#i have like over a hundred graphs on my computer for different comparisons

[agerefandom]

Top 10: Tumblr vs. AO3

Just felt like doing some statistics with my work!! Comparing AO3 popular fics vs. tumblr popular fics and seeing what I found out: thought other people might be interested as well! Ramblings about patterns and causes are under the ‘read more’ :P 

AO3 (by kudos): 

Class Outing: BNHA, regressor!Izuku (1247 kudos) 

Only Heaven I’ll Be Sent To: Resident Evil, regressor!reader, caregiver!Lady Dimitrescu (759 kudos) 

Cold Palms, Warm Heart: Twilight, regressor!reader, caregivers!Alice and Jasper (573 kudos) 

The Doctor’s Office: Twilight, regressor!reader, caregiver!Carlisle (403 kudos) 

Kitchen Friends: Marvel, regressor!reader, caregiver!Steve and Bucky (336 kudos) 

Sound and Silence: BNHA, regressor!Aizawa, cg!Hizashi (321 kudos)

Restrained: Death Note, regressor!Light, caregiver!L (309 kudos)

A Story For Sans: regressor!Sans, caregiver!Papyrus (278 kudos) 

Home Sweet Home: caregivers!Carlisle and Esme, regressor!Cullens (273 kudos) 

To Weather The Storm: caregiver!Tamaki, regressor!Haruhi (238 kudos) 

Tumblr (fics only): 

Class Outing (167 notes) 

Cold Palms, Warm Heart (159 notes)

The Playtime Solution: Sanders Sides, regressor!Logan (159 notes)

The Doctor’s Office (150 notes) 

Sugary Sweet: Twilight, regressor!reader, cg!Jasper and Alice (150 notes) 

Kitchen Friends (125 notes) 

Only Heaven I’ll Be Sent To (116 notes)

What Family Is: Harry Potter, regressor!reader, cg!Remus and Sirius (116 notes) 

Just Plane Overwhelmed: Sanders Sides, regressor!Virgil (111 notes) 

Golden Slumbers: Harry Potter, regressor!reader and Harry, cg!Fred (110 notes) 

Overall Tumblr Top 10:

Caregiver Valerie Frizzle headcanons & moodboard (409 notes)

Writing Prompts 2019 / 2022 (290/365 notes)

Caregivers Tiana and Naveen headcanons (244 notes)

Caregiver Jack Skellington moodboard (229 notes)

Caregiver Morticia Addams moodboard (224 notes)

Regressor Wybie Moodboard (205 notes)

Caregiver Bruno Madrigal headcanons (201 notes)

Caregiver Jack Skellington headcanons (191 notes)

Caregivers Sundrop and Moondrop headcanons (189 notes)

Caregiver Belle headcanons (182 notes)

This was really interesting!! 

Re: overall tumblr top 10: I think it’s funny that my throwaway moodboards are often some of the most popular content on my blog. Things I’m just like ‘ooh I gotta make this’ are mixed in with requests, I think that’s interesting! Ms. Frizzle just blowing away the competition, that’s amazing and I love it. Nothing is even close to how popular she is, and she deserves it. Jack Skellington coming onto the list twice? Come through king, I would love to write a full fic in Halloweentown sometime. 

Generally, the more ‘alternative’ characters seem to get a lot more attention on my blog: The Pumpkin King, Morticia, Wybie, Sundrop and Moondrop... Tiana and Naveen really snuck up there though! 

Moving onto the more direct fic comparison: 

....well this made me realize that I never published my Sanders Sides fics from this blog on AO3, whoops 

Setting that aside, fics with angst and plot tend to do better on AO3, while fluffy stories do better on tumblr: Sugary Sweet doesn’t even hit my top 10 on AO3 and it’s one of the fluffiest fics I’ve ever written, coming in at #5 on the tumblr list 

On the other hand, Only Heaven I’ll Be Sent To is by far one of my best performing fics on AO3, but comes in at number 6 (tied with another fic) on tumblr, probably because it features a lot of action and gore alongside the fluffy agere elements, same for Restrained showing up on the AO3 top but not tumblr’s. 

