Proof-of-stake (POS) outperforms Bitcoin ' s proof-of-work (POW) __pos

Proof-of-stake (POS) models are becoming highly desirable in blockchain consensus designs, especially with the "Casper" Upgrade underway for Ethereum, the second largest cryptocurrency by market cap. Yes, the immediate reason is that it's more energy efficient (reduces computational costs) as opposed to Proof-of-work (P OW) which is highly resource intensive, but there ' s more.

POS, in general, takes individual Digital Signature to prove ownership of the stake selected by the network, based on T Heir proportional stake, in order to validate messages and transactions to the database. If We look deeper, there are 2 main models which come under this category:chain based; which offers ' availability ' as a validator is selected at random during a set time slot to create a block, which points to A previous blocks so, the blocks converge into one growing chain. This type is favoured to a more "permisionless" approach. Notable blockchain projects that implemented this model are NXT, PeerCoin, ardor. Consortium consensus-byzantine Fault Tolerance (BFT) Protocol:which offers ' consistency ' as the validators randomly En for each round the "end" agreeing on whether or not the "block becomes part" of the chain. This type could is favoured for a more "permissioned" approach. Used by Neo, Tendermint, Polkadot, Hyperledge Fabric.

Last week, the BFT consensus algorithm is a heated topic in the industry as the NEO blockchain came to a halt in the face of a disconnected node in the network, leaving other nodes waiting for a reply. The issue is solved with a "forced changeview", i.e restarting all the nodes, posing a question of centralisation, as POW Er is still with NEO. This issue has subsequently caused increased blocks generation time in the network, where transactions are long Er, due to node synchronization issues. This is problem has been interesting to watch, and a valuable learning the for all other curve projects the testing of variations s consensus model. The idea of the ' design ' to have numerous nodes (lets say a hundred) in the network, so as to keep the "decentralised" no tion and not have a single point of the failure in order to ensure a problem as this does is not occur. NEO, only has around "bookkeeping nodes" have more of the "centralised" design. This fact was totally expected as NEO is a ChiNese Blockchain economy, endorsed by the Chinese govenrment, and so it itself total makes. This is arguably the very most reason it are appealing to so many companies.So what is BFT?

BFT is-a popular protocol in distributed computing and has been studied since the 1978 (when it was a-I-introduced by Leslie Lamport). It has got over the protocols to date, as as as the open source implementations. This has been a very popular model used to consensus in the big ' centralised ' companies like Google, yet it's now also a pop Ular choice in blockchain projects as it aims to solve the scalability issue. Popular projects using BFT protocols include Hyperledger Fabric, Tendermint, Polkadot, NEO, amongst others.

When it comes to consensus, the key was how to guarantee fault tolerance when it comes to non-honest and defective on The network, as attacks and software error are common, causing nodes to display arbitrary behaviour (Byzantine faults), b Est described as the analogy of the general ' s Problem '. The "Practical Byzantine Fault Tolerance" (PBFT), algorithm introduced by Miguel Castro and Barbra Liskov, provides Formance Byzantine state machine replication, processing thousands of requests-per second and submillisecond in Latency. This is offers advantages like "consistency", mentioned above, as the there should is agreement by the validator nodes A is generated. Another Advantage is this it ensures settlement ' finality ', speeds up settlement time to under 1 second from the current T Ens of seconds to tens of minutes, and at the same time reduces energy consumption dramatically. A BFT Style consensus model is best suited for consortium blockchains that most FInancial institutions are favouring.

With decentralisation, comes a performance tradeoff as seen with Bitcoin. BFT offers a efficient consensus protocol, achieving better latency and throughput with less, computation, and storage. Specifically, using a standard BFT protocol with a small number of pre-designated trusted entities/nodes. "Even with dozens of nodes, pbft greatly outperforms Bitcoin in both transaction latency and throughput. For example, nodes processing batches of 8192 transactions can achieve a throughput of 4.5K tx/sec., average Transactio N Latency of 1.79 sec., and a estimated resource cost per transaction of just $3.95x10–7 "(1). This model involves a designated the set of homogenous validator nodes that tolerate f-out-of-n faulty. In this model, the transactions are sent to consensus nodes for validation. The nodes validate the transaction and decide, then spread the results. The "Data is deleted" from the "nodes" validation round, so as not to clog the system. This ProtocolCan is customised to have a "controlled membership" model, where there can often be a, a and a, a, a P (beneficial in the case of Financial institutions/governments and some Private companies). It can also have a more "dynamic membership" which varies in the protocol itself, where membership is decided.BFT & Blockchain

