Author: Gamals Ahmed, CoinEx Business Ambassadorsubmitted by CoinEx_Institution to u/CoinEx_Institution [link] [comments]
The DFINITY blockchain computer provides a secure, performant and flexible consensus mechanism. At its core, DFINITY contains a decentralized randomness beacon, which acts as a verifiable random function (VRF) that produces a stream of outputs over time. The novel technique behind the beacon relies on the existence of a unique-deterministic, non-interactive, DKG-friendly threshold signatures scheme. The only known examples of such a scheme are pairing-based and derived from BLS.
The DFINITY blockchain is layered on top of the DFINITY beacon and uses the beacon as its source of randomness for leader selection and leader ranking. A “weight” is attributed to a chain based on the ranks of the leaders who propose the blocks in the chain, and that weight is used to select between competing chains. The DFINITY blockchain is layered on top of the DFINITY beacon and uses the beacon as its source of randomness for leader selection and leader ranking blockchain is further hardened by a notarization process which dramatically improves the time to finality and eliminates the nothing-at-stake and selfish mining attacks.
DFINITY consensus algorithm is made to scale through continuous quorum selections driven by the random beacon. In practice, DFINITY achieves block times of a few seconds and transaction finality after only two confirmations. The system gracefully handles temporary losses of network synchrony including network splits, while it is provably secure under synchrony.
1.INTRODUCTIONDFINITY is building a new kind of public decentralized cloud computing resource. The company’s platform uses blockchain technology which is aimed at building a new kind of public decentralized cloud computing resource with unlimited capacity, performance and algorithmic governance shared by the world, with the capability to power autonomous self-updating software systems, enabling organizations to design and deploy custom-tailored cloud computing projects, thereby reducing enterprise IT system costs by 90%.
DFINITY aims to explore new territory and prove that the blockchain opportunity is far broader and deeper than anyone has hitherto realized, unlocking the opportunity with powerful new crypto.
Although a standalone project, DFINITY is not maximalist minded and is a great supporter of Ethereum.
The DFINITY blockchain computer provides a secure, performant and flexible consensus mechanism. At its core, DFINITY contains a decentralized randomness beacon, which acts as a verifiable random function (VRF) that produces a stream of outputs over time. The novel technique behind the beacon relies on the existence of a unique-deterministic, non-interactive, DKG-friendly threshold signatures scheme. The only known examples of such a scheme are pairing-based and derived from BLS.
DFINITY’s consensus mechanism has four layers: notary (provides fast finality guarantees to clients and external observers), blockchain (builds a blockchain from validated transactions via the Probabilistic Slot Protocol driven by the random beacon), random beacon (provides the source of randomness for all higher layers like smart contract applications), and identity (provides a registry of all clients).
DFINITY’s consensus mechanism has four layers
Figure1: DFINITY’s consensus mechanism layers
1. Identity layer:
Active participants in the DFINITY Network are called clients. Where clients are registered with permanent identities under a pseudonym. Moreover, DFINITY supports open membership by providing a protocol for registering new clients by depositing a stake with an insurance period. This is the responsibility of the first layer.
2. Random Beacon layer:
Provides the source of randomness (VRF) for all higher layers including ap- plications (smart contracts). The random beacon in the second layer is an unbiasable, verifiable random function (VRF) that is produced jointly by registered clients. Each random output of the VRF is unpredictable by anyone until just before it becomes avail- able to everyone. This is a key technology of the DFINITY system, which relies on a threshold signature scheme with the properties of uniqueness and non-interactivity.
3. Blockchain layer:
The third layer deploys the “probabilistic slot protocol” (PSP). This protocol ranks the clients for each height of the chain, in an order that is derived determin- istically from the unbiased output of the random beacon for that height. A weight is then assigned to block proposals based on the proposer’s rank such that blocks from clients at the top of the list receive a higher weight. Forks are resolved by giving favor to the “heaviest” chain in terms of accumulated block weight — quite sim- ilar to how traditional proof-of-work consensus is based on the highest accumulated amount of work.
The first advantage of the PSP protocol is that the ranking is available instantaneously, which allows for a predictable, constant block time. The second advantage is that there is always a single highest-ranked client, which allows for a homogenous network bandwidth utilization. Instead, a race between clients would favor a usage in bursts.
4. Notarization layer:
Provides fast finality guarantees to clients and external observers. DFINITY deploys the novel technique of block notarization in its fourth layer to speed up finality. A notarization is a threshold signature under a block created jointly by registered clients. Only notarized blocks can be included in a chain. Of all RSA-based alternatives exist but suffer from an impracticality of setting up the thresh- old keys without a trusted dealer.
DFINITY achieves its high speed and short block times exactly because notarization is not full consensus.
DFINITY does not suffer from selfish mining attack or a problem nothing at stake because the authentication step is impossible for the opponent to build and maintain a series of linked and trusted blocks in secret.
DFINITY’s consensus is designed to operate on a network of millions of clients. To en- able scalability to this extent, the random beacon and notarization protocols are designed such as that they can be safely and efficiently delegated to a committee
1.1 OVERVIEW ABOUT DFINITYDFINITY is a blockchain-based cloud-computing project that aims to develop an open, public network, referred to as the “internet computer,” to host the next generation of software and data. and it is a decentralized and non-proprietary network to run the next generation of mega-applications. It dubbed this public network “Cloud 3.0”.
DFINITY is a third generation virtual blockchain network that sets out to function as an “intelligent decentralised cloud,”¹ strongly focused on delivering a viable corporate cloud solution. The DFINITY project is overseen, supported and promoted by DFINITY Stiftung a not-for-profit foundation based in Zug, Switzerland.
DFINITY is a decentralized network design whose protocols generate a reliable “virtual blockchain computer” running on top of a peer-to-peer network upon which software can be installed and can operate in the tamperproof mode of smart contracts.
DFINITY introduces algorithmic governance in the form of a “Blockchain Nervous System” that can protect users from attacks and help restart broken systems, dynamically optimize network security and efficiency, upgrade the protocol and mitigate misuse of the platform, for example by those wishing to run illegal or immoral systems.
DFINITY is an Ethereum-compatible smart contract platform that is implementing some revolutionary ideas to address blockchain performance, scaling, and governance. Whereas
DFINITY could pose a credible threat to Ethereum’s extinction, the project is pursuing a coevolutionary strategy by contributing funding and effort to Ethereum projects and freely offering their technology to Ethereum for adoption. DFINITY has labeled itself Ethereum’s “crazy sister” to express it’s close genetic resemblance to Ethereum, differentiated by its obsession with performance and neuron-inspired governance model.