My Harry Potter fics do way better on tumblr, which is interesting? Maybe Harry Potter fans are still reading their fics on independent forums? Or Harry Potter folks on AO3 don’t cross over much with the agere crowd. (Or maybe they’re just overloaded with /reader fics) I haven’t been actually into the HP community since around 2011 so I’m not sure what’s up there. 

Big shoutout to Class Outing for dominating the top of both lists: BNHA is such a big fandom that it makes sense, and I wrote that fic on @agere-fandom-time, which I think got more interaction than this blog: it seems like people are more comfortable interacting with a group-run blog, rather than an individual writer. Or maybe that’s a natural consequence of more writers putting out more consistent content, letting the blog get bigger. I’m not sure! Either way, even if I’m not into BNHA anymore, I feel like it’s a good piece of my writing, so I’m happy for it to be my top spot. 

[scienceblogtumbler]

Graphs to Help plan Deconfinement

The computer scientist Claire Mathieu explains how graph theory can help model the propagation of Covid-19, and assess the relevance of several confinement scenarios.

You are proposing to use tools from graph theory to study the propagation of Covid-19. How did this project come to life, and what are its objectives? Claire Mathieu: the CNRS management encouraged all staff members to make research proposals that could prove useful in the struggle against the virus. While discussing with my colleagues Laurent Viennot and Vincent Cohen-Addad last week, it occurred to us that our research on graphs could be of interest in studying the propagation of the disease in small communities, thereby shedding light on the implementation of deconfinement strategies.

What are graphs, and how are they connected to the propagation of epidemics? C. M.: A graph is a network of points called nodes, which are connected by links. In the case of an epidemic, each node represents an individual at a particular stage of infection (healthy, infected, or recovered), and each link between two nodes illustrates a social interaction between two individuals. Taken together this provides a map of sorts for all social contacts within a group.

Graph recapping all of the contacts (lines) between teachers and students (coloured nodes) from different classes during the course of a day (the larger the dot, the more that person had contacts).

For example, the graph of social interactions in my neighbourhood during this period of confinement will show that I am connected to very few people, essentially my family and the sales assistants where I shop, while my baker’s activity means they are linked to a very large number of locals. We can then use this network to provide a probability for virus transmission during an interaction between two people in the network, which helps understand how the infection spreads within the population.

Using similar models, computer science researchers in the past have studied how best to disseminate information within a group. This in short revealed the importance of highly connected individuals, as well as those belonging to multiple communities at the same time. These people should be given preference in spreading information, and conversely should be the ones that are isolated first and foremost in order to contain an epidemic.

What does this type of model offer in comparison to those already used by epidemiologists? C. M.: In general, the modelling of complex phenomena requires different simulations that are well-adapted to the various spatio-temporal scales under consideration. For instance, in the case of climate patterns, while the physics equations that describe a phenomenon on a very small level can be solved numerically, statistical representations are necessary for large scales, and yet other models are needed for intermediate ones. For the propagation of an epidemic, our proposal can be applied to the finest level of granularity, which is to say small communities and all of the links within them.

What precisely will this involve? C. M.: As part of the “Soci-patterns” project, our physicist colleagues have released data collected in a primary school in 2011, which contains all of the interactions between students and teachers over the course of two days: who met whom, when, where, and for how long. The resulting dynamic graph includes approximately 250 nodes and hundreds of thousands of links. Its propagation properties can be analysed in order to explore different strategies for reopening schools.

Should they be opened part time? Should students be separated into different groups? If so, what would be the optimal size? Should children eat lunch in the classroom? Is it preferable for secondary school teachers to rotate from class to class, instead of their students? Rigorous quantitative analysis can help answer these questions.

We then plan to theoretically model interaction networks that are representative of various situations, which we can subsequently use to conduct similar analyses. It would be interesting to model the typical links within a family, school, or company, and to connect the corresponding graphs in order to understand the specific “pathways” travelled by the epidemic. This could shed light on the deconfinement scenarios being studied on the scale of a city or neighbourhood, by concretely indicating the most relevant links to keep inactive.

Representation of the movement of different classes in the school: each coloured line corresponds to a particular class, with its width being proportional to the number of students involved.

