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With the increasing size and complexity of embedded systems, the impact of software on energy consumption is becoming more important. Previous research focused mainly on energy optimization at the hardware level. However, little research has been carried out regarding energy optimization at the software design level. This paper focuses on the software design level and addresses the gap between software and hardware design for embedded systems. This is achieved by proposing a framework for software design patterns, which takes aspects of power consumption and time behavior of the hardware level into account. We evaluate the expressiveness of the framework by applying it to well-known and novel design patterns. Furthermore, we introduce a dimensionless numerical efficiency factor to make possible energy savings quantifiable.
Driven by the success of Internet of Things, the number of embedded systems is constantly increasing. Reducing power consumption and improving energy efficiency are among the key challenges for battery-powered embedded systems. Additionally, threats like climate change clearly illustrate the need for systems with low resource usages. Due to the impact of software applications on the system’s power consumption, it is important to optimize the software design even in early development phases. The important role of the software layer is often overlooked because energy consumption is commonly associated with the hardware layer. As a result, existing research mainly focuses on energy optimization at the hardware level, while only limited research has been published on energy optimization at the software design level. This work presents a novel approach to propose an energy-aware software design pattern framework description, which takes power consumption and time behavior into account. We evaluate the expressiveness of the framework by defining design patterns, which use elaborated power-saving strategies for various hardware components to reduce the overall energy consumption of an embedded system. Furthermore, we introduce a dimensionless numerical efficiency factor to make energy savings quantifiable and a comparison for design patterns applied in various use cases possible.
Dieser Beitrag vergleicht die Nutzbarkeit der Funkstandards Narrowband-IoT (NB-IoT) und Long Range Wide Area Network (LoRaWAN) zur Datenübertragung von Sensoren, die in den Boden eingebracht sind. Zur Messung der Empfangsqualität wurde jeweils ein mit den Funktechnologien ausgestattetes Sensorboard in Tiefen von bis zu 60 cm in eine landwirtschaftliche Fläche eingebracht und wieder mit Erdreich bedeckt. Dabei wurden Signalstärke (RSSI) und Signal-Rausch-Abstand (SNR) ermittelt. Die Ergebnisse zeigen, dass sowohl NB-IoT als auch LoRaWAN eine ausreichende Bodendurchdringung besitzen und damit eine zuverlässige Kommunikation mit Bodensensoren ermöglichen. Die Auswahl kann abhängig von der Komplexität des Anwendungsszenarios und dem Kostenaufwand erfolgen. Kombiniert mit einer energieeffizienten Elektronik und passender Bodensensorik sind bei vertretbarem Kostenrahmen neue Einsatzgebiete für Precision-Farming erschließbar.
Due to the lack of mobile infrastructure in rural areas, a lot of modern technologies can't be used effciently. With Long Range (LoRa) and Long Range Wide Area Network (LoRaWAN), there are new concepts for wireless long-range communication which have been established. They enable a modern technical solution to communicate in rural areas, where current mobile network coverage is missing. This paper investigates LoRaWAN for agriculture-based use cases. Hence, two use cases were evaluated. In the first use case, the temperature of a horse stable was measured and transmitted by taking the minimal use of the radio channel into account. In the second use case, a self-developed device was buried into the agriculture land at a depth of 10 down to 60 cm to analyze the soil properties and test the permeability of agriculture land. Additionally, a server and gateway architecture with access to a cloud system for data processing purposes was designed and in a second step, a low power prototype with different sensors for data collection for the described use cases was developed. The main benefit of this paper is the evaluation of LoRaWAN for the use in indoor and outdoor applications for agricultural businesses. The presented results are the first step for area-wide real-time monitoring of important agriculture data in rural areas which enables the precision reaction to physical changes.
Rapid-Prototyping and Early Validation of Software Models through Uniform Integration of Hardware
(2023)
Due to the resource-constrained nature of embedded systems, it is crucial to support the estimation of their power consumption as early in the development process as possible. Non-functional requirements based on power consumption directly impact the software design, e.g., watt-hour thresholds and expected lifetimes based on battery capacities. Even if software affects hardware behavior directly, these types of requirements are often overlooked by software developers because they are commonly associated with the hardware layer. Modern trends in software engineering such as Model-Driven Development (MDD) can be used in embedded software development to evaluate power consumption-based requirements in early design phases. However, power consumption aspects are currently not sufficiently considered in MDD approaches. In this paper, we present a model-driven approach using Unified Modeling Language profile extensions to model hardware components and their power characteristics. Software m odels are combined with hardware models to achieve a system-wide estimation, including peripheral devices, and to make the power-related impact in early design stages visible. By deriving energy profiles, we provide software developers with valuable feedback, which may be used to identify energy bugs and evaluate power consumption-related requirements. To demonstrate the potential of our approach, we use a sensor node example to evaluate our concept and to identify its energy bugs.