Read what is a full Turing-complete protocol in one article

How smart contract networks can scale is a potential problem.

Read what is a full Turing-complete protocol in one article

Currently, 75% of the market capitalization that exists in public blockchains cannot be used in a reliable way in smart contracts, which is critical to the construction of the industry as a whole. And how the current smart contract network will scale is a potential problem, both in terms of short- and long-term impact. Now, a solution called a fully Turing-complete protocol has been proposed, so let’s take a look at what this actually is.

At this stage, most emerging networks are implemented using Proof-of-Stake consensus mechanisms (Proof-of-Stake) or similar, and these protocols derive their network security from their native tokens. However, there is an immediate and unavoidable problem with proof-of-stake: the consistent design does not securely guarantee alternative uses of the platform’s native tokens. If token holders can get higher returns by providing collateral to create stable coins, then as economic rationalists, they are likely to do so. And the result of doing so would make the tokens unlockable and compromise the security of the network. So it’s possible that this is the main reason why Ether can remain a leader in decentralized finance and has been the most used blockchain despite relatively high transaction costs and low transaction throughput.

There is also a longer term issue in that as the use of proof-of-stake networks increases, and the value of building on top of that, the value of platform tokens must increase or the network will become insecure. This may be a good thing for token investors, but not for those who want to see decentralization become part of the mainstream approach. This is due to the fact that in order to ensure that the value of platform tokens increases, funds must be diverted from other uses to purchase tokens. Logically, if smart contract networks using proof of stake become the common way of doing business, then the need to transfer funds from other sources just to ensure that value is built on those networks would make the cost of doing business ridiculously high. As a result, this is almost impossible to happen. Since proof of stake only scales transaction volume, but not value, proof of stake is at best a stopgap measure, not a final solution.

Fully Turing-complete protocols

So is there a solution that scales both volume and value? Here, we have to mention the Full Turing Completeness Protocol.

The core of this protocol is actually based on a new scalable smart contract platform that no longer links cybersecurity to the value of the token. Of course, some platforms still require a token to operate the network in order to stop transactions that compromise network security. The protocol’s consistency topology is unique because it does not rely on economic incentives that affect high-value and high-risk use cases, while still enabling security.

With Turing-complete protocols, there will be no need for a centralized medium

Such protocols work as follows: Native token owners on the platform may send their tokens to a collection of smart contracts, and by doing so, users provide collateral to the system, who are also known as agents, and there will be many similar agents in the system.

Suppose one of these agents sends a certain amount of native tokens to the system, and the system will require a certain collateral ratio, which means that the agent must at all times provide the system with the amount of minted coins allocated to them that is equal to the collateral ratio. At this point, an initiator initiates a transaction to the system for a fixed fee. At this point, that transaction tells the system which address to send the coin to on the platform when the minting is complete. If capacity is available in the system, the collateral used to secure the mint will be locked against the initiator’s upcoming transaction for a period of time, so that the initiator does not have to trust the agent. In response, a set of instructions is generated that tells the originator the address of the agent to send the collateral to on the ledger and the last ledger index to use. If there is not enough capacity in the system to issue the required number of minted coins, then the originator will refund the fee.

In the above scenario or in a purely decentralized environment, if there are other agents in the system with sufficient collateral, then he can mint enough tokens and redeem them immediately. In the second case, the responsibility is essentially transferred to the rest of the system. If the agent does nothing and remains in default on the collateral ratio, his collateral is automatically auctioned for the value of the minted tokens issued for him, and the agent keeps all the remaining collateral.

Currently, the complexity of placing collateral on the platform is that smart contracts on the public blockchain have no control over the addresses on the distributed ledger database because smart contracts currently have no reliable way to store keys in a truly confidential manner. Using code alone to place collateral on the platform would require participants to come together with multiple signature addresses that they jointly control, so if just some of the many participants sign a transaction, then that transaction is authorized. Since any user of an asset published by multiple signature addresses must trust these participants, the asset is neither trusted nor decentralized.