Source :https://ift.tt/2W16P8L

The French President announced that schools would reopen on 11 May. What is your opinion thereon at this stage of your research? C. M.: It’s far too early for us to assert anything at all! We have to keep in mind that under normal circumstances, research requires at least six months before we can potentially draw our initial conclusions. In this case, we issued a proposal only ten days ago, and began work last week. That being said, researchers could play an advisory role with university vice-chancellors and school head teachers to prepare for 11 May, or for after the summer.

For that matter, suppose that in the next few weeks we find ourselves in a situation similar to the first epidemiological stage (except for those who have acquired immunity). It would then be necessary to isolate new individuals who are infected, and test their contacts in order to quarantine them where necessary, even before they themselves become contagious. Our approach could help determine priorities in this process. Indeed, while some links should obviously be severed, other more subtle ones could only be revealed through rigorous mathematical analysis.

Could your research results serve as input data to ‘feed’ epidemiological models on a larger scale, thereby making their predictions more accurate? C. M.: Once again it is too early to answer, but it is a relevant question. More generally, I would like to emphasise that during this current period of uncertainty, all questions or remarks, regardless of where they come from, can contribute to reflection. With regard to schools, graphs will perhaps provide answers, but it will also be very interesting to consult head teachers, teachers, and parents. For example, let’s assume that our models suggest that from a strictly epidemiological point of view, it is preferable to separate good friends, in order to eliminate the links with the highest probability of transmitting the virus. Is this truly desirable from a school’s organisation perspective? It is not up to me to answer, but what I do know is that within a network formed by society – all the more so when it comes to complex questions that require swift answers – the circulation of information and experiences that can feed the debate should involve actors from as wide a variety of backgrounds as possible!

source https://scienceblog.com/516075/graphs-to-help-plan-deconfinement/

[legit-scam-review]

Can Crypto Record a 1,000x Return and Reach $200 Trillion Market Cap?

Last week, statements from Binance CEO Changpeng Zhao (aka CZ) and Ethereum co-creator Vitalik Buterin led the community to speculate on the possibility of the crypto market achieving a 1,000 return in value in the long-term.

On Sept. 8, Buterin stated with the awareness of cryptocurrencies by the general public and mainstream reaching a peak in late 2017, it is unrealistic for the valuation of the crypto market to increase by a thousand fold from its current value at $200 billion.

A thousand fold increase from $200 billion is $200 trillion, which is 70 percent of global wealth that includes gold, reserve currencies, and other traditional assets that are utilized as wealth management products.

“The blockchain space is getting to the point where there’s a ceiling in sight. If you talk to the average educated person at this point, they probably have heard of blockchain at least once. There isn’t an opportunity for yet another 1,000-times growth in anything in the space anymore.”

Misreporting about Buterin’s initial statement

Given the context and Buterin’s statement on the growth of awareness of crypto, the claim of the Ethereum co-creator was quite straightforward. While it is possible that decentralized systems and applications (DApps) achieve a thousandfold growth in activity and user base, it is not realistic to expect the valuation of cryptocurrencies to surpass $200 trillion anytime soon.

However, sensationalized headlines and out-of-context social media posts misled many members of the cryptocurrency community to misunderstand Buterin’s statement as a pessimistic take on the rate of growth of the cryptocurrency sector.

As an increasing number of people began to question Buterin’s motive in his rather simple statement, he released a follow-up explanation on social media, reaffirming that, although he struggles to see the valuation of the crypto market achieving $200 trillion, exponential growth in the usage of DApps and blockchain protocols is possible.

“To be clear, I never said that there is ‘no room for growth’ in the crypto ecosystem. I said there is no room for 1000x price increases. A 1000x price increase from today means $200 trillion in crypto, or an entire 70 percent of today’s global wealth being in crypto. What I actually said is that, because large portions of the population have already heard of crypto, further growth of crypto in any sense must come from depth (i.e., actual usage) and not bringing in more attention.”

The viewpoint of Buterin toward the long-term growth of the cryptocurrency market is sensible, as it would undoubtedly be difficult for cryptocurrencies to represent the vast majority of the world’s wealth. It would require banks operating the $30 trillion offshore banking industry and investors holding wealth in traditional stores of value such as gold to switch to cryptocurrencies as the primary store of value.

Instead of expecting an unrealistic return, Buterin noted that it is important to focus on the growth of DApps and protocols to speed up the process of increasing the usage of blockchain-based systems and cryptocurrencies.

