Hierarchical community discovery for multi-stage IP bearer network upgradation

Journal of Network and Computer Applications - Tập 189 - Trang 103151 - 2021
Yuan Liu1, Rentao Gu1, Zeyuan Yang1, Yuefeng Ji1
1Beijing Laboratory of Advanced Information Network, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, 100876, China

Tài liệu tham khảo

Ahn, 2010, Link communities reveal multiscale complexity in networks, Nature, 466, 761, 10.1038/nature09182 Bai, 2017, Fast graph clustering with a new description model for community detection, Inform. Sci., 388, 37, 10.1016/j.ins.2017.01.026 Blondel, 2008, Fast unfolding of communities in large networks, J. Stat. Mech. Theory Exp., 2008, 10.1088/1742-5468/2008/10/P10008 Brandes, 2001, A faster algorithm for betweenness centrality, J. Math. Sociol., 25, 163, 10.1080/0022250X.2001.9990249 Brin, 1998, The anatomy of a large-scale hypertextual web search engine, Comput. Netw., 30, 107 Carey, 2016, Dynamically reconfigurable TDM-DWDM PON ring architecture for efficient rural deployment, 1 Carmi, 2007, A model of Internet topology using k-shell decomposition, Proc. Natl. Acad. Sci., 104, 11150, 10.1073/pnas.0701175104 Chen, 2009, Local community identification in social networks, 237 Choumane, 2020, Core expansion: a new community detection algorithm based on neighborhood overlap, Soc. Netw. Anal. Min., 10, 30, 10.1007/s13278-020-00647-6 Coppersmith, D., Winograd, S., 1987. Matrix multiplication via arithmetic progressions. In: Proceedings of the Nineteenth Annual ACM Symposium on Theory of Computing. pp. 1–6. Cui, 2019, A survey on network embedding, IEEE Trans. Knowl. Data Eng., 31, 833, 10.1109/TKDE.2018.2849727 Du, L., Lu, Z., Wang, Y., et al., 2018. Galaxy network embedding: A hierarchical community structure preserving approach. In: IJCAI. pp. 2079–2085. Fagnan, 2014, Using triads to identify local community structure in social networks, 108 Fiorani, 2015, On the design of 5G transport networks, Photonic Netw. Commun., 30, 403, 10.1007/s11107-015-0553-8 Fortunato, 2007, Resolution limit in community detection, Proc. Natl. Acad. Sci., 104, 36, 10.1073/pnas.0605965104 Fortunato, 2016, Community detection in networks: A user guide, Phys. Rep., 659, 1, 10.1016/j.physrep.2016.09.002 Fu, 2017, A community detection algorithm using network topologies and rule-based hierarchical arc-merging strategies, PLoS One, 12, 1, 10.1371/journal.pone.0187603 Goyal, 2018, Graph embedding techniques, applications, and performance: A survey, Knowl.-Based Syst., 151, 78, 10.1016/j.knosys.2018.03.022 Gu, 2020, Machine learning for intelligent optical networks: A comprehensive survey, J. Netw. Comput. Appl., 157, 10.1016/j.jnca.2020.102576 Hollocou, 2018, Multiple local community detection, ACM SIGMETRICS Perform. Eval. Rev., 45, 76, 10.1145/3199524.3199537 Huang, 2011, Density-based shrinkage for revealing hierarchical and overlapping community structure in networks, Physica A, 390, 2160, 10.1016/j.physa.2010.10.040 Interdonato, 2017, Local community detection in multilayer networks, Data Min. Knowl. Discov., 31, 1444, 10.1007/s10618-017-0525-y Janjić, 2014, The topology of the growing human interactome data, J. Integr. Bioinform., 11, 27, 10.1515/jib-2014-238 Javed, 2018, Community detection in networks: A multidisciplinary review, J. Netw. Comput. Appl., 108, 87, 10.1016/j.jnca.2018.02.011 Jeub, 2017, A local perspective on community structure in multilayer networks, Netw. Sci., 5, 144, 10.1017/nws.2016.22 Karsakov, 2017, Parenclitic network analysis of methylation data for cancer identification, PLoS One, 12, 1, 10.1371/journal.pone.0169661 Lancichinetti, 2009, Detecting the overlapping and hierarchical community structure in complex networks, New J. Phys., 11, 10.1088/1367-2630/11/3/033015 Li, Y., He, K., Bindel, D., et al., 2015. Uncovering the small community structure in large networks: A local spectral approach. In: Proceedings of the 24th International Conference on World Wide Web. pp. 658–668. Li, 2019, Multi-hot compact network embedding, 459 Lin, 2015, An integer programming approach and visual analysis for detecting hierarchical community structures in social networks, Inform. Sci., 299, 296, 10.1016/j.ins.2014.12.009 Liu, 2016, MIRACLE: A multiple independent random walks community parallel detection algorithm for big graphs, J. Netw. Comput. Appl., 70, 89, 10.1016/j.jnca.2016.05.008 Lombardi, R., 2018. Microwave and millimetre-wave for 5G transport. ETSI