Advertisement

RNS Applications in Computer Networks

  • Azadeh Alsadat Emrani ZarandiEmail author
Chapter
  • 785 Downloads

Abstract

Computer networks by providing data exchange capability between connected systems are driving a revolution in digital world. However, by improving the technology and producing low price devices, the number of connected devices is rapidly growing, and users are moving from one computer per person to multidevices per person including cell phones, home appliances, and wearable gadgets which are all connected to the internet. Therefore, new network concepts and also challenges have been introducing to overcome issues of rapid growth of the number of connected devices. Moreover, for future network with huge number of members more complex processors are needed to perform required process. Therefore, researchers of these fields should look for novel methods to overcome distinct emerging challenges. Recently, residue number system (RNS) as an alternative method to reduce network operations overhead attracts network researchers. The RNS has been used as a tool to reduce transmission energy and increase reliability in wireless sensor networks. Moreover, RNS can enhance switching process, and substitute lookup tables with simple modular operations in software-defined network. This chapter presents different types of RNS applications in computer networks in order to familiar researchers with these concepts.

Keywords

Residue number system (RNS) Chinese remainder theorem (CRT) Wireless sensor network (WSN) Software-defined network (SDN) Multicast routing 

References

  1. 1.
    C.H. Chang, A.S. Molahosseini, A.A.E. Zarandi, T.F. Tay, Residue number systems: a new paradigm to datapath optimization for low-power and high-performance digital signal processing applications. IEEE Circuits Syst. Mag. 15(4), 26–44 (2015)CrossRefGoogle Scholar
  2. 2.
    A.S. Molahosseini, S. Sorouri, A.A.E. Zarandi, Research challenges in next-generation residue number system architectures, in Proceedings of International Conference on Computer Science & Education (ICCSE), 2012Google Scholar
  3. 3.
    W.K. Jia, L.C. Wang, A unified unicast and multicast routing and forwarding algorithm for software-defined datacenter networks. IEEE J. Selected Areas Commun. 31(12), 2646–2657 (2013)CrossRefGoogle Scholar
  4. 4.
    G. Campobello, A. Leonardi, S. Palazzo, Improving energy saving and reliability in wireless sensor networks using a simple crt-based packet-forwarding solution. IEEE ACM Trans. Netw. 20(1), 191–205 (2012)CrossRefGoogle Scholar
  5. 5.
    W.K. Jia, C.Y. Chen, Y.C. Chen, ALEX: an arithmetic-based unified unicast and multicast routing for MANETs, in Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), 2014Google Scholar
  6. 6.
    A. Celesti, M. Fazio, M. Villari, A. Puliafito, Adding long-term availability, obfuscation, and encryption to multi-cloud storage systems. J. Netw. Comput. Appl. 59, 208–218 (2016)CrossRefGoogle Scholar
  7. 7.
    R. Ye, A. Boukerch, H. Wang, X. Zho, RESIDENT: a reliable residue number system-based data transmission mechanism for wireless sensor networks. Springer J. Wireless Netw. 1–14, to appear, 2016Google Scholar
  8. 8.
    G. Campobello, S. Serrano, L. Galluccio, S. Palazzo, Applying the Chinese remainder theorem to data aggregation in wireless sensor networks. IEEE Commun. Lett. 17(5), 1000–1003 (2013)CrossRefGoogle Scholar
  9. 9.
    H. Kim, N. Feamster, Improving network management with software defined networking. IEEE Commun. Mag. 51(2), 114–119 (2013)CrossRefGoogle Scholar
  10. 10.
    D. Waitzman, C. Partridge, S. Deering, Distance vector multicast routing protocol, RFC 1075, Internet Engineering Task Force, 1988Google Scholar
  11. 11.
    S. Deering, D. Estrin, D. Farinacci, V. Jacobson, C.-G. Liu, L. Wei, An architecture for wide-area multicast routing. SIGCOMM Comput. Commun. Rev. 24(4), 126–135 (1994)CrossRefGoogle Scholar
  12. 12.
    B.H. Bloom, Space/time trade-offs in hash coding with allowable errors. Commun. ACM 13(7), 422–426 (1970)CrossRefzbMATHGoogle Scholar
  13. 13.
    K. Navi, A.S. Molahosseini, M. Esmaeildoust, How to teach residue number system to computer scientists and engineers. IEEE Trans. Educ. 54(1), 156–163 (2011)CrossRefGoogle Scholar
  14. 14.
    T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, Introduction to algorithms (MIT Press, Cambridge, MA, 2001)zbMATHGoogle Scholar
  15. 15.
    M. Martinello, M.R.N. Ribeiro, R. Emerick, Z.D. de Oliveira, R.A. Vitoi, KeyFlow: a prototype for evolving SDN toward core network fabrics. IEEE Netw. 28(2), 12–19 (2014)CrossRefGoogle Scholar
  16. 16.
    A.A.E. Zarandi, A.S. Molahosseini, L. Sousa, M. Hosseinzadeh, An efficient component for designing signed reverse converters for a class of RNS moduli sets of composite form {2k, 2P − 1}. IEEE Trans. Very Large Scale Integr. Syst., to appear, 2016Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer EngineeringShahid Bahonar University of KermanKermanIran

Personalised recommendations