Currently, most individuals — in both developed cryptocurrency markets, like the U.S. and Japan, and restricted markets, like India and China — are already aware of cryptocurrencies and blockchain protocols. The next phase in blockchain technology might require a shift in the trend from centralized platforms to decentralized alternatives, which could be difficult given the discrepancy in efficiency between centralized and decentralized services.

CZ believes 1,000x increase is possible

Changpeng Zhao, the CEO of the world’s largest cryptocurrency exchange, Binance, better known to the community as CZ, stated that a thousandfold return from the current valuation of the market is “absolutely” possible, offering an extremely optimistic prediction on the future price trend of the market.

CZ stated that $200 trillion could seem unrealistically large if compared to the traditional finance market. But, similar to comparing the taxi industry to the market size of Uber, CZ explained that it is not accurate to measure the potential of the crypto market based on the size of the traditional finance market.

“I still disagree with this. I will say ‘crypto will absolutely grow 1000x and more!’ Just reaching USD market cap will give it close to 1000x, (that’s just one currency with severely restricted use case), and the derivatives market is so much bigger.

“You also can’t use traditional market size to measure potential for new technologies or industries. If you used (and people have) taxi market size to estimate Uber’s potential, you would be off by quite a bit.”

There is merit in CZ’s argument that the potential of cryptocurrencies cannot be measured based on the market size of the traditional finance market. But, over the past year, the biggest companies in crypto, such as Coinbase, Gemini and BitGo, have been working to establish custody solutions to bring in institutional investors into the space, while investors have been highly anticipating the debut of exchange-traded funds (ETFs) and all sorts of publicly tradable instruments around crypto.

Hence, with the majority of investors in the crypto market anticipating an influx of investors from the traditional finance sector, to some extent, investors have to explore the finance market to measure the potential market size of crypto.

Moreover, as ShapeShift CEO Erik Voorhees said, global finance is becoming further integrated with crypto finance, and as the cryptocurrency sector continues to create bridges connecting the two markets, both markets will continue to intertwine and affect one another, positive or negatively.

As CZ stated, it is also important to acknowledge that money is one application of blockchain technology that is best demonstrated by Bitcoin. Venture capital firms and prominent investors like Ben Horowitz generally consider blockchain technology and smart contract blockchain protocols like Ethereum as new global computing systems.

Bitcoin, Ether and other major cryptocurrencies that have started to be adopted as stores of value have alternative use cases. Ether operates as gas that fuels the Ethereum smart contract blockchain protocol, which — with sufficient scaling through the implementation of sharding and Plasma — could compete against centralized web servers and computing platforms in the long term.

The ability of blockchain technology to operate as a computing system on top of a form of money could add more value and, as CZ said, in the sense that blockchain technology is not limited to money, it can be argued that the comparison between crypto and the finance sector represents only one aspect of the market.

Earliest Coinbase investor sees explosive growth for crypto

Garry Tan, a prominent venture capitalist and the earliest investor in Coinbase and Instacart, who has funded more than 100 startups worth $20 billion, said that it is possible for the crypto market to reach hundreds of trillions of dollars in market valuation.

While a thousandfold return is difficult to imagine, Tan stated that the possibility of explosive growth in the cryptocurrency sector cannot be ruled out. He emphasized that the crypto market will not undergo the trend most speculators in the industry expect. Tan told Cointelegraph:

“My general sense is that it is possible but unlikely to be 1000x. Even if it did get there, you would be assuming securitization using security tokens, which isn’t exactly what speculators have in mind when they are hoping for more 1000x situations. They are generally thinking that their worthless altcoins will somehow be worth 1000x and security tokens will merely represent ownership in real assets. It’s a strange nuance but one worth mentioning.”

Still, after nine years, Tan stated that the cryptocurrency market is mostly dominated by retail investors and individual traders. A significant amount of capital is controlled by institutions and the entrance of institutional investors — like pensions, endowments and sovereign wealth funds — could very well lead to an explosive increase in the valuation of crypto.

For institutional investors to commit to an asset, say Bitcoin, a specific type of infrastructure is required to facilitate the transfer of funds. Custody solutions in the crypto market have not existed for more than two months, with the first trusted custodian solution released by Coinbase in July.

