A Software Product Line Process to Develop Agents for the IoT

Ayala, Inmaculada; Amor, Mercedes; Fuentes, Lidia; Troya, José M.

doi:10.3390/s150715640

Cited by 37 publications

(31 citation statements)

References 33 publications

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“…A software product line (SPL) [20]- [25] [41] [42] is a set of software intensive systems that share a common and managed set of features satisfying the specific needs of a particular market segment developed from a common set of core assets in a prescribed way [21] [23]. SPL engineering aims at: effective utilization of software assets, reducing the time required to deliver a product, improving quality, and decreasing the cost of software products.…”

Section: Literature Reviewmentioning

confidence: 99%

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

Brisebois¹,

Abran²,

Nadembéga³

2017

JSEA

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Software industry has evolved to multi-product and multi-platform development based on a mix of proprietary and open source components. Such integration has occurred in software ecosystems through a software product line engineering (SPLE) process. However, metadata are underused in the SPLE and interoperability challenge. The proposed method is first, a semantic metadata enrichment software ecosystem (SMESE) to support multi-platform metadata driven applications, and second, based on mapping ontologies SMESE aggregates and enriches metadata to create a semantic master metadata catalogue (SMMC). The proposed SPLE process uses a component-based software development approach for integrating distributed content management enterprise applications, such as digital libraries. To perform interoperability between existing metadata models (such as Dublin Core, UNIMARC, MARC21, RDF/RDA and BIBFRAME), SMESE implements an ontology mapping model. SMESE consists of nine sub-systems: 1) Metadata initiatives & concordance rules; 2) Harvesting of web metadata & data; 3) Harvesting of authority metadata & data; 4) Rule-based semantic metadata external enrichment; 5) Rule-based semantic metadata internal enrichment; 6) Semantic metadata external & internal enrichment synchronization; 7) User interest-based gateway; 8) Semantic master catalogue. To conclude, this paper proposes a decision support process, called SPLE decision support process (SPLE-DSP) which is then used by SMESE to support dynamic reconfiguration. SPLE-DSP consists of a dynamic and optimized metadata-based reconfiguration model. SPLE-DSP takes into account runtime metadata-based variability functionalities, context-awareness and self-adaptation. It also presents the design and implementation of a working prototype of SMESE applied to a semantic digital library.

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Section: Literature Reviewmentioning

confidence: 99%

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

Brisebois¹,

Abran²,

Nadembéga³

2017

JSEA

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“…In regards engineering approaches, aspect-oriented agents are jointly used with a Common Variability Language within a Software Product Line process in [9]. Their goal is to provide a 4 http://www.oracle.com/technetwork/java/embedded/overview/index.html reusable approach for development of IoT application focusing in self-management and heterogeneity.…”

Section: Performance Assessmentmentioning

confidence: 99%

Towards a Software Framework for the Autonomous Internet of Things

Hernández

Reiff-Marganiec

2016

2016 IEEE 4th International Conference on Future Internet of Things and Cloud (FiCloud)

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Abstract-IoT promises a world where Smart Objects (SO) are able to autonomously communicate and work together to make the (human) user's life easier. Popular approaches for development of IoT applications take for granted that on-object resources are evenly constrained. As consequence, we observe a trend towards a data-feeder architecture in which "smart objects" are simple data gatherers and senders. Raw data is stored and processed in cloud platforms feeding web applications and services. The autonomy of SO is then compromised as they are not able to operate without these platforms. We propose a framework and architecture for the development of IoT applications where smart objects exhibit autonomy in regards platforms and human users. We completed the successful evaluation of our proposal with the implementation of a prototype and the execution of a use case for physical resources provisioning.

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“…1) follows the two life cycles schema of SPL processes that separates domain (DomE) and application (AppE) engineering. The DomE of our process (defined in [3]) analyzes the SPL for MASs in the IoT as a whole to define and produce the commonality and the variability of the SPL (see 2). The second process, the AppE, involves creating and configuring the architecture of agents, which are built by reusing domain artifacts and exploiting SPL engineering.…”

Section: Our Approachmentioning

confidence: 99%

“…1) of our SPL process relies on the use of CVL and the Unified Modeling Language (UML) as MOF-based language. In [3] we defined the global variability model and architecture of the MAS for the IoT (see Fig. 2).…”

Section: Domain Engineering Of the Self-adaptation Concernmentioning

confidence: 99%

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Using SPL to Develop AAL Systems Based on Self-adaptive Agents

Ayala¹,

Amor²,

Fuentes³

2016

Advances in Intelligent Systems and Computing

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Abstract. One of the most important challenges of this decade is the Internet of Things (IoT) that pursues the integration of real-world objects in Internet. One of the key areas of the IoT is the Ambient Assisted Living (AAL) systems, which should be able to react to variable and continuous changes while ensuring their acceptance and adoption by users. This means that AAL systems need to work as self-adaptive systems. The autonomy property inherent to software agents, makes them a suitable choice for developing self-adaptive systems. However, agents lack the mechanisms to deal with the variability present in the IoT domain with regard to devices and network technologies. To overcome this limitation we have already proposed a Software Product Line (SPL) process for the development of self-adaptive agents in the IoT. Here we analyze the challenges that poses the development of self-adaptive AAL systems based on agents. To do so, we focus on the domain and application engineering of the self-adaptation concern of our SPL process. In addition, we provide a validation of our development process for AAL systems.

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A Software Product Line Process to Develop Agents for the IoT

Cited by 37 publications

References 33 publications

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

Towards a Software Framework for the Autonomous Internet of Things

Using SPL to Develop AAL Systems Based on Self-adaptive Agents

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