Distributed systems
A. Matani; A. Sahafi; A. Broumandnia
Abstract
Background and Objectives: Blockchain technology as a distributed and tamper-proof data ledger is attracting more and more attention from various fields around the world. Due to the continuously growing of the blockchain in both transaction data and the number of nodes joining the network, scalability ...
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Background and Objectives: Blockchain technology as a distributed and tamper-proof data ledger is attracting more and more attention from various fields around the world. Due to the continuously growing of the blockchain in both transaction data and the number of nodes joining the network, scalability emerges as a challenging issue. Methods: In this survey, the existing scalability solutions in the blockchain are discussed under five categories including on-chain scalability, off-chain scalability, scalable consensus mechanisms, DAG-based scalability, and horizontal scalability through sharding. Meanwhile, the novelties they have created on the fundamental layers of the blockchain architecture are investigated.Results: As a result, the advantages and disadvantages of the discussed mechanisms are pointed out, and a comparison between them in terms of different scalability metrics such as throughput, latency, bandwidth, and storage usage is presented. Therefore, this study provides a comprehensive understanding of the various aspects of blockchain scalability and the available scalability solutions. Finally, the research directions and open issues in each category are argued to motivate further improvement efforts for blockchain scalability in the future.Conclusion: Scalability allows blockchain system to sustain its performance as it grows up. Lack of scalability has a negative effect on the mass adoption of the blockchain in practical environments. This paper presents a profound analysis of the existing scalability solutions, the issues and challenges they address, and the ones that are not resolved yet. Consequently, it inspires novel ideas for more scalable and efficient blockchains in the future.
Distributed systems
I. Sayedi; M.H. Fatehi; M. Simab
Abstract
Background and Objectives: Distributed generation (DG) sources are modeled using an ideal DC voltage source connected to the microgrid via voltage source converters (VSCs). Model predictive control presents a distinct method for energy processing.Methods: In this method, the electric power converter ...
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Background and Objectives: Distributed generation (DG) sources are modeled using an ideal DC voltage source connected to the microgrid via voltage source converters (VSCs). Model predictive control presents a distinct method for energy processing.Methods: In this method, the electric power converter is considered a power amplifier with a discrete and nonlinear structure. Therefore, unlike linear control methods, the discrete and nonlinear nature of the converter is considered in this method. In this paper, the distributed model predictive controller was selected from among different methods of load allocation among DG sources due to its more advantages compared to the linear quadratic regulator (LQR) controller.Results: It has been Proposed that we could obtain better results in predictive control, utilizing similarity transform in the state matrix and its modification. In this research, all the simulations have been performed in the MATLABSimpower environment of MATLAB software.Conclusion: Moreover, to demonstrate the superior performance of the model predictive controller compared to the LQR controller, both performance modes of the microgrid, namely the grid-connected and islanding modes, have been considered.
