ORCID Profile
0000-0002-3543-2909
Current Organisation
Université de Pau et des Pays de l'Adour
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Publisher: IEEE Comput. Soc
Date: 2004
Publisher: Springer Science and Business Media LLC
Date: 10-10-2008
Publisher: Elsevier BV
Date: 05-2010
Publisher: Ital Publication
Date: 23-08-2021
Abstract: Modern IT technologies shaped the shift in economic models with many advantages on cost, optimization, and time to market. This economic shift has increased the need for transparency and traceability in supply chain platforms to achieve trust among partners. Distributed ledger technology (DLT) is proposed to enable supply chains systems with trust requirements. In this paper, we investigate the existing DLT-based supply chain projects to show their technical part and limitations and extract the tools and techniques used to avoid the DLT scalability issue. We then set the requirements for a typical DLT-based supply chain in this context. The analyses are based on the scalability metrics such as computing, data storage, and transaction fees that fit the typical supply chain system. This paper highlights the effects of Blockchain techniques on scalability and their incorporation in supply chains systems. It also presents other existing solutions that can be applied to the supply chain. The investigation shows the necessity of having such tools in supply chains and developing them to achieve an efficient and scalable system. The paper calls for further scalability enhancements throughout introducing new tools and/or reutilize the current ones. Doi: 10.28991/esj-2021-SP1-04 Full Text: PDF
Publisher: IEEE
Date: 2005
Publisher: Springer Berlin Heidelberg
Date: 2015
Publisher: ACM
Date: 05-12-2011
Publisher: IEEE
Date: 10-2021
Publisher: Informa UK Limited
Date: 06-02-2019
Publisher: Inderscience Publishers
Date: 2010
Publisher: Elsevier BV
Date: 09-2020
Publisher: IEEE
Date: 08-2019
Publisher: Springer International Publishing
Date: 2019
Publisher: IEEE
Date: 03-2017
Publisher: Institution of Engineering and Technology (IET)
Date: 12-2017
Publisher: ACM
Date: 07-11-2017
Publisher: IEEE
Date: 03-2013
Publisher: IEEE
Date: 2010
Publisher: IEEE
Date: 03-2012
Publisher: IEEE
Date: 12-2012
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Springer Science and Business Media LLC
Date: 06-09-2022
Publisher: IEEE
Date: 06-2012
Publisher: IEEE
Date: 11-2009
Publisher: Springer International Publishing
Date: 2017
Publisher: Springer International Publishing
Date: 2021
Publisher: ACM
Date: 26-06-2006
Publisher: Association for Computing Machinery (ACM)
Date: 30-11-2018
DOI: 10.1145/3166070
Abstract: The adoption of the Internet of Things (IoT) drastically witnesses an increase in different domains and contributes to the fast digitalization of the universe. Henceforth, next generation of IoT-based systems are set to become more complex to design and manage. Collecting real-time IoT-generated data unleashes a new wave of opportunities for business to take more precise and accurate decisions at the right time. However, a set of challenges, including the design complexity of IoT-based systems and the management of the ensuing heterogeneous big data as well as the system scalability, need to be addressed for the development of flexible smart IoT-based systems. Consequently, we proposed a set of design patterns that diminish the system design complexity through selecting the appropriate combination of patterns based on the system requirements. These patterns identify four maturity levels for the design and development of smart IoT-based systems. In this article, we are mainly dealing with the system design complexity to manage the context changeability at runtime. Thus, we delineate the autonomic cognitive management pattern, which is at the most mature level. Based on the autonomic computing, this pattern identifies a combination of management processes able to continuously detect and manage the context changes. These processes are coordinated based on cognitive mechanisms that allow the system perceiving and understanding the meaning of the received data to make business decisions, as well as dynamically discovering new processes that meet the requirements evolution at runtime. We demonstrated the use of the proposed pattern with a use case from the healthcare domain more precisely, the patient comorbidity management based on wearables.