Hence, it could take months to years for institutional investors to commit to the crypto market. But, echoing the viewpoint of billionaire investor Mike Novogratz, Tan stated that once institutions find their way into crypto, the market will see a difference in terms of volume and value, as Novogratz previously said:

“I think if you start seeing institutional LPs [limited partnerships] — like endowments, foundations, pension plans and sovereign wealth funds put capital into cryptocurrencies — you will see a tipping point where a percentage of world wealth starts flowing in. We are at the very earliest stages of that. Novogratz talks about the hordes coming, and I think that is correct. Crypto is still extremely driven by retail investors, but it’s staggering how much money is locked up in institutions.”

As seen in the graph below, the volume of the crypto market experienced a large spike in late 2017, as the prices of cryptocurrencies peaked at all-time highs.

But, over the past few months, the volume of the crypto market has started to recover, after experiencing a dip in March and April. In July, the volume of Bitcoin declined to sub 500,000 BTC but since August, apart from the first week of September, the volume of the crypto market has generally been improving.

Generally, crypto is still in its early phases of development, like the internet in 1994. Institutions are just preparing to get involved and infrastructures of the market have only started to improve rapidly since mid-2017. As such, it is too early to discuss the possibility of crypto competing against reserve currencies and central banks. Tan stated that the next 18 months could be crucial for crypto, as it will define the long-term trajectory of the market, adding:

“Central banks are a whole other level, and I don’t really know if and when they might decide it is something they [will] use as a reserve currency. That would be super far in the future, [in] my sense. We need to go from [the] infrastructure phase to [the] application phase, and I think that is the main story for the next 18 months. It’s still the internet in 1994.”

Mike Novogratz sees FOMO among institutions

In June, Novogratz stated that the crypto market will feel like a bubble once it reaches $20 trillion, after experiencing a hundredfold increase from the current price range.

At the time, Novogratz explained that the next rally of crypto will be fueled by institutions entering the crypto market, triggering FOMO (fear of missing out) among other institutional investors.

“[Cryptocurrency] is a global revolution. The internet bubble was only a U.S. thing. It was rich U.S. people participating. [Cryptocurrency] is global. There are kids in Bangladesh buying coins. It is monstrous in Tokyo, in South Korea, in China, in India and in Russia. We’ve got a global market and a global mania. This will feel like a bubble when we’re at $20 trillion.”

Over the past month, as Cointelegraph reported, Citigroup, Morgan Stanley and Goldman Sachs — three of the largest investment banks in the U.S. — have publicly released their plans to facilitate growing demand for Bitcoin from institutional investors.

Morgan Stanley is said to have already established a system to process funds coming from the traditional finance sector into the crypto market and is currently awaiting an internal procedure to launch its crypto custody.

Novogratz stated:

“It won’t go there [$20 trillion] right away. What is going to happen is, one of these intrepid pension funds — somebody who is a market leader — is going to say, ‘You know what? we’ve got custody, Goldman Sachs is involved, [and] Bloomberg has an index I can track my performance against,’ and they’re going to buy. And all of the sudden, the second guy buys. The same FOMO that you saw in retail [will be demonstrated by institutional investors].”

The deployment of crypto custodian solutions by regulated financial institutions and strengthening infrastructure around crypto will increase the probability of institutional investors committing to cryptocurrencies, which may increase the chances of the crypto market potentially achieving hundreds of trillions of dollars in valuation.

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[iota-news]

Note: A small update is made to include Hedera hashgraph platform, a public ledger announced by Swirlds this March.

While blockchain continues gaining attention, be it in cryptocurrency sphere or other innovative use cases in business world, new technologies are coming up to address some of their shortcomings. However the comparison is sometimes made with things mixed together. In this article I try to make it clear what belongs to which area, and then we can have a bigger picture, and make a more proper comparison among them. We don’t have to compare apples with oranges.

In the Beginning: Bitcoin and Blockchain

Bitcoin emerged almost a decade ago, and by and large it is still recognized as the first successful implementation of blockchain. Bitcoin is nothing more than a public ledger distributed in a large amount of nodes, and blockchain is the technology enabling this distributed ledger. A more generic term for this type of technology is called Distributed Ledger Technology (DLT).

