Unmanned Aerial Vehicles (UAVs) are the upshot of the swift advance in leading fields, such as computing, sensing, communication technologies, etc. Years, the military field served as the sole realm holding UAVs applications. However, the advent of small and mini UAVs brought the coda of such an exclusive use case, and the civilian experience has been pushed up. For higher yield, a swarm of UAVs, aka Multi-UAV system, is formed fulfilling a cooperative screenplay. For bulk cases, the Ad-hoc technology is used as the gist of the networking layer connecting the UAVs, forming the new-brand Unmanned Aerial Ad-hoc Network (UAANET). By dint of the limited battery supply, the energy constraint is deemed the UAVs’ primary impediment, which has acquired all-embracing attention since it may significantly restrict the applications’ scope and affect their efficiency, yield, and performance. This points out the optimization of energy saving as a necessity, of great resonance, in such an environment. To make our proposed solution gets an extremely potent form of efficiency, we highlight the communication impact on energy consumption from two distinct outlooks. The first is the explicit impact in relation to the communication protocol. The second is the implicit impact in which we involve the mobility model as an aspect through which we boost energy saving, where basic parameters in relation to mobility and, at the same time, are seen as networking tones, have been considered. Such a trend of highlighting the communication impact is deemed to be the first in the UAVs’ literature, which makes our work more vital and significant. In this paper, we propose a new ElectriBio-inspired Energy-Efficient Self-organization model for UAANET (EBEESU), which is an amalgam of Electrical-inspired and Bio-inspired models blending a mobility model and a cluster-based communication algorithm with two-level data aggregation, wherein energy saving is the intrinsic aim. Via simulation scenarios, our proposed model proved its efficiency in reducing energy consumption, giving increased network lifetime. Besides, the packet loss ratio and the average End-to-End delay are significantly minimized, optimizing thus the network’s quality of service, making our solution particularly fitting for the UAANET.

无人飞行器（UAV）是计算，传感，通信技术等领先领域迅速发展的结果。多年来，军事领域一直是无人机应用的唯一领域。然而，小型和微型无人机的问世带来了这种独家用例的尾声，平民经验得到了提升。为了获得更高的收益，形成了一批UAV（又名Multi-UAV系统），以实现协同编剧。对于大宗情况，Ad-hoc技术被用作连接无人机的网络层的要点，从而形成了新品牌的无人空中Ad-hoc网络（UAANET）。通过有限的电池供电，能量约束被认为是无人机的主要障碍，由于它可能会严重限制应用程序的范围并影响其效率，良率和性能，因此引起了各方的关注。这指出了在这种环境下优化节能的必要性和巨大的共鸣性。为了使我们提出的解决方案获得极为有效的效率，我们从两个截然不同的观点着重说明通信对能源消耗的影响。首先是对通信协议的明确影响。第二个隐含影响是，我们将移动性模型作为提高能源节约的一个方面，其中考虑了与移动性相关的基本参数，同时又将它们视为网络音调。这种强调交流影响的趋势被认为是无人机文献中的第一个，这使我们的工作更加重要和有意义。在本文中，我们提出了一种新的基于UAENET的受ElectriBio启发的能效自组织模型（EBEESU），该模型是将移动性模型和基于集群的通信算法与两个模型结合在一起的电气和生物启发模型的混合物级数据聚合，其中节能是内在的目标。通过仿真场景，我们提出的模型证明了其在降低能耗，提高网络寿命方面的效率。此外，丢包率和平均端到端延迟也大大降低了，从而优化了网络的服务质量，这使得我们的解决方案特别适合UAANET。我们为UAANET（EBEESU）提出了一个新的受ElectriBio启发的节能自组织模型，该模型是由电气启发和生物启发模型组成的混合模型，融合了移动性模型和基于集群的通信算法以及两级数据聚合，其中节能是内在目标。通过仿真场景，我们提出的模型证明了其在降低能耗，提高网络寿命方面的效率。此外，丢包率和平均端到端延迟也大大降低了，从而优化了网络的服务质量，这使得我们的解决方案特别适合UAANET。我们为UAANET（EBEESU）提出了一个新的受ElectriBio启发的节能自组织模型，该模型是由电气启发和生物启发模型组成的混合模型，融合了移动性模型和基于集群的通信算法以及两级数据聚合，其中节能是内在目标。通过仿真场景，我们提出的模型证明了其在降低能耗，提高网络寿命方面的效率。此外，丢包率和平均端到端延迟也大大降低了，从而优化了网络的服务质量，这使得我们的解决方案特别适合UAANET。其中节能是内在目标。通过仿真场景，我们提出的模型证明了其在降低能耗，提高网络寿命方面的效率。此外，丢包率和平均端到端延迟也大大降低了，从而优化了网络的服务质量，这使得我们的解决方案特别适合UAANET。节能是其内在目标。通过仿真场景，我们提出的模型证明了其在降低能耗，提高网络寿命方面的效率。此外，丢包率和平均端到端延迟也大大降低了，从而优化了网络的服务质量，这使得我们的解决方案特别适合UAANET。