Uma Abordagem Dataflow para Processamento Contextual na Internet das Coisas
Resumo
O objetivo deste trabalho é a concepção de uma arquitetura voltada para a composição de fluxos de processamento contextuais, provendo ciência de situação para aplicações na IoT. Este trabalho explora o uso de uma abordagem de programação dataflow integrada ao middleware EXEHDA. Como forma de avaliação da arquitetura, foi executado um estudo de caso na área da saúde.
Referências
Bellavista, P., Corradi, A., Fanelli, M., and Foschini, L. (2012). A survey of context data distribution for mobile ubiquitous systems. ACM Computing Surveys, 44(4):1–45.
Bibri, S. E. (2015). The Human Face of Ambient Intelligence, volume 9.
Chihani, B., Bertin, E., and Crespi, N. (2014). Programmable context awareness framework. Journal of Systems and Software, 92(1):59–70.
Fielding, R. T. (2000). Architectural Styles and the Design of Network-based Software Architectures. PhD thesis, University of California.
Forkan, A., Khalil, I., and Tari, Z. (2014). CoCaMAAL: A cloud-oriented context-aware middleware in ambient assisted living. Future Generation Computer Systems, 35:114–127.
Khodadadi, F., Dastjerdi, A. V., and Buyya, R. (2015). Simurgh: A framework for effective discovery, programming, and integration of services exposed in IoT. Recent Advances in Internet of Things (RIoT), 2015 International Conference on, (April):1–6.
Kwapisz, J. R., Weiss, G. M., and Moore, S. a. (2011). Activity recognition using cell phone accelerometers. ACM SIGKDD Explorations Newsletter, 12:74.
Lara, O. D. and Labrador, M. a. (2012). A Survey on Human Activity Recognition using Wearable Sensors. IEEE Communications Surveys & Tutorials, pages 1–18.
Lopes, J., Souza, R., Geyer, C., Costa, C., Barbosa, J., and Augustin, I. (2014). A middleware architecture for context-aware adaptation in. Journal of Universal Computer Science, 20(9):1327–1351.
Negrão, C. E. and Barreto, A. C. P. (2010). Cardiologia do Exercício: do Atleta ao Cardiopata. Manole, Barueri, SP - Brazil, 3 edition.
Perera, C., Zaslavsky, A., Christen, P., and Georgakopoulos, D. (2013). Context Aware Computing for The Internet of Things : A Survey. IEEE COMMUNICATIONS SURVEYS & TUTORIALS, X(X):1–41.
Rabelo, D., Gil, C., and Araújo, S. D. (2006). Reabilitação cardíaca com ênfase no exercício: uma revisão sistemática. Revista Brasileira de Medicina do Esporte, 12(5):279–285.
Shaw, I. and Simões, M. (2007). Controle e Modelagem Fuzzy. 2 edition.
Sobrevilla, P. and Montseny, E. (2003). Fuzzy Sets in Computer Vision : an Overview. Mathw. Soft Computing, 10:71–83.
Sousa, T. B. (2012). Dataflow programming concept, languages and applications. In Doctoral Symposium on Informatics Engineering, number January.
Ye, J., Dobson, S., and McKeever, S. (2012). Situation identification techniques in pervasive computing: A review. Pervasive and Mobile Computing, 8(1):36–66.
Yuan, B. and Herbert, J. (2014). Context-aware hybrid reasoning framework for pervasive healthcare. Personal and Ubiquitous Computing, 18(4):865–881.
Bibri, S. E. (2015). The Human Face of Ambient Intelligence, volume 9.
Chihani, B., Bertin, E., and Crespi, N. (2014). Programmable context awareness framework. Journal of Systems and Software, 92(1):59–70.
Fielding, R. T. (2000). Architectural Styles and the Design of Network-based Software Architectures. PhD thesis, University of California.
Forkan, A., Khalil, I., and Tari, Z. (2014). CoCaMAAL: A cloud-oriented context-aware middleware in ambient assisted living. Future Generation Computer Systems, 35:114–127.
Khodadadi, F., Dastjerdi, A. V., and Buyya, R. (2015). Simurgh: A framework for effective discovery, programming, and integration of services exposed in IoT. Recent Advances in Internet of Things (RIoT), 2015 International Conference on, (April):1–6.
Kwapisz, J. R., Weiss, G. M., and Moore, S. a. (2011). Activity recognition using cell phone accelerometers. ACM SIGKDD Explorations Newsletter, 12:74.
Lara, O. D. and Labrador, M. a. (2012). A Survey on Human Activity Recognition using Wearable Sensors. IEEE Communications Surveys & Tutorials, pages 1–18.
Lopes, J., Souza, R., Geyer, C., Costa, C., Barbosa, J., and Augustin, I. (2014). A middleware architecture for context-aware adaptation in. Journal of Universal Computer Science, 20(9):1327–1351.
Negrão, C. E. and Barreto, A. C. P. (2010). Cardiologia do Exercício: do Atleta ao Cardiopata. Manole, Barueri, SP - Brazil, 3 edition.
Perera, C., Zaslavsky, A., Christen, P., and Georgakopoulos, D. (2013). Context Aware Computing for The Internet of Things : A Survey. IEEE COMMUNICATIONS SURVEYS & TUTORIALS, X(X):1–41.
Rabelo, D., Gil, C., and Araújo, S. D. (2006). Reabilitação cardíaca com ênfase no exercício: uma revisão sistemática. Revista Brasileira de Medicina do Esporte, 12(5):279–285.
Shaw, I. and Simões, M. (2007). Controle e Modelagem Fuzzy. 2 edition.
Sobrevilla, P. and Montseny, E. (2003). Fuzzy Sets in Computer Vision : an Overview. Mathw. Soft Computing, 10:71–83.
Sousa, T. B. (2012). Dataflow programming concept, languages and applications. In Doctoral Symposium on Informatics Engineering, number January.
Ye, J., Dobson, S., and McKeever, S. (2012). Situation identification techniques in pervasive computing: A review. Pervasive and Mobile Computing, 8(1):36–66.
Yuan, B. and Herbert, J. (2014). Context-aware hybrid reasoning framework for pervasive healthcare. Personal and Ubiquitous Computing, 18(4):865–881.
Publicado
02/07/2017
Como Citar
SCHEUNEMANN, Douglas; YAMIN, Adenauer; REISER, Renata; LOPES, João; GEYER, Cláudio.
Uma Abordagem Dataflow para Processamento Contextual na Internet das Coisas. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO UBÍQUA E PERVASIVA (SBCUP), 9. , 2017, São Paulo.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 968-977.
ISSN 2595-6183.
DOI: https://doi.org/10.5753/sbcup.2017.3303.
