Atribuições Cooperativas de Tarefas de Sensoriamento Baseada em Consenso Relacional para Redes IIoT
Resumo
Entre os atuais serviços IoT destacam-se os voltados a indústrias, que muitas vezes exigem que os objetos desempenhem mais de uma tarefa. Entretanto, o crescimento exponencial dos objetos na IoT impõe o desafio de distribuir e gerenciar a alocação de tarefas entre os objetos. Um dos principais objetivos da alocação de tarefas é melhorar a qualidade das informações e a maximização de tarefas a serem executadas. Embora existam abordagens que otimizem e gerenciem a dinamicidade dos nós, nem todas consideram a relação de similaridade a alocação distribuída sobre o serviço de agrupamento. Este trabalho propõe um mecanismo chamado CONTASKI para alocação de tarefas em redes IIoT, a fim de distribuir as tarefas entre os objetos. Ele baseia-se em estratégias de consenso relacional para alocar as tarefas e de similaridade de capacidades para determinar quais objetos podem atuar na realização dessas tarefas. O CONTASKI foi avaliado no NS-3 gerenciando um ambiente IIoT e obteve uma eficiência de cerca de 98% de tarefas alocadas na maioria dos cenários avaliados e mais de 80% dos agrupamentos IIoT aptos a executá-las.
Palavras-chave:
Alocação de tarefas, consenso, agrupamento, gerência cooperativa
Referências
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Chen, I.-R., Guo, J., and Bao, F. (2016). Trust Management for SOA-Based IoT and Its Application to Service Composition. IEEE Transactions on Services Computing, 9(3):482-495.
Colistra, G., Pilloni, V., and Atzori, L. (2014). Task allocation in group of nodes in the iot: Aconsensus approach. In 2014 IEEE International Conference on Communications (ICC), pages 3848-3853. IEEE.
Evangelista, D., Mezghani, F., Nogueira, M., and Santos, A. (2016). Evaluation of sybil attack detection approaches in the internet of things content dissemination. In 2016 Wireless Days (WD), pages 1-6. IEEE.
Fang, W., Zhang, Q., Liu, M., Liu, Q., and Xia, P. (2018). Earning maximization with quality of charging service guarantee for iot devices. IEEE Internet of Things Journal, 6(1):1114-1124.
Ghanbari, Z., Navimipour, N. J., Hosseinzadeh, M., and Darwesh, A. (2019). Resource allocation mechanisms and approaches on the internet of things. Cluster Computing, pages 1-30.
Gielow, F., Jakllari, G., Nogueira, M., and Santos, A. (2015). Data similarity aware dynamic node clustering in wireless sensor networks. Ad Hoc Networks, 24:29-45.
Gubbi, J., Buyya, R., Marusic, S., and Palaniswami, M. (2013). Internet of things (iot): A vision, architectural elements, and future directions. Future generation computer systems, 29(7):1645-1660.
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Jin, Y., Jin, J., Gluhak, A., Moessner, K., and Palaniswami, M. (2011). An intelligent task allo-cation scheme for multihop wireless networks. IEEE Transactions on Parallel and Distributed Systems, 23(3):444-451.
Khalil, E. A., Ozdemir, S., and Bara'a, A. A. (2019). A new task allocation protocol for extending stability and operational periods in internet of things. IEEE Internet of Things Journal.
Khalil, E. A., Ozdemir, S., and Tosun, S. (2018). Evolutionary task allocation in internet of things-based application domains. Future Generation Computer Systems, 86:121-133.
Kim, M. and Ko, I.-Y. (2015). An efficient resource allocation approach based on a genetic algo-rithm for composite services in iot environments. In 2015 IEEE International Conference on Web Services, pages 543-550. IEEE.
Korsah, G. A., Stentz, A., and Dias, M. B. (2013). A comprehensive taxonomy for multi-robottask allocation. The International Journal of Robotics Research, 32(12):1495-1512.
Pilloni, V. and Atzori, L. (2011). Deployment of distributed applications in wireless sensor networks. Sensors, 11(8):7395-7419.
Pilloni, V. and Atzori, L. (2017). Consensus-based resource allocation among objects in the internet of things. Annals of Telecommunications, 72(7-8):415-429.
Qin, W., Chen, S., and Peng, M. (2020). Recent advances in industrial internet: insights and challenges. Digital Communications and Networks, 6(1):1-13.
Qiu, T., Chen, N., Li, K., Atiquzzaman, M., and Zhao, W. (2018). How can heterogeneous internet of things build our future: A survey. IEEE Communication Surveys & Tutorials, 20(3):2011-2027.
Xu, L.D., Xu, E. L., and Li, L. (2018). Industry 4.0: state of the art and future trends. International Journal of Production Research, 56(8):2941-2962.
