Optimal proactive monitor placement & scheduling for IoT networks

References

• Abdullah, S., & Yang, K. (2014). An energy efficient message scheduling algorithm considering node failure in iot environment. Wireless Personal Communications, 79(3), 1815–1835. https://doi.org/10.1007/s11277-014-1960-3
   Web of Science ®Google Scholar
• Adamatzky, A. (2016). Advances in unconventional computing: Volume 1: Theory. (Vol. 22). Springer.
   Google Scholar
• Agrawal, S., Naidu, K., & Rastogi, R. (2007). Diagnosing link-level anomalies using passive probes. 26th IEEE International Conference on Computer Communications (INFOCOM 2007) (pp. 1757–1765).
   Google Scholar
• Beame, P., Impagliazzo, R., & Sabharwal, A. (2007). The resolution complexity of independent sets and vertex covers in random graphs. Computational Complexity, 16(3), 245–297.
   Web of Science ®Google Scholar
• Bergmann, G., Molnár, M., Gönczy, L., & Cousin, B. (2010). Optimal period length for the CGS sensor network scheduling algorithm. 2010 Sixth International Conference on Networking and Services, 192–199.
   Google Scholar
• Chang, M.-S., Chen, L.-H., Hung, L.-J., Rossmanith, P., & Su, P.-C. (2016). Fixed-parameter algorithms for vertex cover p3. Discrete Optimization, 19, 12–22.
   Web of Science ®Google Scholar
• Chen, Z., Xu, G., Mahalingam, V., Ge, L., Nguyen, J., Yu, W., et al. (2016). A cloud computing based network monitoring and threat detection system for critical infrastructures. Big Data Research, 3, 10–23. https://doi.org/10.1016/j.bdr.2015.11.002
   Web of Science ®Google Scholar
• Datasheet, T. S. (2006). Moteiv Corporation. Saatavissa (viitattu 1.10. 2017). http://www.eecs.harvard.edu/˜konrad/projects/shimmer/references/tmote-sky-datasheet.pdf.
   Google Scholar
• Dinur, I., & Safra, S. (2005). On the hardness of approximating minimum vertex cover. Annals of Mathematics, 439–485.
   Web of Science ®Google Scholar
• Dunning, I., Huchette, J., & Lubin, M. (2017). JuMP: A modeling language for mathematical optimization. SIAM Review, 59(2), 295–320.
   Web of Science ®Google Scholar
• Ferdowsi, A., & Saad, W. (2019). Generative adversarial networks for distributed intrusion detection in the internet of things. 1–6.
   Google Scholar
• Garey, M. R., & Johnson, D. S. (1979). Computers and intractability: A guide to the theory of np-completeness (series of books in the mathematical sciences) (First Edition ed.). W. H. Freeman.
   Google Scholar
• Geng, H. (2017). Internet of things and data analytics handbook. Wiley.
   Google Scholar
• Girvan, M., & Newman, M. E. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences, 99(12), 7821–7826. https://doi.org/10.1073/pnas.122653799
   PubMed Web of Science ®Google Scholar
• Jara, A. J., Ladid, L., & Gómez-Skarmeta, A. F. (2013). The internet of everything through IPv6: An analysis of challenges. Solutions and Opportunities. JoWua, 4(3), 97–118.
   Google Scholar
• Khalifa, A. B., & Stanica, R. (2019). Performance evaluation of channel access methods for dedicated iot networks. In 2019 Wireless Days (WD) (pp. 1–6). https://doi.org/10.1109/WD.2019.8734186
   Google Scholar
• Khelifi, N., Oteafy, S., Hassanein, H., & Youssef, H. (2015). Proactive maintenance in rpl for 6lowpan. 993–999.
   Google Scholar
• Kuang, X., & Shen, J. (2010). SNDS: A distributed monitoring and protocol analysis system for wireless sensor network. In 2010 second international conference on networks security, wireless communications and trusted computing (Vol. 2, p. 422–425). https://doi.org/10.1109/NSWCTC.2010.233
   Google Scholar
• Kumar, R., & Kaur, J. (2004). Efficient beacon placement for network tomography. Proceedings of the 4th ACM SIGCOMM Conference on Internet Measurement (pp. 181–186). https://doi.org/10.1145/1028788.1028810
   Google Scholar
• Kushalnagar, N., Montenegro, G., Schumacher, C. (2007). Ipv6 over low-power wireless personal area networks (6lowpans): Overview, assumptions, problem statement, and goals.
   Google Scholar
• Lee, W. L., Datta, A., & Cardell-Oliver, R. (2006). WinMS: Wireless sensor network-management system, an adaptive policy-based management for wireless sensor networks.
   Google Scholar
• Lin, J., Yu, W., Zhang, N., Yang, X., Zhang, H., & Zhao, W. (2017). A survey on internet of things: Architecture, enabling technologies, security and privacy, and applications. IEEE Internet of Things Journal, 4(5), 1125–1142.
   Web of Science ®Google Scholar
• Liu, X., Gao, Y., Wu, W., Dong, W., & Bu, J. (2015). Robust monitor assignment with minimum cost for sensor network tomography. International Journal of Distributed Sensor Networks, 11(8), 512463.
   Web of Science ®Google Scholar
• Lusseau, D., Schneider, K., Boisseau, O. J., Haase, P., Slooten, E., & Dawson, S. M. (2003). The bottlenose DOLPHIN community of doubtful sound features a large proportion of long-lasting associations. Behavioral Ecology and Sociobiology, 54(4), 396–405. https://doi.org/10.1007/s00265-003-0651-y
   Web of Science ®Google Scholar
• Ma, L., He, T., Swami, A., Towsley, D., & Leung, K. K. (2015). On optimal monitor placement for localizing node failures via network tomography. Performance Evaluation, 91, 16–37.
