Wireless video sensor network (WVSN) has attracted much research interest due to its multi‐faceted potential applications in different fields. An energy‐efficient protocol is fundamental for WVSN since the network has to deal with traffic‐intensive multimedia data, such as images and videos. A few issues come in front for any such setting like energy inefficiency, throughput unfairness, and low network capacity. In many cases, we need to strike a balance between required parameters or aspects, but there is no alternative to ensuring appropriate energy efficiency in the process. Keeping this in mind, this paper proposes a holistic solution named energy‐efficient bio‐inspired Mimosa pudica (EEBIMP) algorithm. EEBIMP for WVSN can reduce the time delay and avoid unnecessary energy consumption due to clustering the network. Our proposed algorithm has been compared with one of the most recent notable solutions, like GREENNESS (Green wiReless vidEo sENsor NEtworks uSing out‐of‐band Signalling), PSO (Particle Swarm Optimization), and CUCKOO search algorithm. The result shows that EEBIMP achieved 95% of energy efficiency and throughput when compared with other algorithms of GREENNESS, PSO, and CUCKOO.

中文翻译：

---

受生物启发的含羞草pudica算法用于节能型无线视频传感器网络

无线视频传感器网络（WVSN）由于其在不同领域的潜在应用而吸引了许多研究兴趣。节能协议对于WVSN至关重要，因为网络必须处理流量密集型多媒体数据，例如图像和视频。任何此类设置都会面临一些问题，例如能源效率低下，吞吐量不公平和网络容量低。在许多情况下，我们需要在所需参数或方面之间取得平衡，但是除了确保过程中适当的能源效率外，别无选择。牢记这一点，本文提出了一种整体解决方案，名为能源高效的生物启发式含羞草（EEBIMP）算法。用于WVSN的EEBIMP可以减少时间延迟，并避免由于群集网络而造成不必要的能耗。我们提出的算法已与最新的著名解决方案之一进行了比较，例如GREENNESS（使用带外信令的绿色无线视频传感器），PSO（粒子群优化）和CUCKOO搜索算法。结果表明，与其他GREENNESS，PSO和CUCKOO算法相比，EEBIMP达到了95％的能源效率和吞吐量。