Context- and Template-Based Compression for Efficient Management of Data Models in Resource-Constrained Systems
dc.contributor.author | Berzosa Macho, Jorge | |
dc.contributor.author | Gardeazabal Montón, Pedro José Luis | |
dc.contributor.author | Cortiñas Rodríguez, Roberto | |
dc.date.accessioned | 2018-05-31T14:54:52Z | |
dc.date.available | 2018-05-31T14:54:52Z | |
dc.date.issued | 2017-08 | |
dc.identifier.citation | Sensors 17(8) : (2017) // Article ID 1755 | es_ES |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/10810/27253 | |
dc.description.abstract | The Cyber Physical Systems (CPS) paradigm is based on the deployment of interconnected heterogeneous devices and systems, so interoperability is at the heart of any CPS architecture design. In this sense, the adoption of standard and generic data formats for data representation and communication, e.g., XML or JSON, effectively addresses the interoperability problem among heterogeneous systems. Nevertheless, the verbosity of those standard data formats usually demands system resources that might suppose an overload for the resource-constrained devices that are typically deployed in CPS. In this work we present Context-and Template-based Compression (CTC), a data compression approach targeted to resource-constrained devices, which allows reducing the resources needed to transmit, store and process data models. Additionally, we provide a benchmark evaluation and comparison with current implementations of the Efficient XML Interchange (EXI) processor, which is promoted by the World Wide Web Consortium (W3C), and it is the most prominent XML compression mechanism nowadays. Interestingly, the results from the evaluation show that CTC outperforms EXI implementations in terms of memory usage and speed, keeping similar compression rates. As a conclusion, CTC is shown to be a good candidate for managing standard data model representation formats in CPS composed of resource-constrained devices. | es_ES |
dc.description.sponsorship | Research partially supported by the European Union Horizon 2020 Programme under Grant Agreement Number H2020-EeB-2015/680708 - HIT2GAP, Highly Innovative building control Tools Tackling the energy performance GAP. Also partially supported by the Department of Education, Universities and Research of the Basque Government under Grant IT980-16 and the Spanish Research Council, under grant TIN2016-79897-P. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/680708 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | cyber physical systems | es_ES |
dc.subject | data models | es_ES |
dc.subject | compression | es_ES |
dc.subject | resource-constrained devices | es_ES |
dc.subject | ad hoc networks | es_ES |
dc.subject | Wireless Sensor Networks (WSN) | es_ES |
dc.title | Context- and Template-Based Compression for Efficient Management of Data Models in Resource-Constrained Systems | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | http://www.mdpi.com/1424-8220/17/8/1755 | es_ES |
dc.identifier.doi | 10.3390/s17081755 | |
dc.contributor.funder | European Commission | |
dc.departamentoes | Arquitectura y Tecnología de Computadores | es_ES |
dc.departamentoes | Tecnología electrónica | es_ES |
dc.departamentoeu | Konputagailuen Arkitektura eta Teknologia | es_ES |
dc.departamentoeu | Teknologia elektronikoa | es_ES |
Files in this item
This item appears in the following Collection(s)
Except where otherwise noted, this item's license is described as 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).