Links table
Abstract and 1. Introduction
2 methodology
3 devices
4 programs
5 network
6 consensus
7 Economies of Crusher Currency
8 applications interface customer
9 Judgment
10 geography
11 case studies
12 discussion and references
A. Decentralization and policy making
Software test
C. Get brief reviews for each layer
D. Decentralization
E. It carries the error and decentralization
D measure decentralization
Our work provides a framework for decentralization analysis in Blockchain, but not specific measures to measure it quantitatively. For example, the scale can set the number one to reflect the proximity of the system to one point of failure, given the distribution of resources to a group of relevant parties. Here, we review in short some standards, at a high level, and let the future work to explore alternatives and accounts on real data. The first option is the enthopotropia [159]. In short, Interopia measures a random variable in uncertainty in its potential results. In our preparation, the greater the number of entrance parts in the distribution of resources, the more diverse, and thus the more centralized the component. Min -NTROPY, that is [150] It can also be used because it also provides a lower limit. The alternative is a genetic laboratory [154]. Jenny expresses the percentage of the distance between the 45O line and the curve that draws the cumulative wealth of the lower x from the population. Intuitively, the genetic value means 0 ideal equality, where each person has the same amount of resources, while 1 reveals severe inequality. Alternative scales can also help assess different aspects of decentralization. Examples from the traditional economy are theil [164]Atkinson [8]And Herfindahl-Hirschman [151] Indicators. Depending on the Blockchain space, the scale used often is the Nakamoto coefficient [144]Which measures the minimum number of parties that control the majority of resources. However, the systematic comparison of all alternatives is an interesting question for the future research.
E tolerance and decentralization error
No centralization is dispersed through a large group of parties. This apparently useful for tolerance systems with Byzantine rift (BFT). On the other hand, it may be the opposite results of other concepts of errors. Specifically, the goal of BFT Systems is to maintain corruption for some of the (limited) participants. Therefore, avoiding individual failure points and distributing system operation is especially useful in this context. The more decentralized BFT, the more parties the opponent needs to damage. The systems may not be other than the BFT, which is, for example, tolerant of error, able to maintain the corruption of any participant. In other words, even if one of the participants act in a Byzantine manner, the system’s characteristics cannot be guaranteed. Thus, the more an uncontrolled system, the greater the surface of the attack. Therefore, its security depends on the weakest security. For larger numbers than the participants, for example, if the system is more central to cancel it, the probability of the opponent will spoil any participant usually increases, because the participants often do not have the same level of safety. Therefore, exploring the relationship between decentralization and tolerance with errors, as well as the settings in which decentralization is useful and those that are not in it, is another interesting topic for research in the future.
