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Performance of Routing Algorithm Remote Operation in Cloud Environment for IoT Devices

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper proposes an advanced routing method in the purpose of increasing IoT routing device’s power-efficiency, which allows to centralize routing tables computing as well as to push loading, related to routing tables computation, towards the Cloud environment at all. We introduced a phased solution for the formulated task. Generally, next steps were performed: stated requirements for the system with Cloud routing, proposed possible solution, and developed the whole system’s structure. For a proper study of the efficiency, the experiment was conducted using the developed system’s prototype for real-life cases, each represents own cluster size (several topologies by each size), used sizes are: 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27 and 29. Expectable results for this research – decrease the time of cluster’s reaction on topology changes (delay, needed to renew routing tables), which improves system’s adaptivity.
Słowa kluczowe
Rocznik
Strony
367--373
Opis fizyczny
Bibliogr. 25 poz., wykr., rys., tab.
Twórcy
  • Lviv Polytechnic National University, Ukraine
autor
  • Lviv Polytechnic National University, Ukraine
  • Lviv Polytechnic National University, Ukraine
autor
  • Lviv Polytechnic National University, Ukraine
autor
  • Lviv Polytechnic National University, Ukraine
autor
  • Lviv Polytechnic National University, Ukraine
Bibliografia
  • [1] A. Murtala, Z. S. Subashini, P. Vetrivelan, and S. Proceedings, Lecture Notes in Electrical Engineering 493 Wireless Communication Networks and Internet of Things, Springer Singapore, vol. VI, 2019.
  • [2] L. M. Camarinha-Matos, S. Tomic, and P. Graça, Eds., Technological Innovation for the Internet of Things, vol. 394. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.
  • [3] A. Suzdalenko and I. Galkin, “Instantaneous, Short-Term and Predictive Long-Term Power Balancing Techniques in Intelligent Distribution Grids,” 2013, pp. 343–350.
  • [4] S. Rani and S. H. Ahmed, Multi-hop Routing in Wireless Sensor Networks. Singapore: Springer Singapore, 2016.
  • [5] M. Klymash, N. Peleh, O. Shpur and I. Lutsiuk, “Clustering model of cloud centers for big data processing”, 14th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, 2018.
  • [6] A. Orda and R. Rom, “Optimal Routing with Packet Fragmentation in Computer Networks,” Int. J. Networks, vol. 29, no. 1, pp. 11–28, 1997.
  • [7] P. Kuila and P. K. Jana, Clustering and Routing Algorithms for Wireless Sensor Networks, 2018.
  • [8] M. Klymash, O. Lavriv, T. Maksymyuk and M. Beshley, “State of the art and further development of information and communication systems”, IEEE International Scientific Conference “Radio Electronics and Info Communications”, 2016.
  • [9] O. K. Sulaiman, A. M. Siregar, K. Nasution, and T. Haramaini, “Bellman Ford algorithm - In Routing Information Protocol (RIP),” J. Phys. Conf. Ser., vol. 1007, no. 1, 2018.
  • [10] J. B. Singh and R. C. Tripathi, “Investigation of Bellman-Ford Algorithm, Dijkstra’s Algorithm for suitability of SPP,” 2018.
  • [11] L. Wang, Y. Cui, I. Stojmenovic, X. Ma, and J. Song, “Energy efficiency on location based applications in mobile cloud computing: A survey,” Computing, vol. 96, no. 7, pp. 569–585, 2014.
  • [12] W. Jackson, JSON Quick Syntax Reference, Apress, 2016.
  • [13] R. Reagan, Web Applications on Azure. Berkeley, CA: Apress, 2018.
  • [14] S. Machiraju and S. Gaurav, Hardening azure applications : techniques and principles for building large-scale, mission-critical applications, Apress, 2019.
  • [15] L. Carlson, Programming for PaaS. O’Reilly Media, Inc, 2013.
  • [16] “What is PaaS? Platform as a Service | Microsoft Azure.” [Online]. Available: https://azure.microsoft.com/en-us/overview/what-is-paas/. [Accessed: 01-Feb-2019].
  • [17] M. Grinberg, Flask Web Development, 2014.
  • [18] B. Swen, “Outline of initial design of the Structured Hypertext Transfer Protocol,” J. Comput. Sci. Technol., vol. 18, no. 3, pp. 287–298, May 2003.
  • [19] S. Patni, Pro RESTful APIs, 2017.
  • [20] S. Guha, Computer Graphics Through OpenGL® : from theory to experiments, CRC Press, 2019.
  • [21] K. Geisshirt, A. Olsson, R. Voss, and E. Zattin, Git version control cookbook : leverage version control to transform your development workflow and boost productivity, 2014.
  • [22] R. Reagan, Web applications on Azure : developing for global scale, Apress, 2018.
  • [23] M. Ravasi and M. Mattavelli, “High-level algorithmic complexity evaluation for system design,” J. Syst. Archit., vol. 48, no. 13–15, pp. 403–427, 2003.
  • [24] “Algorithmic complexity.” [Online]. Available: https://devopedia.org/algorithmic-complexity. [Accessed: 01-Feb-2019].
  • [25] Anna G. Chunovkina, Leonid A. Mironovsky, Valery A. Slaev, Metrology and theory of measurement, 2013.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-52e1e0b3-fdeb-4fff-bb60-3a5adcffb245
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