The smart applications dominating the planet in the present day and age, have innovatively progressed to deploy Internet of Things (IoT) based systems and related infrastructures in all spectrums of life. Since, variety of applications are being developed using this IoT paradigm, there is an immense necessity for storing data, processing them to get meaningful information and render suitable services to the end-users. The “thing” in this decade is not only a smart sensor or a device; it can be any physical or household object, a smart device or a mobile. With the ever increasing rise in population and smart device usage in every sphere of life, when all of such “thing”s generates data, there is a chance of huge data traffic in the internet. This could be handled only by integrating “Internet of Everything (IoE)” paradigm with a completely diversified technology — Cloud Computing. In order to handle this heavy flow of data traffic and process the same to generate meaningful information, various services in the global environment are utilized. Hence the primary focus revolves in integrating these two diversified paradigm shifts to develop intelligent information processing systems. Energy Efficient Cloud Based Internet of Everything (EECloudIoE) architecture is proposed in this study, which acts as an initial step in integrating these two wide areas thereby providing valuable services to the end users. The utilization of energy is optimized by clustering the various IoT network using Wind Driven Optimization Algorithm. Next, an optimized Cluster Head (CH) is chosen for each cluster, using Firefly Algorithm resulting in reduced data traffic in comparison to other non-clustering schemes. The proposed clustering of IoE is further compared with the widely used state of the art techniques like Artificial Bee Colony (ABC) algorithm, Genetic Algorithm (GA) and Adaptive Gravitational Search algorithm (AGSA). The results justify the superiority of the proposed methodology outperforming the existing approaches with an increased life-time and reduction in traffic.

在当今时代占主导地位的智能应用已经取得了创新性进展，可以在所有生活领域中部署基于物联网（IoT）的系统和相关基础架构。由于使用此IoT范例开发了各种应用程序，因此非常需要存储数据，对其进行处理以获取有意义的信息并向最终用户提供合适的服务。在这十年中，“事物”不仅是智能传感器或设备，还包括智能设备。它可以是任何物理或家用物体，智能设备或移动设备。随着生活的各个领域中人口和智能设备使用量的不断增长，当所有这些“事物”都产生数据时，互联网中就有大量数据流量的机会。这只能通过将“万物互联（IoE）”范例与完全多样化的技术（云计算）相集成来解决。为了处理这种繁重的数据流量并对其进行处理以生成有意义的信息，在全球环境中使用了各种服务。因此，主要重点在于整合这两个多样化的范式转换以开发智能信息处理系统。这项研究提出了基于节能云的万物互联（EECloudIoE）体系结构，这是整合这两个广泛领域的第一步，从而为最终用户提供了有价值的服务。通过使用风力驱动优化算法对各种物联网网络进行聚类来优化能源利用。接下来，为每个群集选择一个优化的群集头（CH），与其他非群集方案相比，使用Firefly算法可减少数据流量。提议的IoE聚类与人工蜂群（ABC）算法，遗传算法（GA）和自适应引力搜索算法（AGSA）等广泛使用的最新技术进行了比较。结果证明了所提出的方法的优越性，与现有方法相比，具有更长的使用寿命和更少的交通流量，因此具有优越性。