generate initial routes by integrating path length, node density, and residual energy. Subsequently, the ant colony optimization (ACO) algorithm conducts local optimization to refine these paths, considering data priority and node energy efficiency. Finally, a unique bidirectional feedback mechanism enables the two algorithms to mutually enhance their search breadth and precision, collectively improving the accuracy and efficiency of route selection. Experimental results demonstrate that, compared to representative protocols, the proposed protocol extends the network lifespan by 9.69%, 16.21%, and 18.68%, respectively, and significantly increases the residual network energy in the later stages of operation. This hybrid strategy provides an efficient and robust routing solution for resolving the critical energy consumption and longevity bottlenecks in UWSNs.
The results show that, at the 650th operational round, the network's residual energy was approximately 2.50%, 18.92%, and 22.15% higher, respectively. By combining the global exploration of FOA with the local exploitation of ACO, this hybrid approach effectively resolves key energy and longevity issues in UWSN routing. |
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| AbstractList | ABSTRACT
As a key technology in ocean exploration, underwater wireless sensor networks (UWSNs) are persistently constrained by challenges stemming from limited node energy, namely short network lifespan and low transmission efficiency. Existing routing protocols often fall into local optima due to their inability to effectively balance global exploration and local exploitation. To address these issues, this study proposes a hybrid optimization routing protocol, HFFO‐ACRP (hybrid fruit fly optimization‐ant colony routing protocol). Its core innovation lies in a synergistic division of labor: the fruit fly optimization algorithm (FOA) performs a global search to generate initial routes by integrating path length, node density, and residual energy. Subsequently, the ant colony optimization (ACO) algorithm conducts local optimization to refine these paths, considering data priority and node energy efficiency. Finally, a unique bidirectional feedback mechanism enables the two algorithms to mutually enhance their search breadth and precision, collectively improving the accuracy and efficiency of route selection. Experimental results demonstrate that, compared to representative protocols, the proposed protocol extends the network lifespan by 9.69%, 16.21%, and 18.68%, respectively, and significantly increases the residual network energy in the later stages of operation. This hybrid strategy provides an efficient and robust routing solution for resolving the critical energy consumption and longevity bottlenecks in UWSNs.
The results show that, at the 650th operational round, the network's residual energy was approximately 2.50%, 18.92%, and 22.15% higher, respectively. By combining the global exploration of FOA with the local exploitation of ACO, this hybrid approach effectively resolves key energy and longevity issues in UWSN routing. As a key technology in ocean exploration, underwater wireless sensor networks (UWSNs) are persistently constrained by challenges stemming from limited node energy, namely short network lifespan and low transmission efficiency. Existing routing protocols often fall into local optima due to their inability to effectively balance global exploration and local exploitation. To address these issues, this study proposes a hybrid optimization routing protocol, HFFO‐ACRP (hybrid fruit fly optimization‐ant colony routing protocol). Its core innovation lies in a synergistic division of labor: the fruit fly optimization algorithm (FOA) performs a global search to generate initial routes by integrating path length, node density, and residual energy. Subsequently, the ant colony optimization (ACO) algorithm conducts local optimization to refine these paths, considering data priority and node energy efficiency. Finally, a unique bidirectional feedback mechanism enables the two algorithms to mutually enhance their search breadth and precision, collectively improving the accuracy and efficiency of route selection. Experimental results demonstrate that, compared to representative protocols, the proposed protocol extends the network lifespan by 9.69%, 16.21%, and 18.68%, respectively, and significantly increases the residual network energy in the later stages of operation. This hybrid strategy provides an efficient and robust routing solution for resolving the critical energy consumption and longevity bottlenecks in UWSNs. |
| Author | Hao, Lijun Ma, Chunbo Ao, Jun |
| Author_xml | – sequence: 1 givenname: Lijun orcidid: 0009-0002-8775-4472 surname: Hao fullname: Hao, Lijun email: 23021201006@guet.edu.cn organization: Guilin University of Electronic Technology – sequence: 2 givenname: Chunbo surname: Ma fullname: Ma, Chunbo organization: Guilin University of Electronic Technology – sequence: 3 givenname: Jun surname: Ao fullname: Ao, Jun organization: Guilin University of Electronic Technology |
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| Notes | The authors received no specific funding for this work. Funding |
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As a key technology in ocean exploration, underwater wireless sensor networks (UWSNs) are persistently constrained by challenges stemming from limited... As a key technology in ocean exploration, underwater wireless sensor networks (UWSNs) are persistently constrained by challenges stemming from limited node... |
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| SubjectTerms | ant colony optimization algorithms fruit fly optimization algorithm lifetime underwater wireless sensor networks |
| Title | HFFO‐ACRP: Hybrid Fruit Fly Optimization‐Ant Colony Routing Protocol |
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