Dfinity raised $61 million from Andreesen Horowitz and Polychain Capital in a February 2018 funding round. At the time, Dfinity said it wanted to create an “internet computer” to cut the costs of running cloud-based business applications. A further $102 million funding round in August 2018 brought the project’s total funding to $195 million.
In May 2018, Dfinity announced plans to distribute around $35 million worth of Dfinity tokens in an airdrop. It was part of the company’s plan to create a “Cloud 3.0.” Because of regulatory concerns, none of the tokens went to US residents.
DFINITY be broadening and strengthening the EVM ecosystem by giving applications a choice of platforms with different characteristics. However, if DFINITY succeeds in delivering a fully EVM-compatible smart contract platform with higher transaction throughput, faster confirmation times, and governance mechanisms that can resolve public disputes without causing community splits, then it will represent a clearly superior choice for deploying new applications and, as its network effects grow, an attractive place to bring existing ones. Of course the challenge for DFINITY will be to deliver on these promises while meeting the security demands of a public chain with significant value at risk.
1.1.1 DFINITY FUTURE
1.1.2 DFINITY’S VISIONDFINITY’s vision is its new internet infrastructure can support a wide variety of end-user and enterprise applications. Social media, messaging, search, storage, and peer-to-peer Internet interactions are all examples of functionalities that DFINITY plans to host atop its public Web 3.0 cloud-like computing resource. In order to provide the transaction and data capacity necessary to support this ambitious vision, DFINITY features a unique consensus model (dubbed Threshold Relay) and algorithmic governance via its Blockchain Nervous System (BNS) — sometimes also referred to as the Network Nervous System or NNS.
1.2 DFINITY COMMUNITYThe DFINITY community brings people and organizations together to learn and collaborate on products that help steward the next-generation of internet software and services. The Internet Computer allows developers to take on the monopolization of the internet, and return the internet back to its free and open roots. We’re committed to connecting those who believe the same through our events, content, and discussions.
1.3 DFINITY ROADMAP (TIMELINE) February 15, 2017February 15, 2017
Ethereum based community seed round raises 4M Swiss francs (CHF)
The DFINITY Stiftung, a not-for-profit foundation entity based in Zug, Switzerland, raised the round. The foundation held $10M of assets as of April 2017.
February 8, 2018
Dfinity announces a $61M fundraising round led by Polychain Capital and Andreessen Horowitz
The round $61M round led by Polychain Capital and Andreessen Horowitz, along with an DFINITY Ecosystem Venture Fund which will be used to support projects developing on the DFINITY platform, and an Ethereum based raise in 2017 brings the total funding for the project over $100 million. This is the first cryptocurrency token that Andressen Horowitz has invested in, led by Chris Dixon.
Dfinity raises a $102,000,000 venture round from Multicoin Capital, Village Global, Aspect Ventures, Andreessen Horowitz, Polychain Capital, Scalar Capital, Amino Capital and SV Angel.
January 23, 2020
Dfinity launches an open source platform aimed at the social networking giants
2.DFINITY TECHNOLOGYDfinity is building what it calls the internet computer, a decentralized technology spread across a network of independent data centers that allows software to run anywhere on the internet rather than in server farms that are increasingly controlled by large firms, such as Amazon Web Services or Google Cloud. This week Dfinity is releasing its software to third-party developers, who it hopes will start making the internet computer’s killer apps. It is planning a public release later this year.
At its core, the DFINITY consensus mechanism is a variation of the Proof of Stake (PoS) model, but offers an alternative to traditional Proof of Work (PoW) and delegated PoS (dPoS) networks. Threshold Relay intends to strike a balance between inefficiencies of decentralized PoW blockchains (generally characterized by slow block times) and the less robust game theory involved in vote delegation (as seen in dPoS blockchains). In DFINITY, a committee of “miners” is randomly selected to add a new block to the chain. An individual miner’s probability of being elected to the committee proposing and computing the next block (or blocks) is proportional to the number of dfinities the miner has staked on the network. Further, a “weight” is attributed to a DFINITY chain based on the ranks of the miners who propose blocks in the chain, and that weight is used to choose between competing chains (i.e. resolve chain forks).
A decentralized random beacon manages the random selection process of temporary block producers. This beacon is a Variable Random Function (VRF), which is a pseudo-random function that provides publicly verifiable proofs of its outputs’ correctness. A core component of the random beacon is the use of Boneh-Lynn-Shacham (BLS) signatures. By leveraging the BLS signature scheme, the DFINITY protocol ensures no actor in the network can determine the outcome of the next random assignment.
Dfinity is introducing a new standard, which it calls the internet computer protocol (ICP). These new rules let developers move software around the internet as well as data. All software needs computers to run on, but with ICP the computers could be anywhere. Instead of running on a dedicated server in Google Cloud, for example, the software would have no fixed physical address, moving between servers owned by independent data centers around the world. “Conceptually, it’s kind of running everywhere,” says Dfinity engineering manager Stanley Jones.
DFINITY also features a native programming language, called ActorScript (name may be subject to change), and a virtual machine for smart contract creation and execution. The new smart contract language is intended to simplify the management of application state for programmers via an orthogonal persistence environment (which means active programs are
not required to retrieve or save their state). All ActorScript contracts are eventually compiled down to WebAssembly instructions so the DFINITY virtual machine layer can execute the logic of applications running on the network. The advantage of using the WebAssembly standard is that all major browsers support it and a variety of programming languages can compile down to Wasm (not just ActorScript).
Dfinity is moving fast. Recently, Dfinity showed off a TikTok clone called CanCan. In January it demoed a LinkedIn-alike called LinkedUp. Neither app is being made public, but they make a convincing case that apps made for the internet computer can rival the real things.
2.1 DFINITY CORE APPLICATIONSThe DFINITY cloud has two core applications:
Whilst conceptually similar to Ethereum, DFINITY employs original and new cryptography methods and protocols (crypto:3) at the network level, in concert with AI and network-fuelled systemic governance (Blockchain Nervous System — BNS) to facilitate Corporate adoption.
DFINITY recognises that different users value different properties and sees itself as more of a fully compatible extension of the Ethereum ecosystem rather than a competitor of the Ethereum network.
