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A Software Product Line Process to Develop Agents for the IoT.

Ayala I, Amor M, Fuentes L, Troya JM - Sensors (Basel) (2015)

Bottom Line: Our goal is to enhance the development of IoT applications using agents and software product lines (SPL).Specifically, we propose to use Self-StarMASMAS, multi-agent system) agents and to define an SPL process using the Common Variability Language.In this contribution, we propose an SPL process for Self-StarMAS, paying particular attention to agents embedded in sensor motes.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Lenguajes y Ciencias de la Computación, Andalucía Tech, Universidad de Málaga, Campus de Teatinos s/n, 29071 Málaga, Spain. ayala@lcc.uma.es.

ABSTRACT
One of the most important challenges of this decade is the Internet of Things (IoT), which aims to enable things to be connected anytime, anyplace, with anything and anyone, ideally using any path/network and any service. IoT systems are usually composed of heterogeneous and interconnected lightweight devices that support applications that are subject to change in their external environment and in the functioning of these devices. The management of the variability of these changes, autonomously, is a challenge in the development of these systems. Agents are a good option for developing self-managed IoT systems due to their distributed nature, context-awareness and self-adaptation. Our goal is to enhance the development of IoT applications using agents and software product lines (SPL). Specifically, we propose to use Self-StarMASMAS, multi-agent system) agents and to define an SPL process using the Common Variability Language. In this contribution, we propose an SPL process for Self-StarMAS, paying particular attention to agents embedded in sensor motes.

No MeSH data available.


Domain engineering of the device type concern using CVL and Unified Modeling Language (UML).
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f4-sensors-15-15640: Domain engineering of the device type concern using CVL and Unified Modeling Language (UML).

Mentions: The next step is to link (or relate) the variability model with the components of the multi-agent system architecture (i.e., the base model). This is done using bindings that link the variation points of the variability model to the UML design of the Multi-agent system architecture. We have represented binding variation points using dashed grey lines; however, this does not mean that linked architectural components or VSpecs are optional. For example, in Figure 3, the device type concern is modeled by Device Type CV CVSpec, which is linked to the Device Type CU variation point. Finally, this variation point is linked to the Device Configuration architectural component (see grey arrows in Figure 3). CVL allows dividing and modularizing the complete variability model at different levels of detail. Thus, it is possible to model each feature of the agent separately in different variability models (like in Figure 4) and, afterwards, to define a complete variability model by relating those models, including all of the features of the agents with their dependency relationships.


A Software Product Line Process to Develop Agents for the IoT.

Ayala I, Amor M, Fuentes L, Troya JM - Sensors (Basel) (2015)

Domain engineering of the device type concern using CVL and Unified Modeling Language (UML).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541848&req=5

f4-sensors-15-15640: Domain engineering of the device type concern using CVL and Unified Modeling Language (UML).
Mentions: The next step is to link (or relate) the variability model with the components of the multi-agent system architecture (i.e., the base model). This is done using bindings that link the variation points of the variability model to the UML design of the Multi-agent system architecture. We have represented binding variation points using dashed grey lines; however, this does not mean that linked architectural components or VSpecs are optional. For example, in Figure 3, the device type concern is modeled by Device Type CV CVSpec, which is linked to the Device Type CU variation point. Finally, this variation point is linked to the Device Configuration architectural component (see grey arrows in Figure 3). CVL allows dividing and modularizing the complete variability model at different levels of detail. Thus, it is possible to model each feature of the agent separately in different variability models (like in Figure 4) and, afterwards, to define a complete variability model by relating those models, including all of the features of the agents with their dependency relationships.

Bottom Line: Our goal is to enhance the development of IoT applications using agents and software product lines (SPL).Specifically, we propose to use Self-StarMASMAS, multi-agent system) agents and to define an SPL process using the Common Variability Language.In this contribution, we propose an SPL process for Self-StarMAS, paying particular attention to agents embedded in sensor motes.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Lenguajes y Ciencias de la Computación, Andalucía Tech, Universidad de Málaga, Campus de Teatinos s/n, 29071 Málaga, Spain. ayala@lcc.uma.es.

ABSTRACT
One of the most important challenges of this decade is the Internet of Things (IoT), which aims to enable things to be connected anytime, anyplace, with anything and anyone, ideally using any path/network and any service. IoT systems are usually composed of heterogeneous and interconnected lightweight devices that support applications that are subject to change in their external environment and in the functioning of these devices. The management of the variability of these changes, autonomously, is a challenge in the development of these systems. Agents are a good option for developing self-managed IoT systems due to their distributed nature, context-awareness and self-adaptation. Our goal is to enhance the development of IoT applications using agents and software product lines (SPL). Specifically, we propose to use Self-StarMASMAS, multi-agent system) agents and to define an SPL process using the Common Variability Language. In this contribution, we propose an SPL process for Self-StarMAS, paying particular attention to agents embedded in sensor motes.

No MeSH data available.