Coleta oportunista de dados para a Internet das Coisas com o uso de otimização discreta
Resumo
A Internet das Coisas (Internet of Things – IoT) se baseia na coleta de dados para futuro processamento e tomada de decisão. Em cenários de redes restritas (Low Power and Lossy Network - LLN) com múltiplos saltos, o encaminhamento eficiente de dados em termos de tráfego gerado e consumo de energia se torna fundamental. Este artigo revisita o conceito de agentes móveis para realizar coleta de dados ao longo dos itinerários dos agentes. A ideia é evitar o envio de requisições para rede quando conteúdos, não expirados e coletados de forma oportunista, estão armazenados no cache de um elemento central. No mecanismo proposto, o itinerário é composto por dispositivos de interesse e dispositivos intermediários em um ciclo fechado na origem. É utilizada a otimização Knapsack para acrescentar dados não solicitados de forma oportunista. A recompensa é calculada conforme a popularidade dos dados. As simulações mostram que é possı́vel reduzir o tráfego na rede e a energia con- sumida pelos dispositivos quando comparado com a coleta de agentes móveis tradicional.
Referências
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Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012). Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud computing, pages 13–16. ACM.
Chen, M., Kwon, T., Yuan, Y., and Leung, V. C. (2006). Mobile agent based wireless sensor networks. Journal of computers, 1(1):14–21.
Chou, Y.-C. and Nakajima, M. (2018). A clonal selection algorithm for energy-efficient mobile agent itinerary planning in wireless sensor networks. Mobile Networks and Applications, 23(5):1233–1246.
Christofides, N. (1976). Worst-case analysis of a new heuristic for the travelling salesman problem. Technical report, Carnegie-Mellon University, Pittsburgh.
Dong, M., Ota, K., Yang, L. T., Chang, S., Zhu, H., and Zhou, Z. (2014). Mobile agent- based energy-aware and user-centric data collection in wireless sensor networks. Com- puter networks, 74:58–70.
Gavalas, D., Venetis, I. E., Konstantopoulos, C., and Pantziou, G. (2017). Mobile agent itinerary planning for WSN data fusion: considering multiple sinks and heterogeneous networks. International Journal of Communication Systems, 30(8):e3184.
Jin, Y., Gormus, S., Kulkarni, P., and Sooriyabandara, M. (2016). Content centric routing in IoT networks and its integration in RPL. Computer Communications, 89:87–104.
Li, S., Xu, J., Van Der Schaar, M., and Li, W. (2016). Popularity-driven content ca- ching. In Computer Communications, IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on, pages 1–9. IEEE.
Liu, B., Cao, J., Yin, J., Yu, W., Liu, B., and Fu, X. (2016). Disjoint multi mobile agent iti- nerary planning for big data analytics. EURASIP Journal on Wireless Communications and Networking, 2016(1):99.
Lu, J., Feng, L., Yang, J., Hassan, M. M., Alelaiwi, A., and Humar, I. (2019). Artificial agent: The fusion of artificial intelligence and a mobile agent for energy-efficient traffic control in wireless sensor networks. Future Generation Computer Systems, 95:45–51.
Mekki, K., Derigent, W., Zouinkhi, A., Rondeau, E., Thomas, A., and Abdelkrim, M. N. (2017). Rawpg: A data retrieval protocol in micro-sensor networks based on random walk and pull gossip for communicating materials. IEEE Internet of Things Journal, 4(2):414–426.
Mišić, J. and Mišić, V. B. (2018). Proxy cache maintenance using multicasting in coap iot domains. IEEE Internet of Things Journal, 5(3):1967–1976.
Rahmani, A.-M., Thanigaivelan, N. K., Gia, T. N., Granados, J., Negash, B., Liljeberg, P., and Tenhunen, H. (2015). Smart e-health gateway: Bringing intelligence to internet- of-things based ubiquitous healthcare systems. In Consumer Communications and Networking Conference (CCNC), 2015 12th Annual IEEE, pages 826–834. IEEE.
Xu, G., Ngai, E. C.-H., and Liu, J. (2018). Ubiquitous transmission of multimedia sensor data in internet of things. IEEE Internet of Things Journal, 5(1):403–414.
Xu, X., Li, X.-Y., Wan, P.-J., and Tang, S. (2012). Efficient scheduling for periodic aggre- gation queries in multihop sensor networks. IEEE/ACM Transactions on Networking (TON), 20(3):690–698.
Yang, S., Adeel, U., Tahir, Y., and McCann, J. A. (2017). Practical opportunistic data collection in wireless sensor networks with mobile sinks. IEEE Transactions on Mobile Computing, 16(5):1420–1433.
Zhan, Y., Xia, Y., Zhang, J., and Wang, Y. (2018). Incentive mechanism design in mobile opportunistic data collection with time sensitivity. IEEE Internet of Things Journal, 5(1):246–256.
Zhang, Z., Ma, H., and Liu, L. (2015). Cache-aware named-data forwarding in internet of things. In Global Communications Conference (GLOBECOM), 2015 IEEE, pages 1–6. IEEE.
