Decentralized Systems Aren't

Below the fold is the text of a talk I gave to Berkeley's Information Systems Seminar exploring the history of attempts to build decentralized systems and why so many of them end up centralized.

As usual, you don't need to take notes. The text of my talk with links to the sources will go up at blog.dshr.org after this seminar.

Why Decentralize?

Tweets by language

This is a map of the location of tweets in Europe, colored by language. It vividly shows the contrast between a centralized society and more decentralized ones. I hope we can agree as to which one we'd prefer to live in.

The platonic ideal of a decentralized system has many advantages over a centralized one performing the same functions:

1. It can be more resilient to failures and attacks.
2. It can resist acquisition and the consequent enshittification.
3. It can scale better.
4. It has the economic advantage that it is hard to compare the total system cost with the benefits it provides because the cost is diffused across many independent budgets.

Why Not Decentralize?

But history shows that this platonic ideal is unachieveable because systems decentralization isn't binary and systems that aim to be at the decentralized end of the spectrum suffer four major problems:

1. Their advantages come with significant additional monetary and operational costs.
2. Their user experience is worse, being more complex, slower and less predictable.
3. They are in practice only as decentralized as the least decentralized layer in the stack.
4. They exhibit emergent behaviors that drive centralization.

What Does "Decentralization" Mean?

Source

In Gini Coefficients Of Cryptocurrencies I discussed various ways to measure decentralization. Because decentralization applies at each layer of a system's stack, it is necessary to measure each of the subsystem individually. In 2017's Quantifying Decentralization Srinivasan and Lee identified a set of subsystems for public blockchains, and measured them using their proposed "Nakamoto Coefficient":

The Nakamoto coefficient is the number of units in a subsystem you need to control 51% of that subsystem.

Subsystem	Bitcoin	Ethereum
Mining	5	3
Client	1	1
Developer	5	2
Exchange	5	5
Node	3	4
Owner	456	72

Their table of the contemporary Nakamoto coefficients for Bitcoin and Ethereum makes the case that they were only minimally decentralized.

Blockchains exemplify a more rigorous way to assess decentralization; to ask whether a node can join the network autonomously, or whether it must obtain permission to join. If the system is "permissioned" it cannot be decentralized, it is centralized around the permission-granting authority. Truly decentralized systems must be "permissionless". My title is wrong; the talk is mostly about permissionless systems, not about the permssioned systems that claim to be decentralized but clearly aren't.

TCP/IP

IBM Cabling System

The world has been on a decades-long series of experiments trying to build successful decentralized systems marked almost entirely by failure. Forty years ago I played a small part in one of the first of these experiments. I was working at Carnegie-Mellon's Information Technology Center on the Andrew Project, one of three pioneering efforts in campus networking. The others were at Brown and MIT. It was generously funded by IBM, who were covering the campus with the massively over-engineered "IBM Cabling System". They really wanted these wires to carry IBM's Token Ring network supporting IBM's System Network Architecture (SNA). SNA was competing with the telco's X.25 and DARPA's IP stack for the future of networking, and it wasn't clear which would win. But the three campus projects were adamant that their networks would run IP, largely because it was non-proprietary and far less centralized.

Domain Name System

Source

It is true that TCP/IP now dominates the bottom layers of the stack, but the common complaint is that the systems layered on it are excessively centralized. DNS is centralized around the root servers and IANA's (Internet Assigned Numbers Authority) management of top-level DNS domains and the global IP and AS spaces. They are the Internet's permission-granting authority. To scale, they have delegated management of sub-spaces to others, but the fundamental centralization remains. The Web is so centralized around the tech giants that there is an entire decentralized web movement. E-mail is increasingly centralized around a few major providers making life for those like me who run their own e-mail servers more and more difficult.

The basis of TCP/IP is the end-to-end principle, that to the extent possible network nodes communicate directly with each other, not relying on functions in the infrastructure. So why the need for root servers and IANA? It is because nodes need some way to find each other, and the list of root servers' IP addresses provides a key into the hierarchical structure of DNS.

This illustrates the important point that a system is only as decentralized as the least decentralized layer in its stack.

LOCKSS

Fifteen years on from CMU when Vicky Reich and I started the LOCKSS program we needed a highly resilient system to preserve library materials, so the advantages of decentralization loomed large. In particular, we realized that:

• A centralized system would provide an attractive target for litigation by the publisher oligopoly.
• The paper library system already formed a decentralized, permissionless network.

