We introduce an Autonomic System to perform management of energy consumption in Internet of Things (IoT) devices and Fog Computing, including an advanced orchestration mechanisms to manage dynamic duty cycles for extra energy savings. The solution works by adjusting Home (H) and Away (A) cycles based on contextual information, like environmental conditions, user behavior, behavior variation, regulations on energy and network resources utilization, among others. Performance analysis through a proof-of-concept implementation presents average energy savings of up to 61.51% when augmenting with a scheduling system and variable long sleep cycles (LS), and potential for 75.9% savings in specific conditions. We also concluded that there is no linear relation between increasing LS time and additional savings. The significance of this research is to promote autonomic management as a solution to develop more energy efficient buildings and smarter cities, towards sustainable goals.

我们引入了一个自主系统来管理物联网 (IoT) 设备和雾计算中的能源消耗，包括一个先进的编排机制来管理动态占空比以节省额外的能源。该解决方案的工作原理是根据上下文信息（如环境条件、用户行为、行为变化、能源和网络资源利用规定等）调整 Home (H) 和 Away (A) 周期。通过概念验证实施进行的性能分析表明，在使用调度系统和可变长睡眠周期 (LS) 进行增强时，平均节能高达 61.51%，在特定条件下可能节能 75.9%。我们还得出结论，增加 LS 时间和额外节省之间没有线性关系。