Aguilar, S., Vidal, R., and Gomez, C. (2017). Opportunistic sensor data collection with bluetooth low energy. Sensors, 17(1):159.
Baccelli, E., Mehlis, C., Hahm, O., Schmidt, T. C., and Wählisch, M. (2014). Information centric networking in the IoT: experiments with ndn in the wild. In Proceedings of the 1st ACM Conference on Information-Centric Networking, pages 77–86. ACM.
Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012). Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud computing, pages 13–16. ACM.
Chen, M., Kwon, T., Yuan, Y., and Leung, V. C. (2006). Mobile agent based wireless sensor networks. Journal of computers, 1(1):14–21.
Chou, Y.-C. and Nakajima, M. (2018). A clonal selection algorithm for energy-efficient mobile agent itinerary planning in wireless sensor networks. Mobile Networks and Applications, 23(5):1233–1246.
Christofides, N. (1976). Worst-case analysis of a new heuristic for the travelling salesman problem. Technical report, Carnegie-Mellon University, Pittsburgh.
Dong, M., Ota, K., Yang, L. T., Chang, S., Zhu, H., and Zhou, Z. (2014). Mobile agent- based energy-aware and user-centric data collection in wireless sensor networks. Com- puter networks, 74:58–70.
Gavalas, D., Venetis, I. E., Konstantopoulos, C., and Pantziou, G. (2017). Mobile agent itinerary planning for WSN data fusion: considering multiple sinks and heterogeneous networks. International Journal of Communication Systems, 30(8):e3184.
Jin, Y., Gormus, S., Kulkarni, P., and Sooriyabandara, M. (2016). Content centric routing in IoT networks and its integration in RPL. Computer Communications, 89:87–104.
Li, S., Xu, J., Van Der Schaar, M., and Li, W. (2016). Popularity-driven content ca- ching. In Computer Communications, IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on, pages 1–9. IEEE.
Liu, B., Cao, J., Yin, J., Yu, W., Liu, B., and Fu, X. (2016). Disjoint multi mobile agent iti- nerary planning for big data analytics. EURASIP Journal on Wireless Communications and Networking, 2016(1):99.
Lu, J., Feng, L., Yang, J., Hassan, M. M., Alelaiwi, A., and Humar, I. (2019). Artificial agent: The fusion of artificial intelligence and a mobile agent for energy-efficient traffic control in wireless sensor networks. Future Generation Computer Systems, 95:45–51.
Mekki, K., Derigent, W., Zouinkhi, A., Rondeau, E., Thomas, A., and Abdelkrim, M. N. (2017). Rawpg: A data retrieval protocol in micro-sensor networks based on random walk and pull gossip for communicating materials. IEEE Internet of Things Journal, 4(2):414–426.
Mišić, J. and Mišić, V. B. (2018). Proxy cache maintenance using multicasting in coap iot domains. IEEE Internet of Things Journal, 5(3):1967–1976.
Rahmani, A.-M., Thanigaivelan, N. K., Gia, T. N., Granados, J., Negash, B., Liljeberg, P., and Tenhunen, H. (2015). Smart e-health gateway: Bringing intelligence to internet- of-things based ubiquitous healthcare systems. In Consumer Communications and Networking Conference (CCNC), 2015 12th Annual IEEE, pages 826–834. IEEE.
Xu, G., Ngai, E. C.-H., and Liu, J. (2018). Ubiquitous transmission of multimedia sensor data in internet of things. IEEE Internet of Things Journal, 5(1):403–414.
Xu, X., Li, X.-Y., Wan, P.-J., and Tang, S. (2012). Efficient scheduling for periodic aggre- gation queries in multihop sensor networks. IEEE/ACM Transactions on Networking (TON), 20(3):690–698.
Yang, S., Adeel, U., Tahir, Y., and McCann, J. A. (2017). Practical opportunistic data collection in wireless sensor networks with mobile sinks. IEEE Transactions on Mobile Computing, 16(5):1420–1433.
Zhan, Y., Xia, Y., Zhang, J., and Wang, Y. (2018). Incentive mechanism design in mobile opportunistic data collection with time sensitivity. IEEE Internet of Things Journal, 5(1):246–256.
Zhang, Z., Ma, H., and Liu, L. (2015). Cache-aware named-data forwarding in internet of things. In Global Communications Conference (GLOBECOM), 2015 IEEE, pages 1–6. IEEE.
Publicado
08/07/2019
Como Citar
L. FILHO, Edvar Afonso; CAMPISTA, Miguel Elias M..
Coleta oportunista de dados para a Internet das Coisas com o uso de otimização discreta. In: WORKSHOP EM DESEMPENHO DE SISTEMAS COMPUTACIONAIS E DE COMUNICAÇÃO (WPERFORMANCE), 2019. , 2019, Belém.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
ISSN 2595-6167.
DOI: https://doi.org/10.5753/wperformance.2019.6460.