Our idea was to build a permissionless peer-to-peer system in which libraries would hold copies of their subscription content and model the paper inter-library loan and copy system to repair any loss or damage to them. To detect loss or damage the nodes would vote on the hash of the content. We needed to defend against a "Sybil attack", in which a bad guy wishing to change some content would create enough nodes under his control to win the votes on it. Our initial attempts at designing a protocol were flawed, but we eventually won a "Best Paper" award at the 2003 SOSP conference for a protocol that used proof-of-work (PoW) as a way of making running a node expensive enough to deter Sybil attacks. An honest library need only run one node, the bad guy had to run more than the total of the honest libraries, so would pay many times the per-library cost.

Why LOCKSS Centralized

• Software monoculture
• Centralized development
• Permissioning ensures funding
• Big publishers hated decentralization

Although the LOCKSS technology was designed and implemented to be permissionless, there were a number of reasons why it turned out much less decentralized than we hoped:

• Although we always paid a lot of attention to the security of LOCKSS boxes, we understood that a software monoculture was vulnerable to software supply chain attacks. So we designed a very simple protocol hoping that there would be multiple implementations. But it turned out that the things that a LOCKSS box needed to do other than handling the protocol were quite complex, so despite our best efforts we ended up with a software monoculture.
• We hoped that by using the BSD open-source license we would create a diverse community of developers, but we over-estimated the expertise and the resources of the library community, so Stanford provided the overwhelming majority of the programming effort.
• The program got started with small grants from Michael Lesk at NSF, then subsequently major grants from the NSF, Sun Microsystems and Don Waters at the Mellon Foundation. But Don was clear that grant funding could not provide the long-term sustainability needed for digital preservation. So he provided a matching grant to fund the transition to being funded by the system's users. This also transitioned the system to being permissioned, as a way to ensure the users paid.
• Although many small and open-access publishers were happy to allow LOCKSS to preserve their content, the oligopoly publishers never were. Eventually they funded a completely closed network of a dozen huge systems at major libraries around the world called CLOCKSS. This is merely the biggest of a number of closed, private LOCKSS networks that were established to serve specific genres of content, such as government documents.

Gossip Protocols

If LOCKSS was to be permissionless there could be no equivalent of DNS, so how did a new node find other nodes to vote with?

A gossip protocol or epidemic protocol is a procedure or process of computer peer-to-peer communication that is based on the way epidemics spread. Some distributed systems use peer-to-peer gossip to ensure that data is disseminated to all members of a group. Some ad-hoc networks have no central registry and the only way to spread common data is to rely on each member to pass it along to their neighbors.

Wikipedia

Suppose you have a decentralized network with thousands of nodes that can join and leave whenever they want, and you want to send a message to all the current nodes. This might be because they are maintaining a shared state, or to ask a question that a subset might be able to answer. You don't want to enumerate the nodes, because it would be costly in time and network traffic, and because the answer might be out-of-date by the time you got it. And even if you did sending messages individually to the thousands of nodes would be expensive. This is what IP multicast was for, but it doesn't work well in practice. So you build multicast on top of IP using a Gossip protocol.

Each node knows a few other nodes. The first time it receives a message it forwards it to them, along with the names of some of the nodes it knows. As the alternate name of "epidemic protocol" suggests, this is a remarkably effective mechanism. All that a new node needs in order to join is for the network to publish a few "bootstrap nodes", similar to the way an Internet node accesses DNS by having the set of root servers wired in. But this bootstrap mechanism is inevitably centralized.

The LOCKSS nodes used a gossip protocol to communicate, so in theory all a library needed to join in was to know another library running a node. In the world of academic libraries this didn't seem like a problem. It turned out that the bootstrap node all the libraries knew was Stanford, the place they got the software and the support. So just like DNS, the root identity was effectively wired-in.

Bitcoin

The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers.

Satoshi Nakamoto

Fast forward another ten years and Satoshi Nakamoto published Bitcoin: A Peer-to-Peer Electronic Cash System, a ledger implemented as a chain of blocks containing transactions. Like LOCKSS, the system needed a Sybil-proof way to achieve consensus, in his case on the set of transactions in the next block to be added to the chain. Unlike LOCKSS, where nodes voted in single-phase elections, Nakamoto implemented a three-phase selection mechanism:

1. One node is selected from the network using Proof-of-Work. It is the first node to guess a nonce that made the hash of the block have the required number of leading zeros.
2. The selected node proposes the content of the next block via the gossip network.
3. The "longest chain rule", Nakamoto's most important contribution, ensures that the network achieves consensus on the block proposed by the selected node.

