Low-Latency Multicast and Broadcast Technologies for Real-Time Applications in Smart Grid

  1. Yuemin Ding 2
  2. Xiaohui Li 1
  1. 1 Wuhan University of Science and Technology
    info

    Wuhan University of Science and Technology

    Wuhan, China

    ROR https://ror.org/00e4hrk88

  2. 2 Universidad de Navarra
    info

    Universidad de Navarra

    Pamplona, España

    ROR https://ror.org/02rxc7m23

Libro:
Handbook of Real-Time Computing

Editorial: Springer

ISBN: 978-981-287-250-0,  978-981-287-251-7

Año de publicación: 2022

Páginas: 863-894

Tipo: Capítulo de Libro

DOI: 10.1007/978-981-287-251-7_66 GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

Smart grid integrates modern information and communication technologies with the electrical grid for improved efficiency and reliability. In smart grid, the communication infrastructure is composed of wide area networks (WANs), neighborhood area networks (NANs), and home area networks (HANs). There are many real-time applications demanding low-latency communication technologies, such as wide area protection, urgent demand response, and real-time operations. However, the coexistence of various smart grid applications leads to a competition of limited network resources, leading to negative impacts on communication latency, system reliability, etc. To improve the performance of communication latency, multicast and broadcast technologies are efficient approaches, especially for networks with limited bandwidth and large scalability. This chapter offers a systematic introduction to the multicast and broadcast technologies for real-time applications in smart grid, including low-latency multicast to minimize end-to-end delay for wide area control, low-latency multicast for multiple multicast trees with shared links in WANs, and low-latency constrained broadcast in NANs. Aspects of problem formulation, problem-solving, and illustrative examples have been addressed.

Referencias bibliográficas

  • A.L. Barabasi, R. Albert, Emergence of scaling in random networks. Science 286, 509 (1999)
  • Y. Ding, Y.-C. Tian, X. Li, Y. Mishra, G. Ledwich, C. Zhou, Constrained broadcast with minimized latency in neighborhood area networks of smart grid. IEEE Trans. Ind. Informat. 16(1), 309–318 (2020)
  • H. Gjermundrod, D.E. Bakken, C.H. Hauser, A. Bose, GridStat: A flexible QoS-managed data dissemination framework for the power grid. IEEE Trans. Smart Grid 24(1), 136–143 (2009)
  • A. Goodney, S. Kumar, A. Ravi, Y.H. Cho, Efficient PMU networking with software defined networks, in IEEE International Conference on Smart Grid Communication (Vancouver Oct 21–24 2013), pp. 378–383
  • R. Guimera, A. Diaz-Guilera, F. Vega-Redondo, A. Cabrales, A. Arenas, Optimal network topologies for local search with congestion. Phys. Rev. Lett. 89, 328170 (2002)
  • P. Kansal, A. Bose, Bandwidth and latency requirements for smart transmission grid applications. IEEE Trans. Smart Grid 3(3), 1344–1352 (2012)
  • D. Kim, J. Kim, Design of emergency demand response program using analytic hierarchy process. IEEE Trans. Smart Grid 3(2), 635–644 (2012)
  • V. Konstantinos, B.Y. Katsaros, W.K. Chai, G. Pavlou, Low latency communication infrastructure for synchrophasor applications in distribution networks, in IEEE International Conference on Smart Grid Communication (Venice, 3–6 Nov 2014)
  • K. Kumar, M. Radhakrishnan, K.M. Sivalingam, D.P. Seetharam, M. Karthick, Comparison of publish-subscribe network architectures for smart grid wide area monitoring, in IEEE 3rd International Conference Smart Grid Communication (SmartGridComm) (Tainan, 5–8 Nov 2012), pp. 611–616
  • X. Li, Y.-C. Tian, G. Ledwich, Y. Mishra, X. Han, C. Zhou, Constrained optimization of multicast routing for wide area control of smart grid. IEEE Trans. Smart Grid 10(4), 3801–3808 (2019a). https://doi.org/10.1109/TSG.2018.2835487
  • X. Li, Y.-C. Tian, G. Ledwich, Y. Mishra, C. Zhou, Minimizing multicast routing delay in multiple multicast trees with shared links for smart grid. IEEE Trans. Smart Grid 10(5), 5427–5435 (2019b)
  • M.E.J. Newman, Scientific collaboration networks. II. shortest paths, weighted networks, and centrality. Phys. Rev. E 64(1), 016132 (2001)
  • C.A.S. Oliveira, P.M. Pardalos, A survey of combinatorial optimization problems in multicast routing. Comput. Oper. Res. 32(8), 1953–1981 (2005)
  • L. Pradittasnee, S. Camtepe, Y.-C. Tian, Efficient route update and maintenance for reliable routing in large-scale sensor networks. IEEE Trans. Ind. Inform. 13(1), 144–156 (2017)
  • G. Rajalingham, Q.-D. Ho, T. Le-Ngoc, Attainable throughput, delay and scalability for geographic routing on smart grid neighbor area networks, in 2013 IEEE Wireless Communication and Networking Conference (WCNC) (2013), pp. 1121–1126
  • K. Stachowiak, P. Zwierzykowski, Lagrangian relaxation and linear intersection based QOS routing algorithm. Int. J. Electron. Telecommun. 58(4), 307–314 (2012)
  • G. Tian, S. Camtepe, Y.-C. Tian, A deadline-constrained 802.11 MAC protocol with QoS differentiation for real-time control. IIEEE Trans. Ind. Inform. 12(2), 544–554 (2016)
  • N.H. Tran, C. Pham, M.N.H. Nguyen, S. Ren, C.S. Hong, Incentivizing energy reduction for emergency demand response in multi-tenant mixed-use buildings. IEEE Trans. Smart Grid 9(4), 3701–3715 (2018)
  • Y. Wang, I.R. Pordanjani, W. Xu, An event-driven demand response scheme for power system security enhancement. IEEE Trans. Smart Grid 2(1), 23–29 (2011)
  • G. Yan, T. Zhou, B. Hu, Z.Q. Fu, B.H. Wang, Efficient routing on complex networks. Phy. Rev. E 73(2), 046108 (2006)
  • L. Zhao, Y.-C. Lai, K. Park, N. Ye, Onset of traffic congestion in complex networks. Phy. Rev. E 71, 026125 (2005)