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An Optimal TGO Topology Method for a Scalable and Survivable Network in IOT Communication Technology

  • Shanmuk Srinivas AmiripalliEmail author
  • Veeramallu Bobba
Article
  • 32 Downloads

Abstract

In the year 2015 per person is having 3.47 devices that will be around 25 billion devices, In future years 2020 expected devices per person are 6.58 which is around 50 billion devices. From this statistic, we clearly identified a major problem for IoT devices is scalability and survivability. As the number of devices increases, which is nothing but scalability increases, the quality of service (QoS) will be decreased. To increase the QoS we have to design a novel architecture. To address these problems we come up with a trimet graph optimization (TGO) topology. Topology plays an important role in modern wireless technologies like WSN, Ad hoc networks, cyber-physical system and IOT. We have basic topologies like a bus, ring, star, mesh, tree, etc., which are not fulfilling all the requirements of the modern engineering problems. In this paper, we are making a new attempt to bridge the gap between existing topologies and network design problems. We are testing a novel TGO topology which is used to design a survival, simple, cost-effective topology for Wireless sensor networks and IoT. TGO topology was simulated extensively on various scenarios of wireless technologies using Contiki OS and Cooja simulator. Finally, results are compared with the existing topologies.

Keywords

Topology Optimization Survivable network Wireless technologies IOT Trimet graph 

Notes

References

  1. 1.
    Bondy, J. A., & Murthy, U. S. R. (1976). Graph theory with applications. London: Macmillan Press Ltd.CrossRefGoogle Scholar
  2. 2.
    Liu, C. L., & Mohapatra, D. P. (2008). Elements of discrete mathematics (SiE ed.). New York: McGraw-Hill. ISBN No: 9781259006395.Google Scholar
  3. 3.
    Amiripalli, S. S., & Bobba, V. (2018). Research on network design and analysis of TGO topology, International Journal of Networking and Virtual Organizations. 19(1), 72–86,  https://doi.org/10.1504/IJNVO.2018.10015031.CrossRefGoogle Scholar
  4. 4.
    Amiripalli, S. S., Kumar, A. K., & Tulasi, B. (2016). TRIMET along with its properties and scope. In American Institute of Physics conference proceedings (Vol. 1705, pp. 020032 1–9).Google Scholar
  5. 5.
    Qian, Y., Lu, K., & Tipper, D. (2007). A design for secure and survivable wireless sensor networks. IEEE Wireless Communications, 14, 30–37.  https://doi.org/10.1109/MWC.2007.4396940.CrossRefGoogle Scholar
  6. 6.
    Hajjej, F., Ejbali, R., & Zaied, M. (2016). An efficient deployment approach for improved coverage in wireless sensor networks based on flower pollination algoritham. In NETCOM, NCS, WiMoNe, GRAPH-HOC, SPM, CSEIT-2016 (pp. 117–129),  https://doi.org/10.5121/csit.2016.61511.
  7. 7.
    Jia, D., Li, M., Zhu, H., & Zhang, B. (2016). Layer-cluster topology sensor node deployment for large-scale multi-nodes of WSN. Wireless Personal Communications.  https://doi.org/10.1007/s11277-016-3764-0.Google Scholar
  8. 8.
    Kamalesh, V. N., Shanthala, K. V., Ravindra, V., Chandan, B. K., Pavan, M. P., & Bomble, P. P. (2015). On the design of fault tolerant k-connected network topologies. Journal of Technology Management & Innovation, 6, 339–342.  https://doi.org/10.18178/ijimt.2015.6.5.626.CrossRefGoogle Scholar
  9. 9.
    Ansari, A. Q. (2014). Fixed channel allocation in wireless mesh network subject to efficient spectrum usage and reliability constraint. International Journal of Computer Applications, 106(3), 0975–8887.Google Scholar
  10. 10.
    Gaddour, O., Koubâa, A., Rangarajan, R., Cheikhrouhou, O., Tovar, E., & Abid, M. (2014). Co-RPL: RPL routing for mobile low power wireless sensor networks using Corona mechanism. In 2014 9th IEEE international symposium on industrial embedded systems (SIES) (pp. 200–209).Google Scholar
  11. 11.
    Sitanayah, L., Sreenan, C. J., & Fedor, S. (2013). Demo abstract: A cooja-based tool for maintaining sensor network coverage requirements in a building. In 11th ACM conference on embedded networked sensor systems SenSys 2013 (pp. 5–6). 10.1145/2517351.2517390.Google Scholar
  12. 12.
    Mamun, Q. (2012). A qualitative comparison of different logical topologies for wireless sensor networks. Sensors (Basel), 12, 14887–14913.  https://doi.org/10.3390/s121114887.CrossRefGoogle Scholar
  13. 13.
    Lloret, J., Garcia, M., Bri, D., & Diaz, J. R. (2009). A cluster-based architecture to structure the topology of parallel wireless sensor networks. Sensors, 9, 10513–10544.  https://doi.org/10.3390/s91210513.CrossRefGoogle Scholar
  14. 14.
    Nourildean, S. W. (2012). A study of zigbee network topologies for wireless sensor network with one coordinator and multiple coordinators. Tikrit Journal of Engineering Sciences, 19, 65–81.Google Scholar
  15. 15.
    Johansonbaugh, R. (2001). Discrete mathematics (5th ed.). London: Pearson Education. ISBN No: 10: 0130890081.Google Scholar