Increasing Returns to Scale

Source

More than a decade earlier, W. Brian Arthur had published Increasing Returns and Path Dependence in the Economy explaining how the very strong economies of scale inherent to technology markets led to them being monopolized. Consider a new market opened up by a technological development. Several startups enter, for random reasons one gets bigger then the others, economies of scale make it more profitable and network effects make it more attractive to new customers, so this feedback loop drives it to out-compete the others.

The application to the Bitcoin network starts with this observation. The whole point of the Bitcoin protocol is to make running a miner, a node in the network, costly. The security of the system depends upon making an attack more costly to mount than it would gain. Miners need to defray the costs the system imposes in terms of power, hardware, bandwidth, staff and so on. Thus the protocol rewards miners with newly minted Bitcoin for winning the race for the next block.

Bitcoin Economics

Nakamoto's vision of the network was of many nodes of roughly equal power,"one CPU one vote". This has two scaling problems:

• The target block time is 10 minutes, so in a network of 600 equal nodes the average time between rewards is 100 hours, or about 4 days. But in a network of 600,000 equal nodes it is about 4,000 days or about 11 years. In such a network the average node will never gain a reward before it is obsolete.
• Moore's law means that over timescales of years the nodes are not equal, even if they are all CPUs. But shortly after Bitcoin launched, miners figured out that GPUs were much better mining rigs than CPUs, and later that mining ASICs were even better. Thus the miner's investment in hardware has only a short time to return a profit.

Mining Pools 02/27/23

The result was the formation of mining pools, allowing miners to contribute their power to a single huge node and trade their small chance of an infrequent large reward for a frequent flow of a small share of the node's rewards. But economies of scale applied even below the level of pools. A miner who could fill a warehouse with mining rigs or who was able to steal electricity would have much lower costs than a smaller miner. Thus they would not merely get more of the pool's block rewards, but they would keep more of them as profit. The success of this idea led to GHash.io's single node controlling the Bitcoin network with over 51% of the mining power. Most of it was from warehouses full of mining rigs.

The block rewards inflate the currency, currently by about $100M/day. This plus fees that can reach $23M/day, is the cost to run a system that currently processes 400K transactions/day, or over $250 per transaction plus up to $57 per transaction in fees. Lets talk about the excess costs of decentralization!

Like most permissionless networks, Bitcoin nodes communicate using a gossip protocol. So just like LOCKSS boxes, they need to know one or more bootstrap nodes in order to join the network, just like DNS and LOCKSS.

In Bitcoin Core, the canonical Bitcoin implementation, these bootstrap nodes are hard-coded as trusted DNS servers maintained by the core developers.

Haseeb Qureshi, Bitcoin's P2P Network

There are also fall-back nodes in case of DNS failure encoded in chainparamsseeds.h:

/**
 * List of fixed seed nodes for the bitcoin network
 * AUTOGENERATED by contrib/seeds/generate-seeds.py
 *
 * Each line contains a BIP155 serialized (networkID, addr, port) tuple.
 */

Economies of Scale in Peer-to-Peer Networks

Source

Fast forward another five years. Vicky Reich and I were driving North in my RX-7 for a long weekend at the Mendocino Hotel. On US101 before the driving got interesting on CA128 I was thinking about the recent period during which the GHash.io mining pool controlled 51% of Bitcoin's mining power.

I suddenly realized that this centralization wasn't something about Bitcoin, or LOCKSS for that matter. It was an inevitable result of economic forces generic to all peer-to-peer systems. So I spent much of the weekend sitting in one of the hotel's luxurious houses writing Economies of Scale in Peer-to-Peer Networks.

My insight was that the need to make an attack expensive wasn't something about Bitcoin, any permissionless peer-to-peer network would have the same need. In each case the lack of a root of trust meant that security was linear in cost, not exponential as with, for example, systems using encryption based upon a certificate authority. Thus any successful decentralized peer-to-peer network would need to reimburse nodes for the costs they incurred. How can the nodes' costs be reimbursed?:

There is no central authority capable of collecting funds from users and distributing them to the miners in proportion to these efforts. Thus miners' reimbursement must be generated organically by the blockchain itself; a permissionless blockchain needs a cryptocurrency to be secure.