Begin with Bitcoin as Permissionless Blockchain

The following is just the highlight about the nature of Bitcoin blockchain. We will refer to them when talking about other blockchain implementations.

It is distributed. The Bitcoin network is composed of a big number of computers (nodes). Each node has a copy of the Bitcoin blockchain.

It is permissionless, which means node can join and leave the Bitcoin network at any time. Joining the network helps enhancing its robustness, while leaving the network doesn’t do much harm at all.

It is decentralized, which means that no single organization owns the Bitcoin network, and can shut it down completely. Take a look on the Bitnodes site, the distribution looks quite balanced to certain extent. This also provides some intrinsic capability to withstand Denial of Service (DoS) attacks.

Take a look on how the Bitcoin network is as of today (March 2018), by more than 11,000 nodes running across the world.

Source: bitnodes.earn.com captured in 31st March, 2018.

Then, New Comers in Blockchain Family

Since then, we see several new blockchain initiatives. The largest two so far are Ethereum and Hyperledger. They are different in both use cases and deployment model.

A note: Hyperledger is an umbrella of projects hosted by Linux Foundation. It includes several blockchain projects. Different blockchain projects take some different approaches. Here I pick Hyperledger Fabric, contributed mainly by IBM, due to its larger media coverage and business activities.

Now we have both permissionless and permissioned blockchains

It is not easy to put down every detail. Here I just highlight those items that we will see later how other technologies are challenging blockchain.

Some quick comparison among them.

Both Ethereum and Hyperledger Fabric provide smart contract capability. However it makes little sense to tell which one is better than another. It is not very difficult for anyone to decide whether permissionless or permissioned blockchain is more appropriate in one’s use case.

Hyperledger does not come with native currency. But just this point does not make it less useful. In enterprise or consortium deployment, currency is usually not needed to fund the transaction, as the owner can take care of this. If needed, interfacing with external fiat currency is something doable to fulfil this requirement.

Consensus in Hyperledger in general can be reached much faster than in Bitcoin and Ethereum. It is due to the nature of decentralization on permissionless blockchains. In a permissioned environment, nodes are all under control by one or several known parties, and consensus can be much simpler.

While Ethereum can be deployed as private blockchain, the requirement of mining and lack of access control make Ethereum far from a permissioned implementation. Some efforts have done on Ethereum such as Quorum to make it more enterprise use ready as permissioned blockchain.

Here Comes the Challengers of Blockchain

Since their launch, many have pointed out various problems or challenges the current blockchain implementations are facing and therefore improvement is much needed. The improvement can come from an evolvement, without largely altering what we have today. Examples include the use of side chain or new consensus protocols. Or totally new approaches are proposed to solve the problems. Among the technologies, Directed Acyclic Graph (DAG) recently gets high spotlight. And there happens two implementations adopting DAG, one on permissionless and one on permissioned.

This article only provides a minimum introduction of these technologies. There are more comprehensive material on each of them.

Directed Acyclic Graph (DAG)

DAG is considered another way to represent the data structure with advantages over the blockchain approach.

A DAG. Source: wikipedia

In DAG there are nodes and connections. Nodes here are not computers. We can just see node as a piece of data. Nodes are linked cryptographically. The graph is called “directed” as we see there are directions for nodes (represented by arrows). It is called “acyclic” as there is no loop. This is the very basic about DAG.

There is no a single model how a DAG should be implemented. Here the two proposed approaches using DAG are implemented very differently. Meanwhile, blockchain is considered as one type of DAG of chain shape, and Ethereum is also an implementation of DAG although it’s more perceived as a blockchain.

IOTA Tangle: the Permissionless Ledger

IOTA addresses the challenges of existing permissionless blockchain implementation, in particular on the use cases of machine economy and micropayment. The challenges are,

scalability in handling large amount of transactions

high transaction fee

dichotomy on users (transaction issuers) and miners (transaction approvers)

In short, IOTA introduces Tangle, the DAG where user transactions are held. It is called “bundle of transactions” but for sake of simplicity we just term it “transaction”, represented by a square in the diagram. New transaction has to approve two unapproved transactions, called tips (grey square in the diagram), before being placed on the Tangle. This transaction then becomes a new tip, and is to be approved by transactions coming later. This forms the Tangle.

