Energy-Efficient and Latency-Aware Data Routing in Small-World Internet of Drone Networks

Recently, drones have attracted considerable attention for sensing hostile areas. Multiple drones are deployed to communicate and coordinate sensing and data transfer in the Internet of Drones (IoD) network. Traditionally, multi-hop routing is employed for communication over long distances to increase the network’s lifetime. However, multi-hop routing over large-scale networks leads to energy imbalance and higher data latency. Motivated by this, in this paper, a novel framework of energy-efficient and latency-aware data routing is proposed for Small-World (SW)-IoD networks. We started with an optimization problem formulation in terms of network delay, energy consumption, and reliability. Then, the formulated mixed integer problem is solved by introducing the Small-World Characters (SWC) into the conventional IoD network to form the SW-IoD network. Here, the proposed framework introduces SWC by removing a few existing edges with the least edge weight from the traditional network and introducing the same number of long-range edges with the highest edge weight. We present the simulation results corresponding to packet delivery ratio, network lifetime, and network delay for the performance comparison of the proposed framework with state-of-the-art approaches such as the conventional SWC method, LEACH, Modified LEACH, Canonical Particle Multi-Swarm (PMS) method, and conventional shortest path routing algorithm. We also analyze the effect of the location of the ground control station, the velocity of the drones, and the different heights of layers on the performance of the proposed framework. Through experiments, the superiority of the proposed method is proven to be better when compared to other methods. Finally, the performance evaluation of the proposed model is tested on a network simulator (NS3).

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Publication Details

Journal
IEEE Transactions on Network and Service Management
Published
2024-08-30
DOI
https://doi.org/10.1109/tnsm.2024.3452414
Citations
5
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
6.49

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article

Energy-Efficient and Latency-Aware Data Routing in Small-World Internet of Drone Networks

Sreenivasa Reddy Yeduri, Linga Reddy Cenkeramaddi, Om Jee Pandey, Sindhusha Jeeru
5 citations
IEEE Transactions on Network and Service Management
UAV Applications and Optimization
6.49
article

Energy-Efficient and Latency-Aware Data Routing in Small-World Internet of Drone Networks

Sreenivasa Reddy Yeduri, Linga Reddy Cenkeramaddi, Om Jee Pandey, Sindhusha Jeeru
article en
5 citations

Abstract

Recently, drones have attracted considerable attention for sensing hostile areas. Multiple drones are deployed to communicate and coordinate sensing and data transfer in the Internet of Drones (IoD) network. Traditionally, multi-hop routing is employed for communication over long distances to increase the network’s lifetime. However, multi-hop routing over large-scale networks leads to energy imbalance and higher data latency. Motivated by this, in this paper, a novel framework of energy-efficient and latency-aware data routing is proposed for Small-World (SW)-IoD networks. We started with an optimization problem formulation in terms of network delay, energy consumption, and reliability. Then, the formulated mixed integer problem is solved by introducing the Small-World Characters (SWC) into the conventional IoD network to form the SW-IoD network. Here, the proposed framework introduces SWC by removing a few existing edges with the least edge weight from the traditional network and introducing the same number of long-range edges with the highest edge weight. We present the simulation results corresponding to packet delivery ratio, network lifetime, and network delay for the performance comparison of the proposed framework with state-of-the-art approaches such as the conventional SWC method, LEACH, Modified LEACH, Canonical Particle Multi-Swarm (PMS) method, and conventional shortest path routing algorithm. We also analyze the effect of the location of the ground control station, the velocity of the drones, and the different heights of layers on the performance of the proposed framework. Through experiments, the superiority of the proposed method is proven to be better when compared to other methods. Finally, the performance evaluation of the proposed model is tested on a network simulator (NS3).

IEEE Transactions on Network and Service ManagementVol. 21(6)
University of Agder (NO), Indian Institute of Technology BHU (IN), Banaras Hindu University (IN)
Norges Forskningsråd
Affordable and clean energy
Openalex Percentile: Top 4%
UAV Applications and Optimization
6.49
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