And thus any successful permissionless network would be subject to the centralizing force of economies of scale.

Cryptocurrencies

ETH miners 11/2/20

There have been many attempts to create alternatives to Bitcoin, but of the current total "market cap" of around $2.5T Bitcoin and Ethereum represent $1.75T or 70%. The top 10 "decentralized" coins represent $1.92T, or 77%, so you can see that the coin market is dominated by just two coins. Adding in the top 5 coins that don't even claim to be decentralized gets you to 87% of the total "market cap".

The fact that the coins ranked 3, 6 and 7 by "market cap" don't even claim to be decentralized shows that decentralization is irrelevant to cryptocurrency users. Numbers 3 and 7 are stablecoins with a combined "market cap" of $134B. The largest stablecoin that claims to be decentralized is DAI, ranked at 24 with a "market cap" of $5B. Launching a new currency by claiming better, more decentralized technology than Bitcoin or Ethereum is pointless, as examples such as Chia, now ranked #182, demonstrate. Users care about liquidity, not about technology.

The holders of coins show a similar concentration, the Gini Coefficients Of Cryptocurrencies are extreme.

Ethereum's Merge

ETH Stakes 05/22/23

Ethereum made a praiseworthy effort to reduce their environmental impact by switching from Proof-of-Work to Proof-of-Stake and, in an impressive feat of software engineering, managed a smooth transition. The transition to Proof-of-Stake did in fact greatly reduce the Ethereum network's power consumption. Some fraction of the previous mining power was redirected to mine other Proof-of-Work coins, so the effect on the power consumption of cryptocurrencies as a whole was less significant. But it didn't reduce centralization, as the contrast between the before and after pie-charts shows.

Ethereum Validators

Time in proof-of-stake Ethereum is divided into slots (12 seconds) and epochs (32 slots). One validator is randomly selected to be a block proposer in every slot. This validator is responsible for creating a new block and sending it out to other nodes on the network. Also in every slot, a committee of validators is randomly chosen, whose votes are used to determine the validity of the block being proposed. Dividing the validator set up into committees is important for keeping the network load manageable. Committees divide up the validator set so that every active validator attests in every epoch, but not in every slot.

PROOF-OF-STAKE (POS)

Ethereum's consensus mechanism is vastly more complex than Bitcoin's, but it shares the same three-phase structure. In essence, this is how it works. To take part, a node must stake, or escrow, more than a minimum amount of the cryptocurrency,then:

1. A "smart contract" uses a pseudo-random algorithm to select one node and a "committee" of other nodes with probabilities based on the nodes' stakes.
2. The one node proposes the content of the next block.
3. The "committee" of other validator nodes vote to approve the block, leading to consensus.

Just as Bitcoin and LOCKSS share Proof-of-Work, Ethereum's Proof-of-Stake and LOCKSS share another technique, voting by a random subset of the electorate. In LOCKSS the goal of this randomization was not just "keeping the network load manageable", but also making life hard for the bad guy. To avoid detection, the bad guy needed to vote only in polls where he controlled a large majority of the random subset of the nodes. This was something it was hard for him to know. I'm not clear whether the same thing applies to Ethereum.

Like Bitcoin, the nodes taking part in consensus gain a block reward currently running at $2.75M/day and fees running about $26M/day. This is the cost to run a distributed computer 1/5000 as powerful as a Raspberry Pi.

Validator Centralization

The prospect of a US approval of Ether exchange-traded funds threatens to exacerbate the Ethereum ecosystem’s concentration problem by keeping staked tokens in the hands of a few providers, S&P Global warns.
...
Coinbase Global Inc. is already the second-largest validator ... controlling about 14% of staked Ether. The top provider, Lido, controls 31.7% of the staked tokens,
...
US institutions issuing Ether-staking ETFs are more likely to pick an institutional digital asset custodian, such as Coinbase, while side-stepping decentralized protocols such as Lido. That represents a growing concentration risk if Coinbase takes a significant share of staked ether, the analysts wrote.