Publisher: Institution of Engineering and Technology (IET)
Date: 08-2016
Publisher: Universidad Nacional de Colombia
Date: 07-2018
DOI: 10.15446/DYNA.V85N206.68671
Abstract: SOA (Service Oriented Architecture) ha emergido como una arquitectura dominante para la interoperabilidad entre aplicaciones, por medio de un modelo de acoplamiento débil basado en la flexibilidad que proveen los servicios web, esto ha dado lugar a una lia gama de aplicaciones, en lo que se conoce hoy en día como computación en la nube. Por otro lado, los MAS (Multiagent System, por sus siglas en inglés) son usados liamente en la industria, ya que brindan soluciones apropiadas a problemas complejos, de forma proactiva e inteligente. En particular, los Ambientes Inteligentes (AmI) educativos se benefician de estás dos arquitecturas, ya que por un lado los MAS dotan al AmI de inteligencia, mientras que SOA permite a los usuarios interactuar con servicios académicos en la nube. El propósito de este artículo es proponer una arquitectura de integración bidireccional SOA-MAS para AmI educativos. La solución propuesta aprovecha las ventajas de ambas tecnologías (SOA-MAS), y resuelve problemas de integración planteados en investigaciones previas.
Publisher: IEEE
Date: 12-2017
Publisher: Wiley
Date: 2010
Publisher: IEEE
Date: 10-2021
Publisher: Informa UK Limited
Date: 25-06-2020
Publisher: Springer Science and Business Media LLC
Date: 25-02-2016
Publisher: IEEE
Date: 05-2015
Publisher: IEEE
Date: 06-2013
Publisher: IEEE
Date: 10-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Publisher: IEEE
Date: 2006
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Publisher: KSI Research Inc. and Knowledge Systems Institute Graduate School
Date: 07-2016
Publisher: IEEE
Date: 07-2018
Publisher: IEEE
Date: 06-2012
Publisher: Springer International Publishing
Date: 13-08-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Springer Science and Business Media LLC
Date: 14-08-2018
Publisher: Wiley
Date: 17-12-2013
Publisher: IEEE
Date: 06-2013
Publisher: Informa UK Limited
Date: 07-01-2023
Publisher: IEEE
Date: 12-2010
Publisher: Elsevier BV
Date: 02-2009
Publisher: IEEE
Date: 05-2007
Publisher: Springer Science and Business Media LLC
Date: 21-10-2015
DOI: 10.1007/S10916-015-0344-X
Abstract: Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients' health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The ersity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the "Knowledge as a Service" approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status.
Publisher: Springer International Publishing
Date: 2019
Publisher: IEEE
Date: 2005
Publisher: IEEE
Date: 09-2020
Publisher: Springer Science and Business Media LLC
Date: 24-08-2017
Publisher: IEEE
Date: 2005
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2013
DOI: 10.1109/TC.2012.130
Publisher: ACM Press
Date: 2005
Publisher: MDPI AG
Date: 02-07-2021
Abstract: Data transparency is essential in the modern supply chain to improve trust and boost collaboration among partners. In this context, Blockchain is a promising technology to provide full transparency across the entire supply chain. However, Blockchain was originally designed to provide full transparency and uncontrolled data access. This leads many market actors to avoid Blockchain as they fear for their confidentiality. In this paper, we highlight the requirements and challenges of supply chain transparency. We then investigate a set of supply chain projects that tackle data transparency issues by utilizing Blockchain in their core platform in different manners. Furthermore, we analyze the projects’ techniques and the tools utilized to customize transparency. As a result of the projects’ analyses, we identified that further enhancements are needed to set a balance between the data transparency and process opacity required by different partners, to ensure the confidentiality of their processes and to control access to sensitive data.
Publisher: Emerald
Date: 23-11-2012
DOI: 10.1108/17427371211283001
Abstract: The goal of this paper is to provide contributions aimed at illustrating how the autonomic computing concept may be applied within a multi‐path transport protocol called multi‐path TCP (MPTCP) with the aim of providing as high as possible a quality of service (QoS) for mobile and multimedia applications. The paper's general vision is to define how to use the general IBM Autonomic framework for the design of a new and generic autonomous transport layer aimed at fitting as best as possible both QoS requirements and network constraints. Several QoS‐aware mechanisms are proposed and evaluated and an ontology‐based semantic model for the dynamic discovery of MPTCP mechanisms is also presented. This work was done within the A2NETS project funded by the ITEA 2 program, a strategic pan‐European program for advanced pre‐competitive research and development (R& D). A2NETS aims at developing a set of common services for M2M devices communicating within heterogeneous networks. The originality of this paper is the study of the QoS benefits induced by the implementation of the “partial reliability” concept in MPTCP for interactive video applications based on the codec H.264. The second contribution of the paper is that it deals with the decision process that has to be enforced to provide such an adaptable MPTCP with self‐autonomic capabilities. Towards this goal, a semantic ontology‐based model has been proposed allowing to classify and to define clearly the semantic of the different QoS‐oriented mechanisms that have been proposed for MPTCP. This ontology is aimed at being used by the autonomic manager during the decision process step.
