Ahmed Shakil, Hossain Md Akbar, Chong Peter Han Joo, Ray Sayan Kumar
Department of Mechanical and Electrical Engineering, Massey University, Palmerston North 4442, New Zealand.
School of Computing, Eastern Institute of Technology, Napier 4112, New Zealand.
Sensors (Basel). 2024 Aug 19;24(16):5353. doi: 10.3390/s24165353.
The Internet of Things (IoT) is a promising technology for sensing and monitoring the environment to reduce disaster impact. Energy is one of the major concerns for IoT devices, as sensors used in IoT devices are battery-operated. Thus, it is important to reduce energy consumption, especially during data transmission in disaster-prone situations. Clustering-based communication helps reduce a node's energy decay during data transmission and enhances network lifetime. Many hybrid combination algorithms have been proposed for clustering and routing protocols to improve network lifetime in disaster scenarios. However, the performance of these protocols varies widely based on the underlying network configuration and the optimisation parameters considered. In this research, we used the clustering parameters most relevant to disaster scenarios, such as the node's residual energy, distance to sink, and network coverage. We then proposed the bio-inspired hybrid BOA-PSO algorithm, where the Butterfly Optimisation Algorithm (BOA) is used for clustering and Particle Swarm Optimisation (PSO) is used for the routing protocol. The performance of the proposed algorithm was compared with that of various benchmark protocols: LEACH, DEEC, PSO, PSO-GA, and PSO-HAS. Residual energy, network throughput, and network lifetime were considered performance metrics. The simulation results demonstrate that the proposed algorithm effectively conserves residual energy, achieving more than a 17% improvement for short-range scenarios and a 10% improvement for long-range scenarios. In terms of throughput, the proposed method delivers a 60% performance enhancement compared to LEACH, a 53% enhancement compared to DEEC, and a 37% enhancement compared to PSO. Additionally, the proposed method results in a 60% reduction in packet drops compared to LEACH and DEEC, and a 30% reduction compared to PSO. It increases network lifetime by 10-20% compared to the benchmark algorithms.
物联网（IoT）是一项很有前景的技术，可用于感知和监测环境以减少灾害影响。能源是物联网设备的主要问题之一，因为物联网设备中使用的传感器由电池供电。因此，降低能耗非常重要，尤其是在易发生灾害的情况下进行数据传输时。基于聚类的通信有助于减少节点在数据传输过程中的能量衰减，并延长网络寿命。已经提出了许多混合组合算法用于聚类和路由协议，以提高灾害场景下的网络寿命。然而，这些协议的性能因底层网络配置和所考虑的优化参数而异。在本研究中，我们使用了与灾害场景最相关的聚类参数，例如节点的剩余能量、到汇聚节点的距离和网络覆盖范围。然后，我们提出了受生物启发的混合BOA-PSO算法，其中蝴蝶优化算法（BOA）用于聚类，粒子群优化（PSO）用于路由协议。将所提出算法的性能与各种基准协议（LEACH、DEEC、PSO、PSO-GA和PSO-HAS）的性能进行了比较。剩余能量、网络吞吐量和网络寿命被视为性能指标。仿真结果表明，所提出的算法有效地节省了剩余能量，在短距离场景下实现了超过17%的提升，在长距离场景下实现了10%的提升。在吞吐量方面，所提出的方法与LEACH相比性能提升了60%，与DEEC相比提升了53%，与PSO相比提升了37%。此外，与LEACH和DEEC相比，所提出的方法导致数据包丢失减少了60%，与PSO相比减少了30%。与基准算法相比，它将网络寿命提高了10-20%。
