The sharp increase of the wireless sensor networks (WSNs) performance has increased their power requirements. However, with a limited battery lifetime it is more and more difficult to deploy many more sensors with today's solutions. Therefore, the authors need to implement autonomous WSNs without any human intervention or external power supply. To this end, this study proposes an effective strategy to ensure an energy consumption gain that takes into account time constraints through a power-aware model based on the dynamic voltage and frequency scaling and the dynamic power management that are appropriate to the WSNs and on a global Earliest Deadline First scheduler. To select the most suitable simulator to integrate and simulate the developed models, >25 of the existing WSN simulators are outlined and evaluated. On the basis of this comparative study analysis, the authors chose the simulation tool for real-time multiprocessor scheduling (STORM) to validate their work for its multiple advantages. 2 Comparative study of WSNs simulators The simulation technologies have been widely used mainly, when the experimental approaches are difficult to achieve due to the complexity of the qualitative and quantitative changes applied

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The growth of the Internet of Things (IoTs) and the number of connected devices is driven by emerging applications and business models. One common aim is to provide systems able to synchronize these devices, handle the big amount of daily generated data and meet business demands. This paper proposes a cost-effective cloud-based architecture using an event-driven backbone to process many applications’ data in real-time, called REDA. It supports the Amazon Web Service (AWS) IoT core, and it opens the door as a free software-based implementation. Measured data from several wireless sensor nodes are transmitted to the cloud running application through the lightweight publisher/subscriber messaging transport protocol, MQTT. The real-time stream processing platform, Apache Kafka, is used as a message broker to receive data from the producer and forward it to the correspondent consumer. Micro-services design patterns, as an event consumer, are implemented with Java spring and managed with Apache Maven to avoid the monolithic applications’ problem. The Apache Kafka cluster co-located with Zookeeper is deployed over three availability zones and optimized for high throughput and low latency. To guarantee no message loss and to simulate the system performances, different load tests are carried out. The proposed architecture is reliable in stress cases and can handle records goes to 8000 messages in a second with low latency in a cheap hosted and configured architecture.

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