Intelligence distribution for data processing in smart grids: A semantic approach

Nieves, Juan Carlos; Espinoza, Angelina; Penya, Yoseba K.; Mues, Mariano Ortega de; Pena, Aitor

doi:10.1016/j.engappai.2013.03.016

Cited by 16 publications

(5 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A possible way to achieve this is supporting the open standard agent communication language FIPA ACL 24 . However, as highlighted in a previous publication [14], FIPA ACL does not support communication approaches that have emerged as best practices for real-time distributed systems like publishsubscribe. Also, the application of JS-son in a distributed context can benefit from the enhancement of agent-internal behavior, for example through a feature that supports the asynchronous execution of plans.…”

Section: Discussionmentioning

confidence: 99%

“…The provision of serverless computing services is often referred to as Function-as-a-Service (FaaS). Most FaaS providers, like Heroku 13 , Amazon Web Services Lamda 14 , and Google Cloud Functions 15 , provide Node.js support for their service offerings and allow for the deployment of JavaScript functions with little setup overhead. Consequently, JS-son can emerge as a convenient tool to develop agents and multi-agent systems that are then deployed as serverless functions.…”

Section: Potential Use Casesmentioning

confidence: 99%

See 1 more Smart Citation

JS-son -- A Lean, Extensible JavaScript Agent Programming Library

Kampik¹,

Nieves²

2020

Preprint

Self Cite

View full text Add to dashboard Cite

A multitude of agent-oriented software engineering frameworks exist, most of which are developed by the academic multi-agent systems community. However, these frameworks often impose programming paradigms on their users that are challenging to learn for engineers who are used to modern high-level programming languages such as JavaScript and Python. To show how the adoption of agent-oriented programming by the software engineering mainstream can be facilitated, we provide a lean JavaScript library prototype for implementing reasoning-loop agents. The library focuses on core agent programming concepts and refrains from imposing further restrictions on the programming approach. To illustrate its usefulness, we show how the library can be applied to multi-agent systems simulations on the web, deployed to cloud-hosted function-as-a-service environments, and embedded in Python-based data science tools.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Potential Use Casesmentioning

confidence: 99%

JS-son -- A Lean, Extensible JavaScript Agent Programming Library

Kampik¹,

Nieves²

2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…We adopted CIM [ 29 ] because it provides high expressiveness for modeling, for management purposes, information systems, applications, and networks [ 30 ]. We used OWL [ 31 ] because it enables reasoning in the model and the sharing of knowledge among software agents [ 32 ]. In particular, SIM uses OWL classes and properties to characterize HM entirely by modeling the information domains and their relationships.…”

Section: Sim-knowmentioning

confidence: 99%

A Semantic and Knowledge-Based Approach for Handover Management

Vivas

Rendón

Nieves

2021

Sensors

Self Cite

View full text Add to dashboard Cite

Handover Management (HM) is pivotal for providing service continuity, enormous reliability and extreme-low latency, and meeting sky-high data rates, in wireless communications. Current HM approaches based on a single criterion may lead to unnecessary and frequent handovers due to a partial network view that is constrained to information about link quality. In turn, HM approaches based on multicriteria may present a failure of handovers and wrong network selection, decreasing the throughput and increasing the packet loss in the network. This paper proposes SIM-Know, an approach for improving HM. SIM-Know improves HM by including a Semantic Information Model (SIM) that enables context-aware and multicriteria handover decisions. SIM-Know also introduces a SIM-based distributed Knowledge Base Profile (KBP) that provides local and global intelligence to make contextual and proactive handover decisions. We evaluated SIM-Know in an emulated wireless network. When the end-user device moves at low and moderate speeds, the results show that our approach outperforms the Signal Strong First (SSF, single criterion approach) and behaves similarly to the Analytic Hierarchy Process combined with the Technique for Order Preferences by Similarity to the Ideal Solution (AHP-TOPSIS, multicriteria approach) regarding the number of handovers and the number of throughput drops. SSF outperforms SIM-Know and AHP-TOPSIS regarding the handover latency metric because SSF runs a straightforward process for making handover decisions. At high speeds, SIM-Know outperforms SSF and AHP-TOPSIS regarding the number of handovers and the number of throughput drops and, further, improves the throughput, delay, jitter, and packet loss in the network. Considering the obtained results, we conclude that SIM-Know is a practical and attractive solution for cognitive HM.

show abstract

“…This section presents the CQ-Driven Ontology DEsign Process (CODEP), which is driven by end-users CQs. CODEP has been inspired by taking proved practices from ontology designing experiences in three previous projects ( (Espinoza, Abi-Lahoud, & Butler, 2014), (Nieves, Espinoza, Penya, Ortega De Mues, & Peña, 2013), (Espinoza, et al, 2013)). This process is defined for creating ontologies that will be implemented in Knowledge Bases (KBs) that can be mined.…”

Section: The Cq-driven Ontology Design Processmentioning

confidence: 99%

A validation & verification driven ontology: An iterative process

Espinoza

Del-Moral

Martínez-Martínez

et al. 2021

Self Cite

View full text Add to dashboard Cite

Designing an ontology that meets the needs of end-users, e.g., a medical team, is critical to support the reasoning with data. Therefore, an ontology design should be driven by the constant and efficient validation of end-users needs. However, there is not an existing standard process in knowledge engineering that guides the ontology design with the required quality. There are several ontology design processes, which range from iterative to sequential, but they fail to ensure the practical application of an ontology and to quantitatively validate end-user requirements through the evolution of an ontology. In this paper, an ontology design process is proposed, which is driven by end-user requirements, defined as Competency Questions (CQs). The process is called CQ-Driven Ontology DEsign Process (CODEP) and it includes activities that validate and verify the incremental design of an ontology through metrics based on defined CQs. CODEP has also been applied in the design and development of an ontology in the context of a Mexican Hospital for supporting Neurologist specialists. The specialists were involved, during the application of CODEP, in collecting quality measurements and validating the ontology increments. This application can demonstrate the feasibility of CODEP to deliver ontologies with similar requirements in other contexts.

show abstract

Intelligence distribution for data processing in smart grids: A semantic approach

Cited by 16 publications

References 13 publications

JS-son -- A Lean, Extensible JavaScript Agent Programming Library

JS-son -- A Lean, Extensible JavaScript Agent Programming Library

A Semantic and Knowledge-Based Approach for Handover Management

A validation & verification driven ontology: An iterative process

Contact Info

Product

Resources

About