Zhong, R. Y., Xu, X., Klotz, E., and Newman, S. T. (2017). Intelligent manufacturing in the context of industry 4.0: a review. Engineering, 3(5):616-630.
Borgia, E. (2014). The internet of things vision: Key features, applications and open issues. Computer Communications, 54:1-31.
Botta, A., De Donato, W., Persico, V., and Pescapé, A. (2016). Integration of cloud computing and internet of things: a survey. Future generation computer systems, 56:684-700.
Chen, I.-R., Guo, J., and Bao, F. (2016). Trust Management for SOA-Based IoT and Its Application to Service Composition. IEEE Transactions on Services Computing, 9(3):482-495.
Colistra, G., Pilloni, V., and Atzori, L. (2014). Task allocation in group of nodes in the iot: Aconsensus approach. In 2014 IEEE International Conference on Communications (ICC), pages 3848-3853. IEEE.
Evangelista, D., Mezghani, F., Nogueira, M., and Santos, A. (2016). Evaluation of sybil attack detection approaches in the internet of things content dissemination. In 2016 Wireless Days (WD), pages 1-6. IEEE.
Fang, W., Zhang, Q., Liu, M., Liu, Q., and Xia, P. (2018). Earning maximization with quality of charging service guarantee for iot devices. IEEE Internet of Things Journal, 6(1):1114-1124.
Ghanbari, Z., Navimipour, N. J., Hosseinzadeh, M., and Darwesh, A. (2019). Resource allocation mechanisms and approaches on the internet of things. Cluster Computing, pages 1-30.
Gielow, F., Jakllari, G., Nogueira, M., and Santos, A. (2015). Data similarity aware dynamic node clustering in wireless sensor networks. Ad Hoc Networks, 24:29-45.
Gubbi, J., Buyya, R., Marusic, S., and Palaniswami, M. (2013). Internet of things (iot): A vision, architectural elements, and future directions. Future generation computer systems, 29(7):1645-1660.
Haverkort, B. R. and Zimmermann, A. (2017). Smart industry: How ict will change the game! IEEE internet computing, 21(1):8-10.
Jin, Y., Jin, J., Gluhak, A., Moessner, K., and Palaniswami, M. (2011). An intelligent task allo-cation scheme for multihop wireless networks. IEEE Transactions on Parallel and Distributed Systems, 23(3):444-451.
Khalil, E. A., Ozdemir, S., and Bara'a, A. A. (2019). A new task allocation protocol for extending stability and operational periods in internet of things. IEEE Internet of Things Journal.
Khalil, E. A., Ozdemir, S., and Tosun, S. (2018). Evolutionary task allocation in internet of things-based application domains. Future Generation Computer Systems, 86:121-133.
Kim, M. and Ko, I.-Y. (2015). An efficient resource allocation approach based on a genetic algo-rithm for composite services in iot environments. In 2015 IEEE International Conference on Web Services, pages 543-550. IEEE.
Korsah, G. A., Stentz, A., and Dias, M. B. (2013). A comprehensive taxonomy for multi-robottask allocation. The International Journal of Robotics Research, 32(12):1495-1512.
Pilloni, V. and Atzori, L. (2011). Deployment of distributed applications in wireless sensor networks. Sensors, 11(8):7395-7419.
Pilloni, V. and Atzori, L. (2017). Consensus-based resource allocation among objects in the internet of things. Annals of Telecommunications, 72(7-8):415-429.
Qin, W., Chen, S., and Peng, M. (2020). Recent advances in industrial internet: insights and challenges. Digital Communications and Networks, 6(1):1-13.
Qiu, T., Chen, N., Li, K., Atiquzzaman, M., and Zhao, W. (2018). How can heterogeneous internet of things build our future: A survey. IEEE Communication Surveys & Tutorials, 20(3):2011-2027.
Xu, L.D., Xu, E. L., and Li, L. (2018). Industry 4.0: state of the art and future trends. International Journal of Production Research, 56(8):2941-2962.
Zhong, R. Y., Xu, X., Klotz, E., and Newman, S. T. (2017). Intelligent manufacturing in the context of industry 4.0: a review. Engineering, 3(5):616-630.
Publicado
07/12/2020
Como Citar
PEDROSO, Carlos; UEHARA, Yan; NOGUEIRA, Michele; SANTOS, Aldri.
Atribuições Cooperativas de Tarefas de Sensoriamento Baseada em Consenso Relacional para Redes IIoT. In: WORKSHOP DE GERÊNCIA E OPERAÇÃO DE REDES E SERVIÇOS (WGRS), 25. , 2020, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 195-208.
ISSN 2595-2722.
DOI: https://doi.org/10.5753/wgrs.2020.12461.