It is worth noting that the general rules of the fully Turing-complete protocol apply to any of the non-Turing-complete tokens and can be applied to the network systems and governance of the tokens it supports. Ripple is known to exist effectively in Turing-complete networks, and can be trusted to interoperate with Ether through interoperability protocols such as Cosmos and Polkadot, or through well-defined bridge protocols. In short: these platforms can be used as smart contract platforms for Ripple, and as reliable channels for Ripple to be transferred to other platforms.

Full Turing-complete protocol use cases

Currently, there are already practical use cases for fully Turing-complete protocols. Some blockchain networks based on Full Turing-complete protocols also make use of the Ether Virtual Machine (EVM) to enable the network to run Turing-complete smart contracts, such as the Flare Network, an example of which is the Flare native token called Spark, a non-Turing-complete token that is well suited for smart contracts because Spark has no network security concerns. Flare’s fully Turing-complete protocol, called FXRP, allows initiators to securely send their Ripple coins to a set of addresses (called proxies) on the Ripple ledger, and then the FXRP smart contract on Flare will issue FXRP on Flare that is converted 1:1 with Ripple coins and is secured by Spark. When FXRP holders wish to redeem them for Ripple, they send them back to Flare on the FXRP smart contract, and the agent then sends the Ripple to the recipient’s address on the Ripple book. If the agent does not complete the redemption quickly enough, then the redeemer will be compensated with the equivalent value of Ripple coins, as well as compensation for the transaction costs incurred to purchase Ripple coins.

Spark token ownership allows contributions to the Flare Time Series Prophecy Machine (FTSO), which is designed to provide accurate estimates of Flare data from off-chain while remaining decentralized.The structure of the Flare Time Series Prophecy Machine can provide feed estimates for individual time series, such as XRP/ Spark transaction pair prices are an example of a single time series.

Each time series output by the Flare Time Series Predictor will typically have two groups of participants: the first group is Spark token holders; the second group is the holders of application-dependent tokens, called F-assets (F-assets). In FXRP applications, the F-assets are the FXRP tokens themselves. For more complex applications, such as derivative applications where the application requires multiple time series, the F-assets may be more similar to the issued governance tokens.

In effect, the Flare time series prognosticator will provide a price estimate every few seconds. However, not all Spark holders will want or be able to run the hardware to contribute to the Flare time series prophecy machine, and in addition, they may not be interested in network governance voting. Therefore, Flare sets up two responsibilities for voting that can be separated from the tokens themselves and delegated to others to handle separately. Not only that, the delegation can be cancelled at any time, as it is automatically cancelled when the token is moved from one address to another, meaning that the voting rights come with the token. The mechanism also allows SDAs such as FXRP to delegate Spark holders’ votes to the ultimate owner, who can then further delegate those votes to the entity he wants to vote on his behalf.

Arguably, Flare combines the value of a non-Turing-complete token with the transformative power of a network smart contract, and can scale by token value and transaction volume.

Summing up

The best communities are those that have token assets that support the use of tokens with Turing-complete smart contracts, and these communities will use the tokens and benefit the token holders.

Traditional forks attempt to capture the user base of an existing network and disengage it entirely, often in an adversarial relationship with the original blockchain. In contrast, utility forks aim to bring value back to the original chain, not away from it, and can do some of the things they do best, such as: settle quickly; bring smart contract functionality; and create a de-trusted pipeline to other blockchains.

The fully Turing-complete protocol can securely enable tokens to be de-trusted for issuance, use and redemption on the blockchain. The protocol can connect the platform to other network protocols and can be extended to any non-Turing-complete token; in fact, trustless interoperability with Ether is possible on such platforms through some interoperability protocol, or through a well-defined bridge protocol.

Holders of platform-native tokens can get their tokens back by using these tokens as collateral, de-trusting issuance and redemption, and providing data to the platform’s time series prophecy machine, all without competing with each other. Platforms with fully Turing-complete protocols can not only combine the value of non-Turing-complete tokens with the transformative power of smart contracts on blockchain networks, but can also scale efficiently based on value and transaction throughput.

Posted by:CoinYuppie,Reprinted with attribution to:
Coinyuppie is an open information publishing platform, all information provided is not related to the views and positions of coinyuppie, and does not constitute any investment and financial advice. Users are expected to carefully screen and prevent risks.

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