COOJA/MSPSim: interoperability testing for wireless sensor networks

Eriksson, Joakim; Österlind, Fredrik; Finne, Niclas; Tsiftes, Nicolas; Dunkels, Adam; Voigt, Thiemo; Sauter, Robert; Marrón, Pedro José

doi:10.4108/icst.simutools2009.5637

Cited by 166 publications

(95 citation statements)

References 25 publications

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“…To assess this, we measure the MCU overhead for context transitions and calls to layered functions, as well as memory overhead when using CONESC as compared to nesC. To measure the MCU overhead we use the MSPSim MSP430 emulator [5], while we estimate the memory overhead using tools in the nesC and GNU-C toolchains. As the executions are determinstic, the run-time experiments constantly yield the same measures.…”

Section: E Mcu and Memory Overheadmentioning

confidence: 99%

Context-Oriented Programming for Adaptive Wireless Sensor Network Software

Afanasov

Mottola

Ghezzi

2014

2014 IEEE International Conference on Distributed Computing in Sensor Systems

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Abstract-We present programming abstractions for implementing adaptive Wireless Sensor Network (WSN) software. The need for adaptability arises in WSNs because of unpredictable environment dynamics, changing requirements, and resource scarcity. However, after about a decade of research in WSN programming, developers are still left with no dedicated support. To address this issue, we bring concepts from Context-Oriented Programming (COP) down to WSN devices. Contexts model the situations that WSN software needs to adapt to. Using COP, programmers use a notion of layered function to implement context-dependent behavioral variations of WSN code. To this end, we provide language-independent design concepts to organize the context-dependent WSN operating modes, decoupling the abstractions from their concrete implementation in a programming language. Our own implementation, called CONESC, extends nesC with COP constructs. Based on three representative applications, we show that CONESC greatly simplifies the resulting code and yields increasingly decoupled implementations compared to nesC. For example, by model-checking every function in either implementations, we show a ≈50% reduction in the number of program states that programmers need to deal with, indicating easier debugging. In our tests, this comes at the price of a maximum 2.5% (4.5%) overhead in program (data) memory.

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Section: E Mcu and Memory Overheadmentioning

confidence: 99%

Context-Oriented Programming for Adaptive Wireless Sensor Network Software

Afanasov

Mottola

Ghezzi

2014

2014 IEEE International Conference on Distributed Computing in Sensor Systems

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“…The policies are injected back into the network, where a dedicated sub-system monitors a node's state and possibly executes policies as required. The process relies on the COOJA simulator [58], which allows time-accurate executions of binary code. Because of the binary-level execution, the approach is applicable also to OSes other than Contiki.…”

Section: Toolchain and Run-time Supportmentioning

confidence: 99%

makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

Mottola

Picco

Oppermann³

et al. 2019

IIEEE Trans. Software Eng.

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Abstract-A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language-also directly usable by WSN developers-and then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype-including the complete tool-chain and underlying system support-sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions.

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“…Cooja [36] is a simulator for the Contiki operating system. It has a well-organized radio model, which supports signal reflections from walls, collisions and SNR calculation.…”

Section: State Of the Art In Rtls Designmentioning

confidence: 99%