How to prove that software is decentralized

1. Decentralized exchange refers to the virtual currency exchange. Investors are expected to choose carefully. First of all, there is no formal virtual digital currency exchange or formal trading platform in China, so the state does not recognize virtual digital currency. If investors are involved, they may lose everything.

2. What is "decentralization"

"decentralization" is translated from the English word decentralization, which is composed of the prefix de -, stem central and suffix ization. Among them, the stem central means "center", the suffix - ization means "... Hua", and the prefix de - has the meanings of leaving, removing, canceling and opposite. Therefore, it is very accurate to translate it into decentralization

what is the meaning of decentralization

vitalik buterin, founder of Ethereum, published the article "the meaning of decentralization" in February 2017, elaborating the meaning of decentralization. He thinks that we should distinguish the centralization and decentralization of computer software from three perspectives: architecture, governance and logic

Architecture centralization refers to the number of nodes that the system can tolerate and continue to run; Governance centralization refers to how many indivials and organizations are needed to control the system; Logic centralization refers to whether the interface and data presented by the system are like a single whole

blockchain is a unified account book of the whole network, so it is logically centralized, which is beyond doubt. From the perspective of architecture, blockchain is based on peer-to-peer network, so it is decentralized. From the perspective of governance, blockchain makes it difficult for a few people to control the whole system through consensus algorithm, so it is decentralized. The decentralization of architecture and governance brings three benefits to blockchain: fault tolerance, anti attack and anti collusion

five differences between blockchain and traditional distributed system

as a new kind of distributed system, blockchain is often mistakenly regarded as a distributed database or log system. In fact, there is a fundamental difference between blockchain and traditional distributed system, namely decentralization. Now let's look at the main differences between blockchain and traditional distributed systems:

(1) consistency algorithm: what blockchain needs to solve is the Byzantine general problem, that is, there are one or more fraulent nodes in the network, which may deliberately violate the protocol or transmit wrong data, Therefore, Byzantine fault-tolerant consensus algorithms, such as BFT, pow, POS, are often used in blockchain; The traditional distributed system only needs to consider the node failure and communication errors, and often uses consistency algorithms such as Paxos and raft, which can not resist the fraulent nodes

(2) central controller: there is no central controller in the blockchain network, and no node can control or coordinate the generation of ledger data. All nodes coordinate through consensus algorithm to generate consistent ledger. However, the traditional publishing system is often controlled by one organization, which uniformly dispatches all nodes to participate in the calculation

(3) rule making: the rule of blockchain is consensus protocol, also known as consensus mechanism, and consensus algorithm is a part of it. Consensus mechanism is generally designed and developed by a person or a team, and the corresponding proceres are developed for the community to use. This seems to be the same as the traditional distributed system, but the change and upgrading of the consensus mechanism of the blockchain requires the community to have a consensus on it. If no consensus can be reached, anyone can implement hard bifurcation and build another community and chain. This is the decentralization process of consensus mechanism.

3. The so-called Internet platform is to develop and utilize the information resources of the Internet. I personally understand that the instry should be concentrated together and one key solution should be taken to save the middle cumbersome steps. The 16 year Internet plus summit, which is the latest Internet plus summit held in Beijing in 16, will be held in the 16 month of. This will further promote the development of Internet +. To promote the integration of "Internet plus" with government, people's livelihood and all walks of life, we can learn about this area.

4. Chongqing jinwowo analysis is based on distributed bookkeeping, collective agreement and intelligent consensus mechanism. The information characteristics of blockchain technology, such as decentralization, open sharing, authenticity and reliability, once attracted great attention. Among them, the characteristics of decentralization are particularly popular, and the attention to decentralization has existed since the birth of blockchain.

5. On the Internet, the most typical example of centralization is the portal website. By collecting all the information on the Internet on its own platform, the portal website forms a central node, and then extends many branches from this node. Generally speaking, only one node is making decisions. According to the analysis of jinwowo network technology, the characteristics leading to centralization are as follows:

1. The central node grasps the information of distributed nodes

2. The sub nodes do not master the information of other nodes (centralization, non-public transactions)

moreover, the pain point of centralization is that the security of the system depends on the security of the central node, and the distributed node has no control over it.

6.

Center

1. Click "start" in the menu bar above word

2. Select the words you want to put in the middle

3. Click the center alignment in "paragraph"

7. It is an open source application that runs automatically, stores its data on the blockchain, motivates it in the form of password token, and operates with protocols that show valuable proof.

8. First, the goal of refined operation. For example, if your proct is just a tool, I'm afraid it can't be said that there are too many refined operations. Generally, it's enough to do a good job in routine user behavior analysis, and then cooperate with user qualitative research to guide proct design; If it is a content-based proct, or a proct with both function and content, it really needs to be considered. 2. Design statistical framework suppose that users will frequently interact and use functions on your app, and browse or generate content at the same time, so you need to design your statistical framework well while designing procts. 2、 Data collection first lists the data items you need, then evaluates which parts need to be reported by app and which parts can be counted in the background, and then adds them on the front and back platforms. Generally speaking, the collected data reported by app must be carefully checked and tested before release, because once the version is released and the data collection goes wrong, not only the previous efforts are wasted, but also a lot of dirty data will be brought. At the same time, the running efficiency of the client may be reced, and the gain is not worth the loss. 2. After data collation and data collection, all kinds of original data need to be processed into intuitive and visible data needed by proct managers. Here, we need to do some basic data logical association and display, so we won't repeat it. 3. Data analysis according to the statistical framework designed at the beginning, you can clearly see the data you need. Of course, the above is just a more basic analysis. If you get these data, you can analyze that users who use a function also like B function. The two are closely related. Can you consider more integration or interface adjustment in front-end design; For example, by analyzing the click stream, what are the paths for most users to visit or use the app, and do they hide the core functions too deeply? For another example, we can analyze different user attributes, such as male users and female users. Do they have significant differences in user behavior? wait. There is a big gap between the data analysis methods and models of different procts, which cannot be explained at once. So the above are more examples. 3、 Some principles need to be noted: 1. The data itself is objective, but the data interpreted must be subjective. The same data analyzed by different people is likely to draw completely opposite conclusions, so we must not analyze it with opinions in advance (for example, if we have hypotheses, we can use the data to demonstrate them); 2. Data collection by app must be of low priority. It can't affect proct performance and user experience because of data collection, and it can't collect user's privacy data (although many domestic apps don't do this); 3. Data is not omnipotent. You should trust your own judgment.