In the future, DFINITY hopes that much of their “new crypto might be used within the Ethereum network and are also working hard on shared technology components.”
As the DFINITY project develops over time, the DFINITY Stiftung foundation intends to steadily increase the BNS’ decision-making responsibilities over time, eventually resulting in the dissolution of its own involvement entirely, once the BNS is sufficiently sophisticated.
DFINITY consensus mechanism is a heavily optimized proof of stake (PoS) model. It places a strong emphasis on transaction finality through implementing a Threshold Relay technique in conjunction with the BLS signature scheme and a notarization method to address many of the problems associated with PoS consensus.
2.2 THRESHOLD RELAYAs a public cloud computing resource, DFINITY targets business applications by substantially reducing cloud computing costs for IT systems. They aim to achieve this with a highly scalable and powerful network with potentially unlimited capacity. The DFINITY platform is chalk full of innovative designs and features like their Blockchain Nervous System (BNS) for algorithmic governance.
One of the primary components of the platform is its novel Threshold Relay Consensus model from which randomness is produced, driving the other systems that the network depends on to operate effectively. The consensus system was first designed for a permissioned participation model but can be paired with any method of Sybil resistance for an open participation model.
“The Threshold Relay is the mechanism by which Dfinity randomly samples replicas into groups, sets the groups (committees) up for threshold operation, chooses the current committee, and relays from one committee to the next is called the threshold relay.”
Threshold Relay consists of four layers (As mentioned previously):
2.2.1 HOW DOES THRESHOLD RELAY WORK?Threshold Relay produces an endogenous random beacon, and each new value defines random group(s) of clients that may independently try and form into a “threshold group”. The composition of each group is entirely random such that they can intersect and clients can be presented in multiple groups. In DFINITY, each group is comprised of 400 members. When a group is defined, the members attempt to set up a BLS threshold signature system using a distributed key generation protocol. If they are successful within some fixed number of blocks, they then register the public key (“identity”) created for their group on the global blockchain using a special transaction, such that it will become part of the set of active groups in a following “epoch”. The network begins at “genesis” with some number of predefined groups, one of which is nominated to create a signature on some default value. Such signatures are random values — if they were not then the group’s signatures on messages would be predictable and the threshold signature system insecure — and each random value produced thus is used to select a random successor group. This next group then signs the previous random value to produce a new random value and select another group, relaying between groups ad infinitum and producing a sequence of random values.
In a cryptographic threshold signature system a group can produce a signature on a message upon the cooperation of some minimum threshold of its members, which is set to 51% in the DFINITY network. To produce the threshold signature, group members sign the message
individually (here the preceding group’s threshold signature) creating individual “signature shares” that are then broadcast to other group members. The group threshold signature can be constructed upon combination of a sufficient threshold of signature shares. So for example, if the group size is 400, if the threshold is set at 201 any client that collects that many shares will be able to construct the group’s signature on the message. Other group members can validate each signature share, and any client using the group’s public key can validate the single group threshold signature produced by combining them. The magic of the BLS scheme is that it is “unique and deterministic” meaning that from whatever subset of group members the required number of signature shares are collected, the single threshold signature created is always the same and only a single correct value is possible.
Consequently, the sequence of random values produced is entirely deterministic and unmanipulable, and signatures generated by relaying between groups produces a Verifiable Random Function, or VRF. Although the sequence of random values is pre-determined given some set of participating groups, each new random value can only be produced upon the minimal agreement of a threshold of the current group. Conversely, in order for relaying to stall because a random number was not produced, the number of correct processes must be below the threshold. Thresholds are configured so that this is extremely unlikely. For example, if the group size is set to 400, and the threshold is 201, 200 or more of the processes must become faulty to prevent production. If there are 10,000 processes in the network, of which 3,000 are faulty, the probability this will occur is less than 10e-17.
2.3 DFINITY TOKENThe DFINITY blockchain also supports a native token, called dfinities (DFN), which perform multiple roles within the network, including:
Neuron operators can earn Dfinities by participating in network-wide votes, which could be concerning protocol upgrades, a new economic policy, etc. DFN rewards for participating in the governance system are proportional to the number of tokens staked inside a neuron.
2.4 SCALABILITYDFINITY is constantly developing with a structure that separates consensus, validation, and storage into separate layers. The storage layer is divided into multiple strings, each of which is responsible for processing transactions that occur in the fragment state. The verification layer is responsible for combining hashes of all fragments in a Merkle-like structure that results in a global state fractionation that is stored in blocks in the top-level chain.
2.5 DFINITY CONSENSUS ALGORITHMThe single most important aspect of the user experience is certainly the time required before a transaction becomes final. This is not solved by a short block time alone — Dfinity’s team also had to reduce the number of confirmations required to a small constant. DFINITY moreover had to provide a provably secure proof-of-stake algorithm that scales to millions of active participants without compromising any bit on decentralization.
Dfinity soon realized that the key to scalability lay in having an unmanipulable source of randomness available. Hence they built a scalable decentralized random beacon, based on what they call the Threshold Relay technique, right into the foundation of the protocol. This strong foundation drives a scalable and fast consensus layer: On top of the beacon runs a blockchain which utilizes notarization by threshold groups to achieve near-instant finality. Details can be found in the overview paper that we are releasing today.
The roots of the DFINITY consensus mechanism date back to 2014 when thair Chief Scientist, Dominic Williams, started to look for more efficient ways to drive large consensus networks. Since then, much research has gone into the protocol and it took several iterations to reach its current design.
For any practical consensus system the difficulty lies in navigating the tight terrain that one is given between the boundaries imposed by theoretical impossibility-results and practical performance limitations.
The first key milestone was the novel Threshold Relay technique for decentralized, deterministic randomness, which is made possible by certain unique characteristics of the BLS signature system. The next breakthrough was the notarization technique, which allows DFINITY consensus to solve the traditional problems that come with proof-of-stake systems. Getting the security proofs sound was the final step before publication.
DFINITY consensus has made the proper trade-offs between the practical side (realistic threat models and security assumptions) and the theoretical side (provable security). Out came a flexible, tunable algorithm, which we expect will establish itself as the best performing proof-of-stake algorithm. In particular, having the built-in random beacon will prove to be indispensable when building out sharding and scalable validation techniques.