BFT protocols generally assume a synchronous or weakly synchronous nature, i.e they-rely on A-priori nodes and network Tim ing assumptions and only ensure liveness the network behaves as expected. Therefore, in the case of decentralised blockchain implementations, there are an argument so these protocols come with FA Ults and rather should demonstrate more of the asynchronous nature in order to guarantee liveness without relying on Node A ND timing assumptions. This is argued to significantly increase transaction throughput for scalability. The image below shows how different types of BFT protocols were able to achieve scalability and to what extent, showing th At Parallel BFT achieved a high performance, getting closer to 100,000 tx/s. Scalability/performance Tradeoff (m. vukolic:the Quest for scalable blockchain vs. Fabric:proof-of-work BFT )

Parallel Consensus

Parellel BFT works through processing requests to parallel, through appointing multi-leaders, rather than a single leader In a basic BFT protocol. This is allows for achieving high throughput and scalability. "Sarek" is a parallel ordering framework that partitions the service state to exploit parallelism during both agreement D execution. A Sarek implementation for blockchain would is interesting. Instead of one leader at a time for the entire system, it uses one leader each partition and only establishes a Ord ER on requests accessing the same partition. Sarek also supports operations that span multiple partitions and provides a deterministic mechanism to atomically process them. This ensures is increase in throughput performance by a factor of 2, at half the latency compared to a singleleader Entation, according to Sarek (2). Through Sarek, concurrent rounds of consensus can be run.

Asynchronous BFT

In a asynchronous setting, messages are delivered to different nodes no under timing. These settings are argued to is impractical as they limit throughput in a network. Attempts to solve this issue have been through attempting to solve redundant the work through introducing ' fairness ' (3) i.e. Censorship resilience, which still allows for targeted censorship. However new studies by A. Miller et al, (4) indicate that through the use of Threshold Public-key, encryption Risks can be prevented.

Asynchronous BFT is specifically suited for blockchain implementations as in this field, bandwidth are a scarce resource an D computation is ample, meaning that cryptographic elements like Threshold Public-key encryption can be used, which otherw Ise are expensive (in classical Fault-tolerance database settings) and therefore attacks. In the, rather than aiming for minimizing response time, even under disagreement (in standard BFT settings), message s are eventually delivered, while no timing assumption is made. Regardless of how network conditions fluctuate, throughput always the tracks network ' s available. With experimentation-setting has demonstrated better throughput than PBFT protocols and has proved security and live Ness (4). The Solution involves the process of ' batching ' i.e creating a multi-party pool of nodes, to provide better and Reduce cost, whilst using threshold encryption to preserve censorship resilience.Conclusion

When it comes to comparing POS models with the blockchain consensus model, Bitcoin ' s proof-of-work (POW), based on A Dam back ' s Hashcah POW function (1997), it are worth firstly remembering that there are so many POS variations including th OSE of a BFT style, so it won ' t being a like to like comparison, and a general comparison won ' t suffice.

One of the most common arguments against POS is the issue of "stake grinding", i.e turn-manipulation (for creating the Blo CK and winning the reward). This can is solved through using a Threshold Signature Scheme that generates the key value for the next block creator. Also there is the ' nothing-at-stake ' problem that happens then dis-honest or arbitrary nodes create blocks on multiple cha Ins, which can be solved with penalty measures, like loosing deposits.

Perhaps, the main question could are which model is best for future-proofing a chain, for scalability? In this case, a POS, BFT based model requires the least storage spaces, as less work, i.e (signatures) are needed, due to s Trong finality guarantees as the nodes involved in reaching consensus-have to come to a agreement before actually Generat ing the block. This means is transactions won ' t put as much load on the blockchain. In addition, what is mentioned above about a basic BFT protocol outperforming Bitcoin in both transaction and Latency, not to mention resource costs. Let's end with a comparison of resource costs of a transaction through a PBFT protocol ($39.4) and through POW Bitcoin min ING (a average of $5,000 in the US, can reach up to $26,000 in South Korea). 1. Croman, Kyle et al, "on scaling decentralized blockchains-(A Position Paper)", Financial cryptography-workshops (2016 ). 2. Li, Bijun et al, "Sarek:optimistic Parallel ordering in Byzantine Fault TolerAnce ", 2016 12th European Dependable Computing Conference (EDCC) (2016). 3. Koblitz, Neal et al, "The state of elliptic Curve cryptography", Des. Codes Cryptography 19 (2000). 4. Miller, Andrew et al. "The Honey Badger of BFT protocols." IACR cryptology eprint Archive (2016).

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