   Web of Science ®Google Scholar
• Ma, J., Lou, W., Wu, Y., Li, X.-Y., & Chen, G. (2009). Energy efficient TDMA sleep scheduling in wireless sensor networks. IEEE Infocom, 2009, 630–638.
   Google Scholar
• Mayzaud, A., Badonnel, R., & Chrisment, I. (2017). A distributed monitoring strategy for detecting version number attacks in RPL-based networks. IEEE Transactions on Network and Service Management, 14(2), 472–486.
   Google Scholar
• Mayzaud, A., Sehgal, A., Badonnel, R., Chrisment, I., & Schönwälder, J. (2016). Using the RPL protocol for supporting passive monitoring in the internet of things. NOMS 2016 – 2016 IEEE/IFIP Network Operations and Management Symposium (pp. 366–374). https://doi.org/10.1109/NOMS.2016.7502833
   Google Scholar
• Maalel, N., Natalizio, E., Bouabdallah, A., Roux, P., & Kellil, M. (2013). Reliability for emergency applications in internet of things. 2013 IEEE International Conference on Distributed Computing in Sensor Systems (pp. 361–366).
   Google Scholar
• Mostafa, B., Benslimane, A., Saleh, M., Kassem, S., & Molnar, M. (2018). An energy-efficient multiobjective scheduling model for monitoring in internet of things. IEEE Internet of Things Journal, 5(3), 1727–1738. https://doi.org/10.1109/JIOT.2018.2792326
   Web of Science ®Google Scholar
• Mostafa, B., Benslimane, A., Boureau, E., Molnar, M., & Saleh, M. (2016, April). Distributed monitoring in 6LoWPAN-based Internet of Things. 2016 International Conference on Selected Topics in Mobile Wireless Networking (MoWNeT) (pp. 1–7).
   Google Scholar
• Newman, M. E. (2006). Finding community structure in networks using the Eigenvectors of matrices. Physical Review E, 74(3), 036104. https://doi.org/10.1103/PhysRevE.74.036104
   Web of Science ®Google Scholar
• Olatinwo, D. D., Abu-Mahfouz, A. M., & Hancke, G. P. (2021). Towards achieving efficient mac protocols for wban-enabled iot technology: A review. EURASIP Journal on Wireless Communications and Networking, 2021(1), 1–47. https://doi.org/10.1186/s13638-021-01919-1
   Web of Science ®Google Scholar
• Ozkan, O., Ermis, M., & Bekmezci, I. (2020). Reliable communication network design: The hybridisation of metaheuristics with the branch and bound method. Journal of the Operational Research Society, 71(5), 784–799.
   Web of Science ®Google Scholar
• Rahman, L. F., Ozcelebi, T., & Lukkien, J. (2018). Understanding iot systems: A life cycle approach. Procedia Computer Science, 130, 1057–1062.
   Google Scholar
• Rossi, R. A., & Ahmed, N. K. (2015). The network data repository with interactive graph analytics and visualization. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence. http://networkrepository.com
   Google Scholar
• Sahoo, P., Thakkar, H., Hwang, I. (2017). Pre-scheduled and self-organized sleep-scheduling algorithms for efficient k-coverage in wireless sensor networks. Sensors, 17(12), 2945. https://doi.org/10.3390/s17122945
   PubMed Web of Science ®Google Scholar
• Sehgal, A., Perelman, V., Kuryla, S., & Schönwälder, J. (2012). Management of resource constrained devices in the internet of things. IEEE Communications Magazine, 50.
   Web of Science ®Google Scholar
• Soós, G., Kozma, D., Janky, F. N., & Varga, P. (2018). IoT device lifecycle–a generic model and a use case for cellular mobile networks. In 2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud) (pp. 176–183). https://doi.org/10.1109/FiCloud.2018.00033
   Google Scholar
• Srinidhi, N., Kumar, S. D., & Venugopal, K. (2019). Network optimizations in the internet of things: A review. Engineering Science and Technology: An International Journal, 22(1), 1–21.
   Google Scholar
• Stanisavljević, M., Schmid, A., & Leblebici, Y. (2010). Reliability of nanoscale circuits and systems: Methodologies and circuit architectures. Springer Science & Business Media.
   Google Scholar
• Taheri, R., Ghahramani, M., Javidan, R., Shojafar, M., Pooranian, Z., & Conti, M. (2020). Similarity-based android malware detection using hamming distance of static binary features. Future Generation Computer Systems, 105, 230–247.
   Web of Science ®Google Scholar
• Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of” small-world” networks. Nature, 393(6684), 440. https://doi.org/10.1038/30918
   PubMed Web of Science ®Google Scholar
• Wu, F., Wu, T., & Yuce, M. (2019). An internet-of-things (IoT) network system for connected safety and health monitoring applications. Sensors, 19(1), 21.
   Web of Science ®Google Scholar
• Yücel, T., & Alt In-Kayhan, A. (2019). A Copy-at-neighbouring-node retransmission strategy for improved wireless sensor network lifetime and reliability. Journal of the Operational Research Society, 70(7), 1193–1202.
   Web of Science ®Google Scholar
• Zachary, W. W. (1977). An information flow model for conflict and fission in small groups. Journal of Anthropological Research, 33(4), 452–473. https://doi.org/10.1086/jar.33.4.3629752
   Web of Science ®Google Scholar
• Zhao, Z., Huangfu, W., & Sun, L. (2012). NSSN: A network monitoring and packet sniffing tool for wireless sensor networks. 012 8th International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 537–542).
   Google Scholar