2.6 LINKEDUPThe startup has rather cheekily called this “an open version of LinkedIn,” the Microsoft-owned social network for professionals. Unlike LinkedIn, LinkedUp, which runs on any browser, is not owned or controlled by a corporate entity.
LinkedUp is built on Dfinity’s so-called Internet Computer, its name for the platform it is building to distribute the next generation of software and open internet services.
The software is hosted directly on the internet on a Switzerland-based independent data center, but in the concept of the Internet Computer, it could be hosted at your house or mine. The compute power to run the application LinkedUp, in this case — is coming not from Amazon AWS, Google Cloud or Microsoft Azure, but is instead based on the distributed architecture that Dfinity is building.
Specifically, Dfinity notes that when enterprises and developers run their web apps and enterprise systems on the Internet Computer, the content is decentralized across a minimum of four or a maximum of an unlimited number of nodes in Dfinity’s global network of independent data centers.
Dfinity is an open source for LinkedUp to developers for creating other types of open internet services on the architecture it has built.
“Open Social Network for Professional Profiles” suggests that on Dfinity model one can create “Open WhatsApp”, “Open eBay”, “Open Salesforce” or “Open Facebook”.
The tools include a Canister Software Developer Kit and a simple programming language called Motoko that is optimized for Dfinity’s Internet Computer.
“The Internet Computer is conceived as an alternative to the $3.8 trillion legacy IT stack, and empowers the next generation of developers to build a new breed of tamper-proof enterprise software systems and open internet services. We are democratizing software development,” Williams said. “The Bronze release of the Internet Computer provides developers and enterprises a glimpse into the infinite possibilities of building on the Internet Computer — which also reflects the strength of the Dfinity team we have built so far.”
Dfinity says its “Internet Computer Protocol” allows for a new type of software called autonomous software, which can guarantee permanent APIs that cannot be revoked. When all these open internet services (e.g. open versions of WhatsApp, Facebook, eBay, Salesforce, etc.) are combined with other open software and services it creates “mutual network effects” where everyone benefits.
On 1 November, DFINITY has released 13 new public versions of the SDK, to our second major milestone [at WEF Davos] of demoing a decentralized web app called LinkedUp on the Internet Computer. Subsequent milestones towards the public launch of the Internet Computer will involve:
2.7 WHAT IS MOTOKO?Motoko is a new software language being developed by the DFINITY Foundation, with an accompanying SDK, that is designed to help the broadest possible audience of developers create reliable and maintainable websites, enterprise systems and internet services on the Internet Computer with ease. By developing the Motoko language, the DFINITY Foundation will ensure that a language that is highly optimized for the new environment is available. However, the Internet Computer can support any number of different software frameworks, and the DFINITY Foundation is also working on SDKs that support the Rust and C languages. Eventually, it is expected there will be many different SDKs that target the Internet Computer.
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The Federal Reserve and the United States government are pumping extreme amounts of money into the economy, already totaling over $484 billion. They are doing so because it already had a goal to inflate the United States Dollar (USD) so that the market can continue to all-time highs. It has always had this goal. They do not care how much inflation goes up by now as we are going into a depression with the potential to totally crash the US economy forever. They believe the only way to save the market from going to zero or negative values is to inflate it so much that it cannot possibly crash that low. Even if the market does not dip that low, inflation serves the interest of powerful people.
The impending crash of the stock market has ramifications for Bitcoin, as, though there is no direct ongoing-correlation between the two, major movements in traditional markets will necessarily affect Bitcoin. According to the Blockchain Center’s Cryptocurrency Correlation Tool, Bitcoin is not correlated with the stock market. However, when major market movements occur, they send ripples throughout the financial ecosystem which necessary affect even ordinarily uncorrelated assets.
Therefore, Bitcoin will reach X price on X date after crashing to a price of X by X date.
Stock Market CrashThe Federal Reserve has caused some serious consternation with their release of ridiculous amounts of money in an attempt to buoy the economy. At face value, it does not seem to have any rationale or logic behind it other than keeping the economy afloat long enough for individuals to profit financially and politically. However, there is an underlying basis to what is going on which is important to understand in order to profit financially.
All markets are functionally price probing systems. They constantly undergo a price-discovery process. In a fiat system, money is an illusory and a fundamentally synthetic instrument with no intrinsic value – similar to Bitcoin. The primary difference between Bitcoin is the underlying technology which provides a slew of benefits that fiat does not. Fiat, however, has an advantage in being able to have the support of powerful nation-states which can use their might to insure the currency’s prosperity.
Traditional stock markets are composed of indices (pl. of index). Indices are non-trading market instruments which are essentially summaries of business values which comprise them. They are continuously recalculated throughout a trading day, and sometimes reflected through tradable instruments such as Exchange Traded Funds or Futures. Indices are weighted by market capitalizations of various businesses.
Price theory essentially states that when a market fails to take out a new low in a given range, it will have an objective to take out the high. When a market fails to take out a new high, it has an objective to make a new low. This is why price-time charts go up and down, as it does this on a second-by-second, minute-by-minute, day-by-day, and even century-by-century basis. Therefore, market indices will always return to some type of bull market as, once a true low is formed, the market will have a price objective to take out a new high outside of its’ given range – which is an all-time high. Instruments can only functionally fall to zero, whereas they can grow infinitely.
So, why inflate the economy so much?
Deflation is disastrous for central banks and markets as it raises the possibility of producing an overall price objective of zero or negative values. Therefore, under a fractional reserve system with a fiat currency managed by a central bank – the goal of the central bank is to depreciate the currency. The dollar is manipulated constantly with the intention of depreciating its’ value.
Central banks have a goal of continued inflated fiat values. They tend to ordinarily contain it at less than ten percent (10%) per annum in order for the psyche of the general populace to slowly adjust price increases. As such, the markets are divorced from any other logic. Economic policy is the maintenance of human egos, not catering to fundamental analysis. Gross Domestic Product (GDP) growth is well-known not to be a measure of actual growth or output. It is a measure of increase in dollars processed. Banks seek to produce raising numbers which make society feel like it is growing economically, making people optimistic. To do so, the currency is inflated, though inflation itself does not actually increase growth. When society is optimistic, it spends and engages in business – resulting in actual growth. It also encourages people to take on credit and debts, creating more fictional fiat.
