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Reliable Data Exchange in UAV Swarm Networks Using Advanced Networking Techniques
Research Article  ·  Published: 12 May 2026
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ICCK Transactions on Advanced Computing and Systems
Volume 2, Issue 3, 2026: 212-224
Research Article Open Access

Reliable Data Exchange in UAV Swarm Networks Using Advanced Networking Techniques

by
Syed Haider Ali Syed Haider Ali 1 *
Syed Ashraf Ali Syed Ashraf Ali 2
James Adu Ansere James Adu Ansere 3 ORCID
Muhammad Younas Muhammad Younas 1
Sana Ullah Sana Ullah 1
1 Pakistan Council of Scientific & Industrial Research, Peshawar, Pakistan
2 Iqra National University, Peshawar, Pakistan
3 Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL, Canada
* Corresponding Author: Syed Haider Ali, [email protected]
Volume 2, Issue 3
Volume 2, Issue 3 2026
Received: 03 July 2025 Revised: 02 December 2025 Accepted: 08 February 2026 Published: 12 May 2026 CrossMark
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DOI: 10.62762/TACS.2025.747408
ARK: ark:/57805/tacs.2025.747408
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Article Information

Published in ICCK Transactions on Advanced Computing and Systems
Volume/Issue Volume 2, Issue 3, 2026
Pages 212-224
Cited by 2 (Crossref) 2 (Scopus)

Abstract

The proliferation of unmanned aerial vehicles (UAVs) has driven the emergence of Flying Ad-hoc Networks (FANETs) as distributed cyber-physical computing systems for surveillance, disaster management, precision agriculture, and logistics. Optimizing computational and communication resource utilization within these constrained aerial systems is essential to extend network lifespan and maintain satisfactory quality of service (QoS). This study proposes integrating the Fisheye State Routing (FSR) protocol with a 3$\times$3 Manhattan Grid mobility model as a computing-systems solution for reliable data exchange in dynamic UAV swarm networks. FSR maintains distributed topology tables and applies Dijkstra's algorithm to compute optimal routing paths, enabling adaptive resource allocation across continuously reconfiguring network architectures. Performance is evaluated across six metrics—packet delivery ratio, packet drop rate, end-to-end delay, channel utilization, throughput, and jitter—under two scenarios of twenty and thirty nodes. FSR achieves packet delivery ratios of 46% and 53% respectively, with minimal end-to-end latencies of 0.010 and 0.244 seconds and reduced jitter, outperforming five topology-based protocols (OLSR, AODV, DSR, TORA, DSDV) in resource utilization across all evaluated metrics.

Graphical Abstract

Reliable Data Exchange in UAV Swarm Networks Using Advanced Networking Techniques

Keywords

UAV swarm networks FSR FANET network and communication systems internet of aerial vehicles cyber-physical systems resource optimization green UAV communications routing protocol

Data Availability Statement

Data will be made available on request.

Funding

This work was supported without any funding.

Conflicts of Interest

James Adu Ansere served as an Associate Editor of the ICCK Transactions on Advanced Computing and Systems at the time of manuscript submission. To ensure the integrity of the peer-review process, James Adu Ansere was not involved in the editorial handling, peer review, or decision-making process for this manuscript, which was handled independently by another editor. The remaining authors declare no conflicts of interest.

AI Use Statement

The authors declare that no generative AI was used in the preparation of this manuscript.

Ethical Approval and Consent to Participate

Not applicable.