Publisher: MDPI AG
Date: 09-07-2021
DOI: 10.3390/S21144703
Abstract: IOTA is a distributed ledger technology (DLT) platform proposed for the internet of things (IoT) systems in order to tackle the limitations of Blockchain in terms of latency, scalability, and transaction cost. The main concepts used in IOTA to reach this objective are a directed acyclic graph (DAG) based ledger, called Tangle, used instead of the chain of blocks, and a new validation mechanism that, instead of relying on the miners as it is the case in Blockchain, relies on participating nodes that cooperate to validate the new transactions. Due to the different IoT capabilities, IOTA classifies these devices into full and light nodes. The light nodes are nodes with low computing resources which seek full nodes’ help to validate and attach its transaction to the Tangle. The light nodes are manually connected to the full nodes by using the full node IP address or the IOTA client load balancer. This task distribution method overcharges the active full nodes and, thus, reduces the platform’s performance. In this paper, we introduce an efficient mechanism to distribute the tasks fairly among full nodes and hence achieve load balancing. To do so, we consider the task allocation between the nodes by introducing an enhanced resource allocation scheme based on the weight least connection algorithm (WLC). To assess its performance, we investigate and test different implementation scenarios. The results show an improved balancing of data traffic among full nodes based on their weights and number of active connections.
Publisher: Elsevier BV
Date: 10-2020
Publisher: Elsevier BV
Date: 07-2008
Publisher: ACM
Date: 02-09-2005
Publisher: IEEE
Date: 06-2018
Publisher: IGI Global
Date: 2016
DOI: 10.4018/978-1-4666-9834-5.CH008
Abstract: Decision-making in disaster management requires information gathering, sharing, and integration by means of collaboration on a global scale and across governments, industries, and communities. Large volume of heterogeneous data is available however, current data management solutions offer few or no integration capabilities and limited potential for collaboration. Moreover, recent advances in NoSQL, cloud computing, and Big Data open the door for new solutions in disaster data management. This chapter presents a Knowledge as a Service (KaaS) framework for disaster cloud data management (Disaster-CDM), with the objectives of facilitating information gathering and sharing storing large amounts of disaster-related data and facilitating search and supporting interoperability and integration. In the Disaster-CDM approach NoSQL data stores provide storage reliability and scalability while service-oriented architecture achieves flexibility and extensibility. The contribution of Disaster-CDM is demonstrated by integration capabilities, on ex les of full-text search and querying services.
Publisher: IEEE
Date: 03-2013
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: IEEE
Date: 09-2020
Publisher: IEEE
Date: 2007
DOI: 10.1109/MUE.2007.24
Publisher: Springer US
Date: 2008
Publisher: Elsevier BV
Date: 08-2008
Publisher: IEEE
Date: 02-2018
Publisher: Elsevier BV
Date: 2016
Publisher: IEEE
Date: 06-2012
Publisher: IEEE
Date: 10-2013
Publisher: IEEE
Date: 2005
DOI: 10.1109/MMMC.2005.27
Publisher: Elsevier BV
Date: 05-2020
Publisher: Elsevier BV
Date: 09-2016
Publisher: Elsevier BV
Date: 06-2017
Publisher: IEEE
Date: 05-2013
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Springer Nature Switzerland
Date: 2023
Publisher: Wiley
Date: 17-06-2014
Publisher: Elsevier BV
Date: 04-2008
Publisher: Elsevier BV
Date: 2023
Publisher: Springer International Publishing
Date: 2014
Publisher: IEEE
Date: 12-2013
No related grants have been discovered for Ernesto Exposito.