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Parameterized Pulsed Transaction Injection Computation Model And Performance Optimizer For IOTA-Tango

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Advances on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 24))

Abstract

To keep a cryptocurrency system at its optimal performance, it is necessary to utilize the resources and avoid latency in its network. To achieve this goal, dynamically and efficiently injecting the unverified transactions to enable synchronicity based on the current system configuration and the traffic of the network is crucial. To meet this need, we design the pulsed transaction injection parameterization (PTIP) protocol to provide a preliminary dynamic injection mechanism. To further assist the network to achieve its subgoals based on various house policies (such as maximal revenue to the network or maximum throughput of the system), we turn the house policy based optimization into a 0/1 knapsack problem. To efficiently solve these NP-hard problems, we adapt and improve a fully polynomial time approximation scheme (FPTAS) and dynamic programming as components in our approximate optimization algorithm.

Equal contribution among authors.

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References

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Acknowledgement

The authors gratefully acknowledge support from the State University of New York Polytechnic Institute.

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Authors and Affiliations

  1. State University of New York Polytechnic Institute, 100 Seymour Ave, Utica, NY, 13502, USA

    Bruno Andriamanalimanana, Chen-Fu Chiang, Jorge Novillo, Sam Sengupta & Ali Tekeoglu

Authors
  1. Bruno Andriamanalimanana
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  2. Chen-Fu Chiang
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  3. Jorge Novillo
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  4. Sam Sengupta
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  5. Ali Tekeoglu
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Corresponding author

Correspondence to Chen-Fu Chiang .

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Editors and Affiliations

  1. Dept De Ciències De La Computació, Universitat Politècnica De Catalunya, Barcelona, Spain

    Fatos Xhafa

  2. Tunghai University, Taichung, Taiwan

    Fang-Yie Leu

  3. Università Della Campania Luigi Vanvitelli, Caserta, Italy

    Massimo Ficco

  4. Tunghai University, Taichung, Taiwan

    Chao-Tung Yang

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Andriamanalimanana, B., Chiang, CF., Novillo, J., Sengupta, S., Tekeoglu, A. (2019). Parameterized Pulsed Transaction Injection Computation Model And Performance Optimizer For IOTA-Tango. In: Xhafa, F., Leu, FY., Ficco, M., Yang, CT. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-030-02607-3_7

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  • DOI: https://doi.org/10.1007/978-3-030-02607-3_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02606-6

  • Online ISBN: 978-3-030-02607-3

  • eBook Packages: EngineeringEngineering (R0)

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