This post is part of a series that compares Ardor to other blockchain projects with similar features or goals. You can find the previous posts here:
This week I studied IOTA, a distributed ledger that doesn’t use a blockchain.
Why Compare Ardor and IOTA?
At first blush, IOTA is about as different from Ardor as a distributed ledger can be. It uses a directed acyclic graph (DAG), which its developers call “the tangle,” to represent the history of transactions, instead of storing transactions on a blockchain. It is intended to be used primarily for machine-to-machine microtransactions on the Internet of Things (IoT), a vision enabled by the fact that IOTA requires no transaction fees. And it doesn’t (yet) support the “blockchain 2.0” features that form a core part of Ardor’s appeal. On the surface, it doesn’t really look like a competitor to Ardor.
So why include IOTA in a series entitled “Ardor vs. the Competition”?
As I’ve mentioned before, my main interest with this series is in exploring different distributed ledgers’ approaches to scaling, and this is where the IOTA community has made some extraordinary claims. As I learned more about IOTA to better understand how it scales, I eventually came to the conclusion that IOTA and Ardor offer complementary (or more bluntly, opposite) solutions to the scaling problem:
Ardor dramatically reduces blockchain bloat but requires all nodes of the network to agree about the strict ordering of transactions; whereas IOTA achieves potentially higher throughput by relaxing the consensus rules a bit, allowing temporary discrepancies between transactions, but faces a significant challenge in coping with the growth of the tangle. These tradeoffs, plus what I learned about the security of the tangle, seemed interesting enough to warrant a post in this series.
If you aren’t convinced, though, please still check in next week!
After this post, I plan to shift my focus away from scalability and towards features and market fit. Stratis, Ark, and Waves are on the agenda, but I’m not sure of the order, yet.
Without a doubt, the key distinguishing feature of IOTA is the tangle.
IOTA’s other unique features, such as its lack of transaction fees, the fact that transactions are not strictly ordered but still eventually consistent, and the notion that (some) spam actually increases the throughput of the network, all stem directly from the way the tangle works.
For this reason, and also because I want to sidestep at least some of the recent controversy surrounding the IOTA project, I will try to focus primarily on understanding and evaluating the tangle itself, rather than picking apart the details of IOTA’s specific implemetation of it.
The tangle is a directed acyclic graph whose vertices represent individual transactions, and whose edges represent “approvals” of previous transactions. Each time a node submits a new transaction to the network it must choose two previous transactions to validate, which it references in the new transaction it submits. As the new transaction permeates the network, each node adds it to its local copy of the tangle, with one edge pointed to each transaction that the new transaction approved.
I tried my best, but this description is probably confusing. This diagram should help. Each square represents a transaction, and the arrows that point from each transaction to two others represent that transaction’s approval of the two earlier ones. The genesis transaction is somewhere far off the left side of the diagram, and the newest transactions, called “tips” in the white paper, are on the right side, shaded in gray.
What does it mean to validate, and hence approve, a transaction? Conceptually, the node doing the validation must start at the two transactions that it is validating and walk all paths back to the genesis transaction, ensuring that it never encounters a contradiction (e.g., double-spend, insufficient balance, or the like). If there is a contradiction, it chooses another pair of transactions to approve, knowing that no other node would ever approve the transaction it is submitting if it had approved a set of inconsistent transactions.
Notice that this means that each new transaction not only directly approves each of the two transactions it has chosen to validate, but also indirectly approves the transactions that those two approve, and the transactions that those transactions approve, and so on all the way back to the genesis. This is part of the basis for “eventual consensus” on the tangle.
In case you’re wondering about the computational burden of doing this validation, in practice it can be optimized substantially. Notice from the figures on this page that as you walk the tangle from the tips (far right) towards the genesis, you eventually reach a point past which all transactions are (indirectly) approved by all tips. In these figures, transactions approved by all tips are colored green. You could, therefore, cut the tangle across arrows that point to green transactions, validate the paths from those particular green transactions to the genesis a single time, cache the results, and from that point forward only validate from your new transaction back to those green transactions. This optimization saves you the time of validating the entire tangle every time you submit a transaction, and also allows the tangle to be pruned. More on that below.
One very interesting feature of a tangle-based ledger like IOTA is that nodes that receive new transactions from their peers don’t have to immediately validate them. In fact, the tangle can temporarily contain contradictory transactions. Eventually, though, a node must decide which of the contradictory transactions to approve (possibly indirectly) as it adds a new transaction.
How does it choose between conflicting transactions? Assuming that each transaction is valid if considered separately, then the short answer is that a node could choose to approve either one. It has an incentive to approve the one that the rest of the network will build on, though, so that its own transaction will eventually be approved, too. Most of the nodes on the network are assumed to run the reference algorithm for selecting transactions to approve, so in the event of a conflict, a node has an incentive to choose the transaction that the reference algorithm selects.