Inflation is necessary for markets to continue to reach new heights, generating positive emotional responses from the populace, encouraging spending, encouraging debt intake, further inflating the currency, and increasing the sale of government bonds. The fiat system only survives by generating more imaginary money on a regular basis.
Bitcoin investors may profit from this by realizing that stock investors as a whole always stand to profit from the market so long as it is managed by a central bank and does not collapse entirely. If those elements are filled, it has an unending price objective to raise to new heights. It also allows us to realize that this response indicates that the higher-ups believe that the economy could crash in entirety, and it may be wise for investors to have multiple well-thought-out exit strategies.
Economic Analysis of BitcoinThe reason why the Fed is so aggressively inflating the economy is due to fears that it will collapse forever or never rebound. As such, coupled with a global depression, a huge demand will appear for a reserve currency which is fundamentally different than the previous system. Bitcoin, though a currency or asset, is also a market. It also undergoes a constant price-probing process. Unlike traditional markets, Bitcoin has the exact opposite goal. Bitcoin seeks to appreciate in value and not depreciate. This has a quite different affect in that Bitcoin could potentially become worthless and have a price objective of zero.
Bitcoin was created in 2008 by a now famous mysterious figure known as Satoshi Nakamoto and its’ open source code was released in 2009. It was the first decentralized cryptocurrency to utilize a novel protocol known as the blockchain. Up to one megabyte of data may be sent with each transaction. It is decentralized, anonymous, transparent, easy to set-up, and provides myriad other benefits. Bitcoin is not backed up by anything other than its’ own technology.
Bitcoin is can never be expected to collapse as a framework, even were it to become worthless. The stock market has the potential to collapse in entirety, whereas, as long as the internet exists, Bitcoin will be a functional system with a self-authenticating framework. That capacity to persist regardless of the actual price of Bitcoin and the deflationary nature of Bitcoin means that it has something which fiat does not – inherent value.
Bitcoin is based on a distributed database known as the “blockchain.” Blockchains are essentially decentralized virtual ledger books, replete with pages known as “blocks.” Each page in a ledger is composed of paragraph entries, which are the actual transactions in the block.
Blockchains store information in the form of numerical transactions, which are just numbers. We can consider these numbers digital assets, such as Bitcoin. The data in a blockchain is immutable and recorded only by consensus-based algorithms. Bitcoin is cryptographic and all transactions are direct, without intermediary, peer-to-peer.
Bitcoin does not require trust in a central bank. It requires trust on the technology behind it, which is open-source and may be evaluated by anyone at any time. Furthermore, it is impossible to manipulate as doing so would require all of the nodes in the network to be hacked at once – unlike the stock market which is manipulated by the government and “Market Makers”. Bitcoin is also private in that, though the ledge is openly distributed, it is encrypted. Bitcoin’s blockchain has one of the greatest redundancy and information disaster recovery systems ever developed.
Bitcoin has a distributed governance model in that it is controlled by its’ users. There is no need to trust a payment processor or bank, or even to pay fees to such entities. There are also no third-party fees for transaction processing. As the ledge is immutable and transparent it is never possible to change it – the data on the blockchain is permanent. The system is not easily susceptible to attacks as it is widely distributed. Furthermore, as users of Bitcoin have their private keys assigned to their transactions, they are virtually impossible to fake. No lengthy verification, reconciliation, nor clearing process exists with Bitcoin.
Bitcoin is based on a proof-of-work algorithm. Every transaction on the network has an associated mathetical “puzzle”. Computers known as miners compete to solve the complex cryptographic hash algorithm that comprises that puzzle. The solution is proof that the miner engaged in sufficient work. The puzzle is known as a nonce, a number used only once. There is only one major nonce at a time and it issues 12.5 Bitcoin. Once it is solved, the fact that the nonce has been solved is made public.
A block is mined on average of once every ten minutes. However, the blockchain checks every 2,016,000 minutes (approximately four years) if 201,600 blocks were mined. If it was faster, it increases difficulty by half, thereby deflating Bitcoin. If it was slower, it decreases, thereby inflating Bitcoin. It will continue to do this until zero Bitcoin are issued, projected at the year 2140. On the twelfth of May, 2020, the blockchain will halve the amount of Bitcoin issued when each nonce is guessed. When Bitcoin was first created, fifty were issued per block as a reward to miners. 6.25 BTC will be issued from that point on once each nonce is solved.
Unlike fiat, Bitcoin is a deflationary currency. As BTC becomes scarcer, demand for it will increase, also raising the price. In this, BTC is similar to gold. It is predictable in its’ output, unlike the USD, as it is based on a programmed supply. We can predict BTC’s deflation and inflation almost exactly, if not exactly. Only 21 million BTC will ever be produced, unless the entire network concedes to change the protocol – which is highly unlikely.
Some of the drawbacks to BTC include congestion. At peak congestion, it may take an entire day to process a Bitcoin transaction as only three to five transactions may be processed per second. Receiving priority on a payment may cost up to the equivalent of twenty dollars ($20). Bitcoin mining consumes enough energy in one day to power a single-family home for an entire week.
Trading or Investing?The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this article, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. In order to determine when the stock market will crash, causing a major decline in BTC price, we will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We are concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets and currencies ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets and instruments rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market or instrument is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The Bitcoin market is open twenty-four-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy. Bitcoin is an asset which an individual can both trade and invest, however this article will be focused on trading due to the wide volatility in BTC prices over the short-term.
Technical Indicator Analysis of BitcoinTechnical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. They are also often discounted when it comes to BTC. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
Trend Definition Analysis of BitcoinTrend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw a downtrend line on the BTC chart, but it is possible to correctly draw an uptrend – indicating that the overall trend is downwards. The only mitigating factor is the impending stock market crash.
Time Symmetry Analysis of BitcoinTime is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will measure it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
Evaluating the yearly lows, we see that BTC tends to have its lows primarily at the beginning of every year, with a possibility of it being at the end of the year. Following the same methodology, we get the middle of the month as the likeliest day. However, evaluating the monthly lows for the past year, the beginning and end of the month are more likely for lows.
Therefore, we have two primary dates from our histogram.
1/1/21, 1/15/21, and 1/29/21
2:00am, 8:00am, 12:00pm, or 10:00pm
In fact, the high for this year was February the 14th, only thirty days off from our histogram calculations.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is February 9, 2020 – a reasonably accurate depiction of the low for this year (which was on 3/12/20). (Taking only the Armstrong model into account, the next high should be Saturday, April 23, 2022). Therefore, the Armstrong model indicates that we have actually bottomed out for the year!
