Microcontrollers for IoT: Optimizations, Computing Paradigms, and Future Directions

Chéour, Rym; Khriji, Sabrine; Abid, Mohamed; Kanoun, Olfa

doi:10.1109/wf-iot48130.2020.9221219

Cited by 24 publications

(17 citation statements)

References 29 publications

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“…Different techniques are implemented to reduce the power consumption of the processing unit of a wireless sensor node including the Dynamic Voltage and Frequency Scaling (DVFS) [ 71 ]. The DVFS is designed to minimize the power consumption during the execution of tasks by adjusting dynamically the operating voltage and frequency depending on the system performance requirement at a fixed time.…”

Section: Energy Managementmentioning

confidence: 99%

Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review

Kanoun

Bradai

Khriji

et al. 2021

Sensors

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Nowadays, wireless sensor networks are becoming increasingly important in several sectors including industry, transportation, environment and medicine. This trend is reinforced by the spread of Internet of Things (IoT) technologies in almost all sectors. Autonomous energy supply is thereby an essential aspect as it decides the flexible positioning and easy maintenance, which are decisive for the acceptance of this technology, its wide use and sustainability. Significant improvements made in the last years have shown interesting possibilities for realizing energy-aware wireless sensor nodes (WSNs) by designing manifold and highly efficient energy converters and reducing energy consumption of hardware, software and communication protocols. Using only a few of these techniques or focusing on only one aspect is not sufficient to realize practicable and market relevant solutions. This paper therefore provides a comprehensive review on system design for battery-free and energy-aware WSN, making use of ambient energy or wireless energy transmission. It addresses energy supply strategies and gives a deep insight in energy management methods as well as possibilities for energy saving on node and network level. The aim therefore is to provide deep insight into system design and increase awareness of suitable techniques for realizing battery-free and energy-aware wireless sensor nodes.

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Section: Energy Managementmentioning

confidence: 99%

Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review

Kanoun

Bradai

Khriji

et al. 2021

Sensors

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“…Connectivity problems, therefore, arise over time, which can lead to a high latency and subsequently low Quality of Service (QoS). As a result, the power cost of the activation of its processing unit during the operations performed or when reading/writing in memory must be optimized [ 2 ].…”

Section: Survey Of Energy Optimization Approaches In Wsnsmentioning

confidence: 99%

“…Wireless Sensor Networks (WSNs) set a very real benchmark for the Internet of Things (IoT) by using the recent technologies to optimize communication and safety systems in hazardous environments [ 1 , 2 , 3 ]. Thanks to the advantages offered by these technologies, in particular, collecting data in real time with a low cost, WSNs are gaining popularity in several fields of applications such as tele-surgery, intelligent transportation, smart home, industrial control, business sector, virtual reality, law enforcement [ 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

“…WSNs have to be highly flexible, scalable, interoperable, and reliable. Furthermore, different challenges need to be addressed including improving the energy efficiency, contributing to environmental monitoring and enhancing social services [ 2 ]. Indeed, having low power consumption is the primary driver behind the long flow of independent battery-powered devices and to reduce the maintenance cost as most of the nodes are deployed in unattended places.…”

Section: Introductionmentioning

confidence: 99%

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Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks

Chéour

Jmal

Khriji

et al. 2021

Sensors

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Wireless Sensor Networks (WSNs) are prone to highly constrained resources, as a result ensuring the proper functioning of the network is a requirement. Therefore, an effective WSN management system has to be integrated for the network efficiency. Our objective is to model, design, and propose a homogeneous WSN hybrid architecture. This work features a dedicated power utilization optimization strategy specifically for WSNs application. It is entitled Hybrid Energy-Efficient Power manager Scheduling (HEEPS). The pillars of this strategy are based on the one hand on time-out Dynamic Power Management (DPM) Intertask and on the other hand on Dynamic Voltage and Frequency Scaling (DVFS). All tasks are scheduled under Global Earliest Deadline First (GEDF) with new scheduling tests to overcome the Dhall effect. To minimize the energy consumption, the HEEPS predicts, defines and models the behavior adapted to each sensor node, as well as the associated energy management mechanism. HEEPS’s performance evaluation and analysis are performed using the STORM simulator. A comparison to the results obtained with the various state of the art approaches is presented. Results show that the power manager proposed effectively schedules tasks to use dynamically the available energy estimated gain up to 50%.

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“…In fact, the IoT is supported by an alliance of key assets, including the massive proliferation of smart devices, the confluence of low-cost technologies such as sensors, large amount of data (Big Data), High Performance Computing capabilities (HPC) and Wireless Sensor Networks (WSNs) [6][7][8]. In the context of WSNs, the cloud architecture is designed to monitor, control and record many wireless sensor nodes [9,10]. For this reason, it needs to host massive amount of continuously generated data and satisfies numerous competing analytical requests.…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of a cloud-based event-driven architecture for real-time data processing in wireless sensor networks

et al. 2021

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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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Microcontrollers for IoT: Optimizations, Computing Paradigms, and Future Directions

Cited by 24 publications

References 29 publications

Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review

Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review

Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks

Design and implementation of a cloud-based event-driven architecture for real-time data processing in wireless sensor networks

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