  16. 16.
    Rao, I. H. N. R., & Raju, S. V. S. R. (2012). Semi complete graphs—III. Journal of International Mathematical Virtual Institute, 2, 21–37.MathSciNetzbMATHGoogle Scholar
  17. 17.
    Rao, I. H. N. R., Raju, S. V. S. R., & Shanmuk Srinivas, A. (2012). On path connector sets. IJMSC, 2(2), 55–65.CrossRefGoogle Scholar
  18. 18.
    Rao, I., Rao, I. H. N. R., & Raju, S. V. S. R. (2010). Semi-complete graphs-II. International Journal of Computational Cognition, 8(3), 57–62.Google Scholar
  19. 19.
    Bendigeri, K. Y., & Mallapur, J. D. (2015). Multiple node placement strategy for efficient routing in wireless sensor networks. Wireless Sensor Network, 7, 101–112.  https://doi.org/10.4236/wsn.2015.78009.CrossRefGoogle Scholar
  20. 20.
    Meghanathan, N. (2012). Graph theory algorithms for mobile ad hoc networks. Informatica—An International Journal of Computing and Informatics, 36, 185–200.MathSciNetGoogle Scholar
  21. 21.
    Singh, S. P., & Sharma, S. C. (2015). A survey on research issues in wireless sensor networks. Open Transmission in Wireless Sensor Networks, 2, 1–18.Google Scholar
  22. 22.
    Liu, L., Li, X., Jin, J., & Huang, Z. (2012). Graph-based routing, broadcasting and organizing routing, broadcasting algorithms for networks and organizing algorithms for ad-hoc networks. Wireless Ad-Hoc Networks, 1, 1.  https://doi.org/10.5772/54146.Google Scholar
  23. 23.
    Kugler, P., Nordhus, P., & Eskofier, B. (2013). Shimmer, Cooja and Contiki: A new toolset for the simulation of on-node signal processing algorithms. In 2013 IEEE international conference body sensors networks, BSN 2013. (2013). 10.1109/BSN.2013.6575497.Google Scholar
  24. 24.
    Kamalesh, V. N., & Srivatsa, S. K. (2009) Topological design of minimum cost survivable computer communication networks, bipartite graph method. International Journal of Computer Science and Information Security. http://arxiv.org/abs/0908.1033.
  25. 25.
    Saxena, P. C., Sabharwal, S., & Maneesha, (2012). An efficient constructive approximation approach to design A K-connected network topology. Procedia Technology, 4, 140–144.  https://doi.org/10.1016/j.protcy.2012.05.020.CrossRefGoogle Scholar
  26. 26.
    Pietro Gonizzi, I., & Duquennoy, S. (2013). *Hands on Contiki OS and Cooja simulator: Exercises Part II, Internet of Things and Smart Cities Ph.D. School 2013-University of Parma (pp. 1–15).Google Scholar
  27. 27.
    Wikipedia. [online] https://en.wikipedia.org/. Accessed February 07, 2016.
  28. 28.
    Baranidharan, B. (2011). A new graph theory based routing protocol for wireless sensor networks. International Journal on Applications of Graph Theory in Wireless Ad hoc Networks and Sensor Networks, 3(4), 15–26.CrossRefGoogle Scholar
  29. 29.
    Pose, R., & Gondal, I. (2009). A cross-layer approach for QoS topology control in wireless ad hoc networks. In TENCON 2009–2009 IEEE region 10 conference,  https://doi.org/10.1109/TENCON.2009.5395950.
  30. 30.
    Stojmenovic, I. (2012). A general framework for broadcasting in static to highly mobile wireless ad hoc, sensor, robot and vehicular networks, In IEEE 18th International conference on parallel and distributed systems (ICPADS), 2012,  https://doi.org/10.1109/ICPADS.2012.12.
  31. 31.
    Ali, Z. H., Ali, H. A., & Badawy, M. M. (2015). Internet of Things (IoT): Definitions, Challenges and Recent Research Directions. International Journal of Computer Applications, 128(1), 37–47.CrossRefGoogle Scholar
  32. 32.
    Rani, S., Talwar, R., Malhotra, J., Ahmed, S., Sarkar, M., & Song, H. (2015). A novel scheme for an energy efficient internet of things based on wireless sensor networks. Sensors, 15(11), 28603–28626.CrossRefGoogle Scholar
  33. 33.
    Ernst, J. B., & Denko, M. K. (2011). The design and evaluation of fair scheduling in wireless mesh networks. Journal of Computer and System Sciences, 77, 652–664.  https://doi.org/10.1016/j.jcss.2010.02.006.MathSciNetCrossRefGoogle Scholar
  34. 34.
    Pirzada, A. A., Portmann, M., Wishart, R., & Indulska, J. (2009). SafeMesh: A wireless mesh network routing protocol for incident area communications. Pervasive and Mobile Computing, 5, 201–221.  https://doi.org/10.1016/j.pmcj.2008.11.005.CrossRefGoogle Scholar
  35. 35.
    Gross, J. L., & Yellen, J. (2005). Graph theory and its applications (2nd ed.). Boca Raton: CRC Press, ISBN No: 9780429190544.Google Scholar
  36. 36.
    Dâmaso, A., Rosa, N., & Maciel, P. (2014). Reliability of wireless sensor networks. Sensors (Basel), 14, 15760–15785.  https://doi.org/10.3390/s140915760.CrossRefGoogle Scholar
  37. 37.
    Rao, I. H. N. R., & Raju, S. V. S. R. (2009). Semi-complete graphs. International Journal of Computational Cognition, 7(3), 50–54.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Shanmuk Srinivas Amiripalli
    • 1
    Email author
  • Veeramallu Bobba
    • 1
  1. 1.Department of Computer Science and EngineeringK L UniversityGunturIndia

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