Bear markets cannot exist in perpetuity whereas bull markets can. Bear markets will eventually have price objectives of zero, whereas bull markets can increase to infinity. It can occur for individual market instruments, but not markets as a whole. Since bull markets are defined by low volatility, they also last longer. Once a bull market is indicated, the trader can remain in a long position until a new high is reached, then switch to shorts. The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of this bear market – roughly speaking. They cannot be shorter than fifteen months for a central-bank controlled market, which does not apply to Bitcoin. (Otherwise, it would continue until Sunday, September 12, 2021.) However, we should expect Bitcoin to experience its’ exponential growth after the stock market re-enters a bull market.
Terry Laundy’s T-Theory implemented by measuring the time of an indicator from peak to trough, then using that to define a future time window. It is similar to an head-and-shoulders pattern in that it is the process of forming the right side from a synthetic technical indicator. If the indicator is making continued lows, then time is recalculated for defining the right side of the T. The date of the market inflection point may be a price or indicator inflection date, so it is not always exactly useful. It is better to make us aware of possible market inflection points, clustered with other data. It gives us an RSI low of May, 9th 2020.
The Bradley Cycle is coupled with volatility allows start dates for campaigns or put options as insurance in portfolios for stocks. However, it is also useful for predicting market moves instead of terminal dates for discretes. Using dates which correspond to discretes, we can see how those dates correspond with changes in VIX.
Therefore, our timeline looks like:
This article is written by the CoinEx Chain lab. CoinEx Chain is the world’s first public chain exclusively designed for DEX, and will also include a Smart Chain supporting smart contracts and a Privacy Chain protecting users’ privacy.submitted by coinexchain to u/coinexchain [link] [comments]
longcpp @ 20200618
This is Part 1 of the serialized articles aimed to explain the Tendermint consensus protocol in detail.
Part 1. Preliminary of the consensus protocol: security model and PBFT protocol
Part 2. Tendermint consensus protocol illustrated: two-phase voting protocol and the locking and unlocking mechanism
Part 3. Weighted round-robin proposer selection algorithm used in Tendermint project
Any consensus agreement that is ultimately reached is the General Agreement, that is, the majority opinion. The consensus protocol on which the blockchain system operates is no exception. As a distributed system, the blockchain system aims to maintain the validity of the system. Intuitively, the validity of the blockchain system has two meanings: firstly, there is no ambiguity, and secondly, it can process requests to update its status. The former corresponds to the safety requirements of distributed systems, while the latter to the requirements of liveness. The validity of distributed systems is mainly maintained by consensus protocols, considering the multiple nodes and network communication involved in such systems may be unstable, which has brought huge challenges to the design of consensus protocols.
The semi-synchronous network model and Byzantine fault toleranceResearchers of distributed systems characterize these problems that may occur in nodes and network communications using node failure models and network models. The fail-stop failure in node failure models refers to the situation where the node itself stops running due to configuration errors or other reasons, thus unable to go on with the consensus protocol. This type of failure will not cause side effects on other parts of the distributed system except that the node itself stops running. However, for such distributed systems as the public blockchain, when designing a consensus protocol, we still need to consider the evildoing intended by nodes besides their failure. These incidents are all included in the Byzantine Failure model, which covers all unexpected situations that may occur on the node, for example, passive downtime failures and any deviation intended by the nodes from the consensus protocol. For a better explanation, downtime failures refer to nodes’ passive running halt, and the Byzantine failure to any arbitrary deviation of nodes from the consensus protocol.
Compared with the node failure model which can be roughly divided into the passive and active models, the modeling of network communication is more difficult. The network itself suffers problems of instability and communication delay. Moreover, since all network communication is ultimately completed by the node which may have a downtime failure or a Byzantine failure in itself, it is usually difficult to define whether such failure arises from the node or the network itself when a node does not receive another node's network message. Although the network communication may be affected by many factors, the researchers found that the network model can be classified by the communication delay. For example, the node may fail to send data packages due to the fail-stop failure, and as a result, the corresponding communication delay is unknown and can be any value. According to the concept of communication delay, the network communication model can be divided into the following three categories:
The design and selection of consensus protocols for public chain networks that allow nodes to dynamically join and leave need to consider possible Byzantine failures. Therefore, the consensus protocol of a public chain network is designed to guarantee the security and liveness of the network under the semi-synchronous network model on the premise of possible Byzantine failure. Researchers of distributed systems point out that to ensure the security and liveness of the system, the consensus protocol itself needs to meet three requirements:
The CAP theorem and Byzantine Generals ProblemIn a semi-synchronous network, is it possible to design a Byzantine fault-tolerant consensus protocol that satisfies validity, agreement, and termination? How many Byzantine nodes can a system tolerance? The CAP theorem and Byzantine Generals Problem provide an answer for these two questions and have thus become the basic guidelines for the design of Byzantine fault-tolerant consensus protocols.
Lamport, Shostak, and Pease abstracted the design of the consensus mechanism in the distributed system in 1982 as the Byzantine Generals Problem, which refers to such a situation as described below: several generals each lead the army to fight in the war, and their troops are stationed in different places. The generals must formulate a unified action plan for the victory. However, since the camps are far away from each other, they can only communicate with each other through the communication soldiers, or, in other words, they cannot appear on the same occasion at the same time to reach a consensus. Unfortunately, among the generals, there is a traitor or two who intend to undermine the unified actions of the loyal generals by sending the wrong information, and the communication soldiers cannot send the message to the destination by themselves. It is assumed that each communication soldier can prove the information he has brought comes from a certain general, just as in the case of a real BFT consensus protocol, each node has its public and private keys to establish an encrypted communication channel for each other to ensure that its messages will not be tampered with in the network communication, and the message receiver can also verify the sender of the message based thereon. As already mentioned, any consensus agreement ultimately reached represents the consensus of the majority. In the process of generals communicating with each other for an offensive or retreat, a general also makes decisions based on the majority opinion from the information collected by himself.