Coinbase is already a staking provider for three of the four largest ether-staking ETFs outside the US, they wrote. For the recently approved Bitcoin ETF, Coinbase was the most popular choice of crypto custodian by issuers. The company safekeeps about 90% of the roughly $37 billion in Bitcoin ETF assets, chief executive officer Brian Armstrong said

Yueqi Yang, Ether ETF Applications Spur S&P Warning on Concentration Risks

A system in which those with lots of money make lots more money but those with a little money pay those with a lot, and which has large economies of scale, might be expected to suffer centralization. As the pie-chart shows, this is what happened. In particular, exchanges hold large amounts of Ethereum on behalf of their customers, and they naturally stake it to earn income. The top two validators, the Lido pool and the Coinbase exchange, have 46.1% of the stake, and the top five have 56.7%.

Producer Centralization

Producers 03/18/24

The concentration is worse for block producers. The chart shows the top producer is generating 47.4% of the blocks and gaining 56.6% of the rewards.

Olga Kharif and Isabelle Lee report that these concentrations are a major focus of the SEC's consideration of Ethereum spot ETFs:

In its solicitations for public comments on the proposed spot Ether ETFs, the SEC asked, “Are there particular features related to ether and its ecosystem, including its proof of stake consensus mechanism and concentration of control or influence by a few individuals or entities, that raise unique concerns about ether’s susceptibility to fraud and manipulation?”

Software Centralization

Source

There is an even bigger problem for Ethereum. The software that validators run is close to a monoculture. Two of the minor players have recently suffered bugs that took them off-line, as Sam Kessler reports in Bug That Took Down 8% of Ethereum's Validators Sparks Worries About Even Bigger Outage:

A bug in Ethereum's Nethermind client software – used by validators of the blockchain to interact with the network – knocked out a chunk of the chain's key operators on Sunday.
...
Nethermind powers around 8% of the validators that operate Ethereum, and this weekend's bug was critical enough to pull those validators offline. ... the Nethermind incident followed a similar outage earlier in January that impacted Besu, the client software behind around 5% of Ethereum's validators.
...
Around 85% of Ethereum's validators are currently powered by Geth, and the recent outages to smaller execution clients have renewed concerns that Geth's dominant market position could pose grave consequences if there were ever issues with its programming.
...
Cygaar cited data from the website execution-diversity.info noting that popular crypto exchanges like Coinbase, Binance and Kraken all rely on Geth to run their staking services. "Users who are staked in protocols that run Geth would lose their ETH" in the event of a critical issue," Cygaar wrote.

The fundamental problem is that most layers in the software stack are highly concentrated, starting with the three operating systems. Network effects and economies of sclae apply at every layer. Remember "no-one ever gets fired for buying IBM"? At the Ethereum layer, it is "no-one ever gets fired using Geth" because, if there was ever a big problem with Geth, the blame would be so widely shared.

The Decentralized Web

One mystery was why venture capitalists like Andreesen Horwitz, normally so insistent on establishing wildly profitable monopolies, were so keen on the idea of a Web 3 implemented as "decentralized apps" (dApps) running on blockchains like Ethereum. Moxie Marlinspike revealed the reason:

companies have emerged that sell API access to an ethereum node they run as a service, along with providing analytics, enhanced APIs they’ve built on top of the default ethereum APIs, and access to historical transactions. Which sounds… familiar. At this point, there are basically two companies. Almost all dApps use either Infura or Alchemy in order to interact with the blockchain. In fact, even when you connect a wallet like MetaMask to a dApp, and the dApp interacts with the blockchain via your wallet, MetaMask is just making calls to Infura!

Providing a viable user experience when interacting with blockchains is a market with economies of scale and network effects, so it has centralized.

It Isn't About The Technology

What is the centralization that decentralized Web advocates are reacting against? Clearly, it is the domination of the Web by the FANG (Facebook, Amazon, Netflix, Google) and a few other large companies such as the cable oligopoly.

These companies came to dominate the Web for economic not technological reasons. The Web, like other technology markets, has very large increasing returns to scale (network effects, duh!). These companies build centralized systems using technology that isn't inherently centralized but which has increasing returns to scale. It is the increasing returns to scale that drive the centralization.