IOTA Tangle. Source: IOTA Tangle Whitepaper

With Tangle, there is no node specifically for mining, as each transaction itself acts as the “miner” to approve two other transactions. As no incentive is needed for miners, no transaction fee is needed. This fee-free fund transfer is foundation of machine economy and micropayment. The DAG is maintained through the tip selection by Random Walk Monte Carlo algorithm by every transaction. IOTA comes with native currency called iota, and the ledger is held inside the Tangle.

Swirlds Hashgraph: the Consensus protocol for Permissioned Ledger

Swirlds Hashgraph is positioned as a consensus protocol that promises “fast, secure and fair” when handling large volume of transactions.

Hashgraph today is a permissioned implementation, which is for enterprise or consortium deployment. In a nutshell, a group of participants share the transactions they know to others. The unit is called “event”, which contains the transaction items they know and they believe unknown to others (a circle shown in the diagram below). By proper linking the events cryptographically, everyone has the full graphic presentation of events and can therefore come up with a consensus on transactions with timestamp without third party involvement, which is called “virtual voting” among them.

Here is how Hashgraph looks like. The five participants forms the consensus after sharing events to one another. The Hashgraph algorithm guarantees the consensus achieved.

Hashgraph. Source: Hashgraph Whitepaper

Updated: Swirlds announced a public ledger, named Hedera hashgraph platform, in their launch event this March. This platform is permissionless, meaning that everyone can participate into the hashgraph consensus, while under permissioned governance by a Governing Board. It comes with its own cryptocurrency as one will expect in permissionless ledger, and can run smart contracts. We are expecting more information from Hedera before we can make a more comprehensive comparison.

Comparison with New Technologies

IOTA and Hashgraph are widely perceived as challengers to existing blockchain technology. Here we put them into the table, and try to make some reasonable comparisons.

A bigger picture of DLT, including implementations of blockchain and DAG.

IOTA Tangle is a valid challenger to Bitcoin and Ethereum as they all are permissionless, and coming with native cryptocurrency. In particular, IOTA addresses the shortcoming of scalability and high transaction fee which is not suitable for machine economy. There are quite many issues on IOTA during their first implementation. Nevertheless, just from technology perspective, we can keep our eyes how blockchain-based and DAG-based competes in the permissionless arena. One drawback currently on IOTA is the lack of smart contract capability, though some third parties are working on something like token standard on IOTA.

In some Hashgraph introduction, when they talk about how fast Hashgraph is (at hundreds of thousands per second), they always bring out Bitcoin (3–7 per second) and Ethereum (10–20 per second) for comparison. My view is that Bitcoin and Ethereum require additional effort to maintain its permissionlessness, which is the key difference compared to Hashgraph permissioned implementation. For better comparison, it should be either Hashgraph versus existing permissioned blockchain-based implementations like those in Hyperledger, or when Hashgraph comes out a permissionless network as what Bitcoin and Ethereum are doing today. Note: it is not simply a public ledger, but a real permissionless implementation as what Bitcoin and Ethereum work today.

Besides, Hashgraph is clearly positioned as a consensus layer, and a more complete framework is being built on top of it. As Hyperledgers projects support pluggable consensus services, instead of competing each other, there may be a way of collaboration. Nevertheless, the business model Swirlds currently taking is more an enterprise software approach and therefore they may prefer building their whole platform.

No serious comparison between Tangle and Hashgraph is observed so far. It makes sense as both are addressing different use cases, and the use of DAG has not much overlap. As both are still developing their technology and ecosystem we will see whether there will be any overlapping, such as Tangle in Enterprise use, or Hashgraph becomes a more permissionless deployment.

Summary

As mentioned in the beginning, new DAG-based technologies are challenging the existing blockchain players, in both permissionless and permissioned implementations. Understanding which part they belong to helps us to draft a bigger picture in this industry.

We will continue seeing heated debates among them. Put aside the investment values, reading their effort in bring new approaches is very inspiring, and let’s see how they are evolving and how the acceptance will be in the market, either in community or in business world.

Hope you enjoy reading. Give me some claps, and reach me on my LinkedIn.

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