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APA Style
Ali, S. H., Ali, S. A., Ansere, J. A., Younas, M., & Ullah, S. (2026). Reliable Data Exchange in UAV Swarm Networks Using Advanced Networking Techniques. ICCK Transactions on Advanced Computing and Systems, 2(3), 212-224. https://doi.org/10.62762/TACS.2025.747408
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TY  - JOUR
AU  - Ali, Syed Haider
AU  - Ali, Syed Ashraf
AU  - Ansere, James Adu
AU  - Younas, Muhammad
AU  - Ullah, Sana
PY  - 2026
DA  - 2026/05/12
TI  - Reliable Data Exchange in UAV Swarm Networks Using Advanced Networking Techniques
JO  - ICCK Transactions on Advanced Computing and Systems
T2  - ICCK Transactions on Advanced Computing and Systems
JF  - ICCK Transactions on Advanced Computing and Systems
VL  - 2
IS  - 3
SP  - 212
EP  - 224
DO  - 10.62762/TACS.2025.747408
UR  - https://www.icck.org/article/abs/TACS.2025.747408
KW  - UAV swarm networks
KW  - FSR
KW  - FANET
KW  - network and communication systems
KW  - internet of aerial vehicles
KW  - cyber-physical systems
KW  - resource optimization
KW  - green UAV communications
KW  - routing protocol
AB  - The proliferation of unmanned aerial vehicles (UAVs) has driven the emergence of Flying Ad-hoc Networks (FANETs) as distributed cyber-physical computing systems for surveillance, disaster management, precision agriculture, and logistics. Optimizing computational and communication resource utilization within these constrained aerial systems is essential to extend network lifespan and maintain satisfactory quality of service (QoS). This study proposes integrating the Fisheye State Routing (FSR) protocol with a 3$\times$3 Manhattan Grid mobility model as a computing-systems solution for reliable data exchange in dynamic UAV swarm networks. FSR maintains distributed topology tables and applies Dijkstra's algorithm to compute optimal routing paths, enabling adaptive resource allocation across continuously reconfiguring network architectures. Performance is evaluated across six metrics—packet delivery ratio, packet drop rate, end-to-end delay, channel utilization, throughput, and jitter—under two scenarios of twenty and thirty nodes. FSR achieves packet delivery ratios of 46% and 53% respectively, with minimal end-to-end latencies of 0.010 and 0.244 seconds and reduced jitter, outperforming five topology-based protocols (OLSR, AODV, DSR, TORA, DSDV) in resource utilization across all evaluated metrics.
SN  - 3068-7969
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  -
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@article{Ali2026Reliable,
  author = {Syed Haider Ali and Syed Ashraf Ali and James Adu Ansere and Muhammad Younas and Sana Ullah},
  title = {Reliable Data Exchange in UAV Swarm Networks Using Advanced Networking Techniques},
  journal = {ICCK Transactions on Advanced Computing and Systems},
  year = {2026},
  volume = {2},
  number = {3},
  pages = {212-224},
  doi = {10.62762/TACS.2025.747408},
  url = {https://www.icck.org/article/abs/TACS.2025.747408},
  abstract = {The proliferation of unmanned aerial vehicles (UAVs) has driven the emergence of Flying Ad-hoc Networks (FANETs) as distributed cyber-physical computing systems for surveillance, disaster management, precision agriculture, and logistics. Optimizing computational and communication resource utilization within these constrained aerial systems is essential to extend network lifespan and maintain satisfactory quality of service (QoS). This study proposes integrating the Fisheye State Routing (FSR) protocol with a 3\$\times\$3 Manhattan Grid mobility model as a computing-systems solution for reliable data exchange in dynamic UAV swarm networks. FSR maintains distributed topology tables and applies Dijkstra's algorithm to compute optimal routing paths, enabling adaptive resource allocation across continuously reconfiguring network architectures. Performance is evaluated across six metrics—packet delivery ratio, packet drop rate, end-to-end delay, channel utilization, throughput, and jitter—under two scenarios of twenty and thirty nodes. FSR achieves packet delivery ratios of 46\% and 53\% respectively, with minimal end-to-end latencies of 0.010 and 0.244 seconds and reduced jitter, outperforming five topology-based protocols (OLSR, AODV, DSR, TORA, DSDV) in resource utilization across all evaluated metrics.},
  keywords = {UAV swarm networks, FSR, FANET, network and communication systems, internet of aerial vehicles, cyber-physical systems, resource optimization, green UAV communications, routing protocol},
  issn = {3068-7969},
  publisher = {Institute of Central Computation and Knowledge}
}

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