Source

The four FANG companies last year had a combined free cash flow of $159.7B. I know of no decentralized Web effort that has a viable business model. This isn't surprising, since they are focused on developing technology not a business model. This means they pose no threat to the FANG. Consider that, despite Elon Musk's attempts to make it unusable and the availability of federated alternatives such as Mastodon, Twitter retains the vast bulk of its user base. But as I explained in Competition-proofing, if they ever did pose a threat, in the current state of anti-trust the FANGs would just buy them. In 2018 I wrote in It Isn't About The Technology:

If a decentralized Web doesn't achieve mass participation, nothing has really changed. If it does, someone will have figured out how to leverage antitrust to enable it. And someone will have designed a technical infrastructure that fit with and built on that discovery, not a technical infrastructure designed to scratch the itches of technologists.

I think this is still the situation.

BitTorrent

Seven years ago I wrote:

Unless decentralized technologies specifically address the issue of how to avoid increasing returns to scale they will not, of themselves, fix this economic problem. Their increasing returns to scale will drive layering centralized businesses on top of decentralized infrastructure, replicating the problem we face now, just on different infrastructure.

Source

The only way that has worked in practice to avoid increasing returns to scale is not to reimburse nodes for their costs, but to require them to be run as a public service. The example we have of avoiding centralization in this way is Bram Cohen's BitTorrent, it is the exception that proves the rule. The network doesn't reward nodes for hosting content, but many sites find it a convenient way to distribute content. The network doesn't need consensus, thus despite being permissionless it isn't vulnerable to a Sybil attack. Users have to trust that the tracker correctly describes its content, so there are other possible attacks. But if we look at the content layer, it is still centralized. The vast majority of the content is at a few large sites like The Pirate Bay.

Blockchains

In 2022 DARPA funded a large team from the Trail of Bits cybersecurity company to publish a report entitled Are Blockchains Decentralized? which conformed to Betteridge's Law by concluding "No":

Every widely used blockchain has a privileged set of entities that can modify the semantics of the blockchain to potentially change past transactions.

The "privileged set of entities" must at least include the developers and maintainers of the software, because:

The challenge with using a blockchain is that one has to either (a) accept its immutability and trust that its programmers did not introduce a bug, or (b) permit upgradeable contracts or off-chain code that share the same trust issues as a centralized approach.

Source

The gossip network underlying Bitcoin has centralized in two ways. First:

A dense, possibly non-scale-free, subnetwork of Bitcoin nodes appears to be largely responsible for reaching consensus and communicating with miners—the vast majority of nodes do not meaningfully contribute to the health of the network.

And second:

Of all Bitcoin traffic, 60% traverses just three ISPs.

Source

Trail of Bits found remarkable vulnerabilities to internal or external supply chain attacks because:

The Ethereum ecosystem has a significant amount of code reuse: 90% of recently deployed Ethereum smart contracts are at least 56% similar to each other.

The risk isn't confined to individual ecosystems, it is generic to the entire cryptosphere because, as the chart shows, the code reuse spans across blockchains to such an extent that Ethereum's Geth shares 90% of its code with Bitcoin Core.

Decentralized Finance

Source

I mentioned Moxie Marlinspike's My first impressions of web3 showing that dApps all used Infura or Alchemy. Many of them implement "decentralized finance" (DeFi), and much research shows this layer has centralized. Prof. Hilary Allen's DeFi: Shadow Banking 2.0? concludes:

TL;DR: DeFi is neither decentralized, nor very good finance, so regulators should have no qualms about clamping down on it to protect the stability of our financial system and broader economy.

DeFi risks and the decentralisation illusion by Sirio Aramonte, Wenqian Huang and Andreas Schrimpf of the Bank for International Settlements similarly conclude:

While the main vision of DeFi’s proponents is intermediation without centralised entities, we argue that some form of centralisation is inevitable. As such, there is a “decentralisation illusion”. First and foremost, centralised governance is needed to take strategic and operational decisions. In addition, some features in DeFi, notably the consensus mechanism, favour a concentration of power.