According to the research of Lamport et al, if there are 1/3 or more traitors in the node, the generals cannot reach a unified decision. For example, in the following figure, assume there are 3 generals and only 1 traitor. In the figure on the left, suppose that General C is the traitor, and A and B are loyal. If A wants to launch an attack and informs B and C of such intention, yet the traitor C sends a message to B, suggesting what he has received from A is a retreat. In this case, B can't decide as he doesn't know who the traitor is, and the information received is insufficient for him to decide. If A is a traitor, he can send different messages to B and C. Then C faithfully reports to B the information he received. At this moment as B receives conflicting information, he cannot make any decisions. In both cases, even if B had received consistent information, it would be impossible for him to spot the traitor between A and C. Therefore, it is obvious that in both situations shown in the figure below, the honest General B cannot make a choice.
According to this conclusion, when there are $n$ generals with at most $f$ traitors (n≤3f), the generals cannot reach a consensus if $n \leq 3f$; and with $n > 3f$, a consensus can be reached. This conclusion also suggests that when the number of Byzantine failures $f$ exceeds 1/3 of the total number of nodes $n$ in the system $f \ge n/3$ , no consensus will be reached on any consensus protocol among all honest nodes. Only when $f < n/3$, such condition is likely to happen, without loss of generality, and for the subsequent discussion on the consensus protocol, $ n \ge 3f + 1$ by default.
The conclusion reached by Lamport et al. on the Byzantine Generals Problem draws a line between the possible and the impossible in the design of the Byzantine fault tolerance consensus protocol. Within the possible range, how will the consensus protocol be designed? Can both the security and liveness of distributed systems be fully guaranteed? Brewer provided the answer in his CAP theorem in 2000. It indicated that a distributed system requires the following three basic attributes, but any distributed system can only meet two of the three at the same time.
A distributed system aims to provide consistent services. Therefore, the consistency attribute requires that the two nodes in the system cannot provide conflicting status information or expired information, which can ensure the security of the distributed system. The availability attribute is to ensure that the system can continuously update its status and guarantee the availability of distributed systems. The partition tolerance attribute is related to the network communication delay, and, under the semi-synchronous network model, it can be the status before GST when the network is in an asynchronous status with an unknown delay in the network communication. In this condition, communicating nodes may not receive information from each other, and the network is thus considered to be in a partitioned status. Partition tolerance requires the distributed system to function normally even in network partitions.
The proof of the CAP theorem can be demonstrated with the following diagram. The curve represents the network partition, and each network has four nodes, distinguished by the numbers 1, 2, 3, and 4. The distributed system stores color information, and all the status information stored by all nodes is blue at first.
The discovery of the CAP theorem seems to declare that the aforementioned goals of the consensus protocol is impossible. However, if you’re careful enough, you may find from the above that those are all extreme cases, such as network partitions that cause the failure of information transmission, which could be rare, especially in P2P network. In the second case, the system rarely returns the same information with node 2, and the general practice is to query other nodes and return the latest status as believed after a while, regardless of whether it has received the request information of other nodes. Therefore, although the CAP theorem points out that any distributed system cannot satisfy the three attributes at the same time, it is not a binary choice, as the designer of the consensus protocol can weigh up all the three attributes according to the needs of the distributed system. However, as the communication delay is always involved in the distributed system, one always needs to choose between availability and consistency while ensuring a certain degree of partition tolerance. Specifically, in the second case, it is about the value that node 2 returns: a probably outdated value or no value. Returning the possibly outdated value may violate consistency but guarantees availability; yet returning no value deprives the system of availability but guarantees its consistency. Tendermint consensus protocol to be introduced is consistent in this trade-off. In other words, it will lose availability in some cases.
The genius of Satoshi Nakamoto is that with constraints of the CAP theorem, he managed to reach a reliable Byzantine consensus in a distributed network by combining PoW mechanism, Satoshi Nakamoto consensus, and economic incentives with appropriate parameter configuration. Whether Bitcoin's mechanism design solves the Byzantine Generals Problem has remained a dispute among academicians. Garay, Kiayias, and Leonardos analyzed the link between Bitcoin mechanism design and the Byzantine consensus in detail in their paper The Bitcoin Backbone Protocol: Analysis and Applications. In simple terms, the Satoshi Consensus is a probabilistic Byzantine fault-tolerant consensus protocol that depends on such conditions as the network communication environment and the proportion of malicious nodes' hashrate. When the proportion of malicious nodes’ hashrate does not exceed 1/2 in a good network communication environment, the Satoshi Consensus can reliably solve the Byzantine consensus problem in a distributed environment. However, when the environment turns bad, even with the proportion within 1/2, the Satoshi Consensus may still fail to reach a reliable conclusion on the Byzantine consensus problem. It is worth noting that the quality of the network environment is relative to Bitcoin's block interval. The 10-minute block generation interval of the Bitcoin can ensure that the system is in a good network communication environment in most cases, given the fact that the broadcast time of a block in the distributed network is usually just several seconds. In addition, economic incentives can motivate most nodes to actively comply with the agreement. It is thus considered that with the current Bitcoin network parameter configuration and mechanism design, the Bitcoin mechanism design has reliably solved the Byzantine Consensus problem in the current network environment.
Practical Byzantine Fault Tolerance, PBFTIt is not an easy task to design the Byzantine fault-tolerant consensus protocol in a semi-synchronous network. The first practically usable Byzantine fault-tolerant consensus protocol is the Practical Byzantine Fault Tolerance (PBFT) designed by Castro and Liskov in 1999, the first of its kind with polynomial complexity. For a distributed system with $n$ nodes, the communication complexity is $O(n2$.) Castro and Liskov showed in the paper that by transforming centralized file system into a distributed one using the PBFT protocol, the overwall performance was only slowed down by 3%. In this section we will briefly introduce the PBFT protocol, paving the way for further detailed explanations of the Tendermint protocol and the improvements of the Tendermint protocol.
The PBFT protocol that includes $n=3f+1$ nodes can tolerate up to $f$ Byzantine nodes. In the original paper of PBFT, full connection is required among all the $n$ nodes, that is, any two of the n nodes must be connected. All the nodes of the network jointly maintain the system status through network communication. In the Bitcoin network, a node can participate in or exit the consensus process through hashrate mining at any time, which is managed by the administrator, and the PFBT protocol needs to determine all the participating nodes before the protocol starts. All nodes in the PBFT protocol are divided into two categories, master nodes, and slave nodes. There is only one master node at any time, and all nodes take turns to be the master node. All nodes run in a rotation process called View, in each of which the master node will be reelected. The master node selection algorithm in PBFT is very simple: all nodes become the master node in turn by the index number. In each view, all nodes try to reach a consensus on the system status. It is worth mentioning that in the PBFT protocol, each node has its own digital signature key pair. All sent messages (including request messages from the client) need to be signed to ensure the integrity of the message in the network and the traceability of the message itself. (You can determine who sent a message based on the digital signature).
