• Sustainability is defined as a trustworthiness attribute in SW architecture design. • Design of 4 SW architectures for an indoor environmental IoT system in the Edge. • Response time and energy consumption experimental evaluation report of 30 experiments. • 11 findings for the green and performance trustworthy design of IoT SW architectures. • The 30 experiments’ dataset with response and computing times and energy consumption. Identifying and implementing sustainable solutions to address the high energy consumption of ICT solutions has become a necessity in Industry 4.0. Therefore, the construction of Green software products is a priority for its customers, who need to trust that their software products are sustainable to fulfil the sustainability policies of their companies. We present sustainability as a key attribute in addressing the trustworthiness of software architectures. This work is focused on IoT monitoring software architectures in the Edge, since IoT energy consumption is a critical issue for sustainability due to the huge amount of power connections required by IoT devices and the high energy consumption needed for processing and transmitting their data. We present an exploratory research study conducted to determine how to design trustworthy IoT monitoring software architectures in the Edge considering two critical attributes, performance and sustainability. Specifically, this study evaluates how the configuration of the components that comprise Edge IoT monitoring architectures may influence their energy consumption and response time. This work presents the experimental results of the exploratory study and its findings, in which the energy consumption and response time of four different software architecture configurations of an indoor environmental monitoring IoT system are measured. From the execution of thirty experiments, this study reveals the importance of balancing the monitoring activities between the Edge nodes and servers, and it indicates that it is possible to construct trustworthy IoT monitoring software architectures in the Edge with software components that reduce both energy consumption and response time.