Protocol	Revenue	Market
	$M	Share %
Lido	304	55.2
Uniswap V3	55	10.0
Maker DAO	48	8.7
AAVE V3	24	4.4
Top 4		78.2
Venus	18	3.3
GMX	14	2.5
Rari Fuse	14	2.5
Rocket Pool	14	2.5
Pancake Swap AMM V3	13	2.4
Compound V2	13	2.4
Morpho Aave V2	10	1.8
Goldfinch	9	1.6
Aura Finance	8	1.5
Yearn Finance	7	1.3
Stargate	5	0.9
Total	551

Muyao Shen writes in DeFi Is Becoming Less Competitive a Year After FTX’s Collapse Battered Crypto that:

Based on the [Herfindahl-Hirschman Index], the most competition exists between decentralized finance exchanges, with the top four venues holding about 54% of total market share. Other categories including decentralized derivatives exchanges, DeFi lenders, and liquid staking, are much less competitive. For example, the top four liquid staking projects hold about 90% of total market share in that category,

Based on data on 180 days of revenue of DeFI projects from Shen's article, I compiled this table, showing that the top project, Lido, had 55% of the revenue, the top two had 2/3, and the top four projects had 78%. This is clearly a highly concentrated market, typical of cryptocurrency markets in general.

Federation

Source

The alternative to decentralization that is currently popular, especially in social media, is federation. Instead of forming a single system, federation allows many centralized subsystems to interoperate. Examples include BlueSky, Threads and Mastodon. Federation does offer significant advantages, including the opportunity for competition in the policies offered, and the ability for users to migrate to services they find more congenial.

How attractive are these advantages? The first bar chart shows worldwide web traffic to social media sites. Every single one of these sites is centralized, even the barely visible ones like Nextdoor. Note that Meta owns 3 of the top 4, with about 5 times the traffic of Twitter.

Source

The second bar chart shows monthly active users (MAUs) on mobile devices in the US. This one does have two barely visible systems that are intended eventually to be federated, Threads and Bluesky. Despite the opportunity provided by Elon Musk, the federated competitors have had minimal impact:

That leaves Mastodon with a total of 1.8 million monthly active users at present, an increase of 5% month-over-month and 10,000 servers, up 12%

In terms of monthly active users, Twitter claims 528M, Threads claims 130M, Bluesky claims 5.2M and Mastodon claims 1.8M. Note that the only federate-able one with significant market share is owned by the company that owns 3 of the top 4 centralized systems. Facebook claims 3,000M MAU, Instagram claims 2,000M MAU, and WhatsApp claims 2,000M MAU. Thus Threads is about 3% of Facebook alone, so not significant in Meta's overall business. It may be early days yet, but federated social media have a long way to go before they have significant market share.

Summary

Radia Perlman's answer to the question of what exactly you get in return for the decentralization provided by the enormous resource cost of blockchain technologies is:

a ledger agreed upon by consensus of thousands of anonymous entities, none of which can be held responsible or be shut down by some malevolent government

This is what the blockchain advocates want you to think, but as Vitalik Buterin, inventor of Ethereum pointed out in The Meaning of Decentralization:

In the case of blockchain protocols, the mathematical and economic reasoning behind the safety of the consensus often relies crucially on the uncoordinated choice model, or the assumption that the game consists of many small actors that make decisions independently. If any one actor gets more than 1/3 of the mining power in a proof of work system, they can gain outsized profits by selfish-mining. However, can we really say that the uncoordinated choice model is realistic when 90% of the Bitcoin network’s mining power is well-coordinated enough to show up together at the same conference?

As we have seen, in practice it just isn't true that "the game consists of many small actors that make decisions independently" or "thousands of anonymous entities". Even if you could prove that there were "thousands of anonymous entities", there would be no way to prove that they were making "decisions independently". One of the advantages of decentralization that Buterin claims is:

it is much harder for participants in decentralized systems to collude to act in ways that benefit them at the expense of other participants, whereas the leaderships of corporations and governments collude in ways that benefit themselves but harm less well-coordinated citizens, customers, employees and the general public all the time.

But this is only the case if in fact "the game consists of many small actors that make decisions independently" and they are "anonymous entities" so that it is hard for the leader of a conspiracy to find conspirators to recruit via off-chain communication. Alas, the last part isn't true for blockchains like Ethereum that support "smart contracts", as Philip Daian et al's On-Chain Vote Buying and the Rise of Dark DAOs shows that "smart contracts" also provide for untraceable on-chain collusion in which the parties are mutually pseudonymous.

Questions

If we want the advantages of permissionless, decentralized systems in the real world, we need answers to these questions:

• What is a viable business model for participation that has decreasing returns to scale?
• How can Sybil attacks be prevented other than by imposing massive costs?
• How can collusion between supposedly independent nodes be prevented?
• What software development and deployment model prevents a monoculture emerging?
• Does federation provide the upsides of decentralization without the downsides?