Tiered versus tierless IoT stacks

Lubbers, Mart; Koopman, Pieter; Ramsingh, Adrian; Singer, Jeremy; Trinder, Phil

doi:10.1145/3410992.3411002

Cited by 3 publications

(4 citation statements)

References 18 publications

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“…The current work extends (Lubbers et al, 2020) as follows. Contributions C3 and C4 are entirely new, and C1 is enhanced by being based on the analysis of four rather than two languages and implementations.…”

Section: C1mentioning

confidence: 75%

“…12. Tiered versus Tierless IoT Stacks: Comparing Smart Campus Software Architectures (Lubbers, Koopman, Ramsingh, Singer and Trinder, 2020) 6 compares traditional tiered programming to tierless architectures by comparing two implementations of a smart-campus application. The paper was published in the International Conference on the Internet of Things (IoT) 2020 in Malmö, Sweden (moved to online).…”

Section: Episode Iii: Tiered Versus Tierless Programmingmentioning

confidence: 99%

“…Funded by the Radboud-Glasgow Collaboration Fund, collaborative work was executed with Phil Trinder, Jeremy Singer, and Adrian Ravi Kishore Ramsingh. An existing smart campus application was developed using mTask and quantitatively and qualitatively compared to the original application that was developed using a traditional IoT stack (Lubbers et al, 2020). This research was later extended to include a four-way comparison: Python, MicroPython, iTask, and mTask (Lubbers et al, 2023c) (see chapter 10).…”

Section: Using Mtask In Practicementioning

confidence: 99%

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Orchestrating the Internet of Things with Task-Oriented Programming

Lubbers

2023

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The development of reliable software for the internet of things (IoT) is difficult because IoT systems are dynamic, interactive, distributed, collaborative, multi-tiered, and multitasking in nature. The complexity is increased further by semantic friction that arises through different hardware and software characteristics between tiers. Many computers that operate in IoT systems are edge devices that interact with the environment using sensors and actuators. Edge devices are often powered by low-cost microcontrollers designed for embedded applications. They have little memory, unhurried processors, and are slow in communication but are also small and energy efficient. Task-oriented programming (TOP) can cope with the challenges of IoT programming. In TOP, the main building blocks are tasks, an abstract representation of work. During execution, the current value of the task is observable, and other tasks can act upon it. Collaboration patterns can be modelled by combining and transforming tasks into compound tasks. Programming edge devices benefits from TOP as well, but running such a system within the limitations of resource-constrained microcontrollers is not straightforward. This dissertation demonstrates how to include edge devices in TOP systems using domain-specific languages (DSLs). With these techniques, all tiers and their interoperation of an IoT system are specified in a single high-level source, language, paradigm, high abstraction level, and type system. First, I present advanced DSL embedding techniques. Then mTask is shown, a TOP DSL for IoT edge devices, embedded in iTask. Tasks are constructed and compiled at run time in order to allow tasks to be tailored to the current work requirements. The task is then sent to the device for interpretation. A device is programmed once with a lightweight domain-specific OS to be used in an mTask system. This OS executes tasks in an energy-efficient way and automates all communications and data sharing. All aspects of the mTask system are shown: example applications, language design, implementation details, integration with iTask, and green computing facilities such as automatic sleeping. Finally, tierless IoT programming is compared to traditional tiered programming. In tierless programming frameworks, the size of the code and the number of required programming languages is reduced significantly. By using a single paradigm and a system-wide type system, tierless programming reduces problems such as semantic friction; maintainability and robustness issues; and interoperation safety.

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Section: C1mentioning

confidence: 75%

Section: Episode Iii: Tiered Versus Tierless Programmingmentioning

confidence: 99%

Section: Using Mtask In Practicementioning

confidence: 99%

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Orchestrating the Internet of Things with Task-Oriented Programming

Lubbers

2023

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“…To enable TOP on small microprocessors we have created mTask [10,12]. The domain-specific language mTask is also embedded in Clean.…”

Section: Mtaskmentioning

confidence: 99%

Reducing the Power Consumption of IoT with Task-Oriented Programming

Crooijmans

Lubbers

Koopman

2022

Lecture Notes in Computer Science

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Limiting the energy consumption of IoT nodes is a hot topic in green computing. For battery-powered devices this necessity is obvious, but the enormous growth of the number of IoT nodes makes energy efficiency important for every node in the IoT. In this paper, we show how we can automatically compute execution intervals for our task-oriented programs for the IoT. These intervals offer the possibility to save energy by bringing the microprocessor driving the IoT node into a low-power sleep mode until the task need to be executed. Furthermore, they offer an elegant way to add interrupts to the system. We do allow an arbitrary number of tasks on the IoT nodes and achieve significant reductions of the energy consumption by bringing the microprocessor in sleep mode as much as possible. We have seen energy reductions of an order of magnitude without imposing any constraints on the tasks to be executed on the IoT nodes.

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