The following figure shows the basic flow of the PBFT consensus protocol. Assume that the current view’s master node is node 0. Client C initiates a request to the master node 0. After the master node receives the request, it broadcasts the request to all slave nodes that process the request of client C and return the result to the client. After the client receives f+1 identical results from different nodes (based on the signature value), the result can be taken as the final result of the entire operation. Since the system can have at most f Byzantine nodes, at least one of the f+1 results received by the client comes from an honest node, and the security of the consensus protocol guarantees that all honest nodes will reach consensus on the same status. So, the feedback from 1 honest node is enough to confirm that the corresponding request has been processed by the system.
For the status synchronization of all honest nodes, the PBFT protocol has two constraints on each node: on one hand, all nodes must start from the same status, and on the other, the status transition of all nodes must be definite, that is, given the same status and request, the results after the operation must be the same. Under these two constraints, as long as the entire system agrees on the processing order of all transactions, the status of all honest nodes will be consistent. This is also the main purpose of the PBFT protocol: to reach a consensus on the order of transactions between all nodes, thereby ensuring the security of the entire distributed system. In terms of availability, the PBFT consensus protocol relies on a timeout mechanism to find anomalies in the consensus process and start the View Change protocol in time to try to reach a consensus again.
The figure above shows a simplified workflow of the PBFT protocol. Where C is the client, 0, 1, 2, and 3 represent 4 nodes respectively. Specifically, 0 is the master node of the current view, 1, 2, 3 are slave nodes, and node 3 is faulty. Under normal circumstances, the PBFT consensus protocol reaches consensus on the order of transactions between nodes through a three-phase protocol. These three phases are respectively: Pre-Prepare, Prepare, and Commit:
In the three-phase protocol execution of the PBFT protocol, in addition to maintaining the status information of the distributed system, the node itself also needs to log all kinds of consensus information it receives. The gradual accumulation of logs will consume considerable system resources. Therefore, the PBFT protocol additionally defines checkpoints to help the node deal with garbage collection. You can set a checkpoint every 100 or 1000 sequence numbers according to the request sequence number. After the client request at the checkpoint is executed, the node broadcasts
The three-phase protocol of the PBFT protocol can ensure the consistency of the processing order of the client request, and the checkpoint mechanism is set to help nodes perform garbage collection and further ensures the status consistency of the distributed system, both of which can guarantee the security of the distributed system aforementioned. How is the availability of the distributed system guaranteed? In the semi-synchronous network model, a timeout mechanism is usually introduced, which is related to delays in the network environment. It is assumed that the network delay has a known upper bound after GST. In such condition, an initial value is usually set according to the network condition of the system deployed. In case of a timeout event, besides the corresponding processing flow triggered, additional mechanisms will be activated to readjust the waiting time. For example, an algorithm like TCP's exponential back off can be adopted to adjust the waiting time after a timeout event.
To ensure the availability of the system in the PBFT protocol, a timeout mechanism is also introduced. In addition, due to the potential the Byzantine failure in the master node itself, the PBFT protocol also needs to ensure the security and availability of the system in this case. When the Byzantine failure occurs in the master node, for example, when the slave node does not receive the PRE-PREPARE message or the PRE-PREPARE message sent by the master node from the master node within the time window and is thus determined to be illegitimate, the slave node can broadcast
VIEWCHANGE contains a lot of information. For example, C contains 2f+1 signature information, P contains several signature sets, and each set has 2f+1 signature. At least 2f+1 nodes need to send a VIEWCHANGE message before prompting the system to enter the next new view, and that means, in addition to the complex logic of constructing the information of VIEWCHANGE and NEW-VIEW, the communication complexity of the view conversion protocol is $O(n2$.) Such complexity also limits the PBFT protocol to support only a few nodes, and when there are 100 nodes, it is usually too complex to practically deploy PBFT. It is worth noting that in some materials the communication complexity of the PBFT protocol is inappropriately attributed to the full connection between n nodes. By changing the fully connected network topology to the P2P network topology based on distributed hash tables commonly used in blockchain projects, high communication complexity caused by full connection can be conveniently solved, yet still, it is difficult to improve the communication complexity during the view conversion process. In recent years, researchers have proposed to reduce the amount of communication in this step by adopting aggregate signature scheme. With this technology, 2f+1 signature information can be compressed into one, thereby reducing the communication volume during view change.
There is extreme volatility and deviation in the DXY itself compared to dominance, after tracing along perfectly for years. Altcoins perform well during dollar weakness, even more so than Bitcoin according to what the correlation suggests. If this is true and more stimulus is on the way. A very powerful altcoin season could be right around the ... Mining Bitcoin on Mars would be unprofitable because of the propagation delay, assuming Earth maintains hash power dominance. The Martian miners would have a view of the blockchain up to 22 minutes out of date, so by the time their latest mined block reaches the majority of hash power on Earth, on average there would be four new blocks added to the chain. — Clark Moody, Bitcoin and the ... Bitcoin Mining Hardware Comparison Currently, based on (1) price per hash and (2) electrical efficiency the best Bitcoin miner options are: AntMiner S7 4.73 Th/s 0.25 W/Gh 8.8 pounds Yes N/A 0.1645 AntMiner S9 13.5 Th/s 0.098 W/Gh 8.1 pounds Yes N/A 0.3603 Avalon6 3.5 Th/s 0.29 W/Gh 9.5 pounds No N/A 0.1232 Bitmain Tech introduces, second newest version of its Antminer series of Bitcoin miners ... Best Bitcoin Mining Software Reviewed. By: Ofir Beigel Last updated: 8/23/20 If you’re thinking of getting into Bitcoin mining, one of the things you’re going to need is a software to run your mining hardware.In this post I’ll review the top Bitcoin mining software available on the market. Block weight is defined as Base size * 3 + Total size. (rationale) ... Any commitments that are not consensus-critical to Bitcoin, such as merge-mining, MUST NOT use the witness reserved value to preserve the ability to do upgrades of the Bitcoin consensus protocol. The optional data space following the commitment also leaves room for metadata of future softforks, and MUST NOT be used for ...
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