White Paper 25. Long, Q., Wang, Y., Du, L., et al., 2019. Hierarchical community structure preserving network embedding: A subspace approach. In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management. pp. 409–418. Luo, 2018, Local community detection with the dynamic membership function, IEEE Trans. Fuzzy Syst., 26, 3136, 10.1109/TFUZZ.2018.2812148 Luo, 2019, Multiscale local community detection in social networks, IEEE Trans. Knowl. Data Eng., 10.1109/TKDE.2019.2938173 Mahoney, 2012, A local spectral method for graphs: With applications to improving graph partitions and exploring data graphs locally, J. Mach. Learn. Res., 13, 2339 Malliaros, 2015, Graph-based term weighting for text categorization, 1473 Manning, 2008 Mata, 2018, Artificial intelligence (AI) methods in optical networks: A comprehensive survey, Opt. Switch. Netw., 28, 43, 10.1016/j.osn.2017.12.006 Mikolov, 2013 Moradi, 2014, A local seed selection algorithm for overlapping community detection, 1 Newman, 2004, Finding and evaluating community structure in networks, Phys. Rev. E, 69 Ni, 2019, Local overlapping community detection, ACM Trans. Knowl. Discov. Data, 14, 1, 10.1145/3361739 Perozzi, 2014, DeepWalk: Online learning of social representations, 701 Ruhnau, 2000, Eigenvector-centrality—a node-centrality?, Social Networks, 22, 357, 10.1016/S0378-8733(00)00031-9 Schiano, 2015, Flexible node architectures for metro networks, J. Opt. Commun. Netw., 7, B131, 10.1364/JOCN.7.00B131 Sehier, 2019, Transport evolution for the RAN of the future, J. Opt. Commun. Netw., 11, B97, 10.1364/JOCN.11.000B97 Shakeri, 2017, Network clustering and community detection using modulus of families of loops, Phys. Rev. E, 95, 10.1103/PhysRevE.95.012316 Simmons, 2014 Sun, 2019, Delay-aware content distribution via cell clustering and content placement for multiple tenants, J. Netw. Comput. Appl., 137, 112, 10.1016/j.jnca.2019.04.004 Sun, 2017, Dominating communities for hierarchical control of complex networks, Inform. Sci., 414, 247, 10.1016/j.ins.2017.05.052 Tang, 2015, LINE: Large-scale information network embedding, 1067 Tu, C., Liu, H., Liu, Z., et al., 2017. Cane: Context-aware network embedding for relation modeling. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vol. 1: Long Papers. pp. 1722–1731. Tu, C., Zhang, W., Liu, Z., et al., 2016. Max-margin deepwalk: Discriminative learning of network representation. In: IJCAI, Vol. 2016. pp. 3889–3895. Wang, 2016, A K-means-based network partition algorithm for controller placement in software defined network, 1 Wei, 2020, Reliability of the local IP bearer network: Analysis and optimization, 207 Wey, 2019, Passive optical networks for 5G transport: Technology and standards, J. Lightwave Technol., 37, 2830, 10.1109/JLT.2018.2856828 Whang, 2013, Overlapping community detection using seed set expansion, 2099 Wong, 2017, Enhancing the survivability and power savings of 5G transport networks based on DWDM rings, IEEE/OSA J. Opt. Commun. Networking, 9, D74, 10.1364/JOCN.9.000D74 Yang, C., Liu, Z., Zhao, D., et al., 2015. Network representation learning with rich text information. In: IJCAI, Vol. 2015. pp. 2111–2117. Yang, 2017, Hypergraph partitioning for social networks based on information entropy modularity, J. Netw. Comput. Appl., 86, 59, 10.1016/j.jnca.2016.10.002 Zhang, 2018, New multi-hop clustering algorithm for vehicular ad hoc networks, IEEE Trans. Intell. Transp. Syst., 20, 1517, 10.1109/TITS.2018.2853165 Zhang, C., Jiang, M., Zhang, X., et al., 2020. Multi-modal network representation learning. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. pp. 3557–3558. Zhang, H., King, I., Lyu, M., 2015. Incorporating implicit link preference into overlapping community detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 29, No. 1. Zhang, 2017, Novel unequal clustering routing protocol considering energy balancing based on network partition & distance for mobile education, J. Netw. Comput. Appl., 88, 1, 10.1016/j.jnca.2017.03.025 Zhang, 2018, Novel optimized link state routing protocol based on quantum genetic strategy for mobile learning, J. Netw. Comput. Appl., 122, 37, 10.1016/j.jnca.2018.07.018 Zhang, 2018, A kind of effective data aggregating method based on compressive sensing for wireless sensor network, EURASIP J. Wireless Commun. Networking, 2018, 1, 10.1186/s13638-018-1176-4 Zhang, 2016, Research on metro intelligent optical network planning and optimization, 1