In order to understand the reference algorithm, it is important to first understand the concept of the cumulative weight of a transaction.
Each node that submits a new transaction must do some proof-of-work (PoW), which determines the “own weight” of the transaction. The cumulative weight of a transaction is then its own weight plus the own weights of all transactions that have directly or indirectly approved it. In a general tangle the node can decide how much work to do for a transaction, but in IOTA all transactions require the same PoW and thus have the same own weight. As a result, the cumulative weight of a transaction is proportional to the number of other transactions that directly or indirectly approve it.
What, then, is the reference algorithm? The author of the white paper calls it Markov-Chain Monte Carlo (MCMC, see section 4.1), which is a fancy way of saying that it is a random walk along the tangle that favors paths with greater cumulative weight. This post is already getting long, so I’ll skip the details. Suffice it to say that, when there are conflicting transactions, the MCMC algorithm resolves the conflict by tending to choose whichever transaction has the greater cumulative weight behind it. Eventually, one subtangle becomes dominant and the other is orphaned. This is analogous to the mechanism that blockchains use to resolve forks, and the cumulative weight of a transaction in IOTA is a rough measure of its finality in the same way that adding blocks to a blockchain confirms previous transactions with greater and greater certainty.
By the way, the fact that nodes don’t immediately need to validate each new transaction received from their peers has big implications for performance. Each node does less work this way, validating transactions only when it submits a new transaction, and taking for granted that transactions that are indirectly approved by all tips have already been validated by the rest of the network. Also, validations run in parallel across the network, as different nodes choose different subsets of transactions to approve.
So far I have mostly just regurgitated the information found in the IOTA white paper. The issue of the security of the tangle, on the other hand, is where things get a lot more interesting. While I definitely recommend reading the analysis in the white paper of different attacks on the tangle–and the rest of the white paper, for that matter, because it is very well written–I won’t discuss most of that analysis here.
Instead, I want to focus on the most obvious threat, which is a 51% attack. The IOTA devs actually refer to it as a 34% attack, for reasons that I’m not sure I understand. I suspect it’s because an attacker who waits for a fork to occur naturally only needs enough hashpower to out-compute the nodes on each branch of the fork–i.e., more than 50% of the rest of the network’s hashpower. Anyway, the exact number isn’t important, and for the remainder of this article I will use the term “34% attack.”
With IOTA, a 34% attack would look roughly like this. An attacker issues a transaction that spends some funds, represented by the rightmost red dot, then computes (or perhaps has precomputed) his own “parasitic” subtangle, which anchors to the main tangle somewhere upstream of his transaction and which contains a double-spend transaction, represented by the leftmost red dot. His goal is to add enough cumulative weight to his parasitic tangle to convince the MCMC algorithm to orphan the main tangle and follow the parasitic one.
Hopefully, the analogies to the blockchain are clear so far, because there is one more important one. Like a PoW blockchain, the tangle is secured by the current hashpower of the network, since this hashpower is what adds cumulative weight to the legitimate tangle. Unlike a PoW blockchain, though, nodes on IOTA only do PoW when they submit transactions. The security of the tangle, therefore, depends only on the transaction rate and the amount of PoW per transaction. Take a second to let that idea sink in because it is absolutely central to understanding the security of the tangle.
Because the IOTA network is currently small and the transaction rate is low, the IOTA team has established a single trusted node, called the Coordinator, that is ultimately responsible for deciding the current state of the tangle. Its purpose is to protect against 34% attacks, among other attacks. I’m not going to spend any more time on it, but I encourage you to read this critique and the devs’ responses, and draw your own conclusions about whether IOTA can be called decentralized while running under the supervision of the Coordinator.
Let’s see if we can come up with an order-of-magnitude estimate of how secure the network could be without the Coordinator. A recent stress test achieved well over 100 transactions per second (tps) on a small test network. The team suggested that 1,000 tps is achievable. To be generous, let’s assume that IOTA will eventually scale to 10,000 tps. I don’t know what the current PoW requirement on IOTA is, but let’s suppose that the average IoT device is approximately a Raspberry Pi and it runs at 100% CPU for 10 seconds to do the required PoW. Again, I’m trying to be generous; many IoT devices are considerably less powerful than a Raspberry Pi, and pegging the CPU for 10 seconds for each transaction would probably be a dealbreaker.
With these assumptions, we conclude that the average computational power securing the network is roughly 10,000 x (# of computations by Raspberry Pi in 10 s) per second, or equivalently, 100,000 times the computational power of a single Raspberry Pi. There are a lot of nuances to properly benchmarking computers, but we’re not concerned about factors of two or three–we’re just going for an order-of-magnitude estimate–so we’ll use some numbers I found on the internet.
A Raspberry Pi3 can achieve hundreds of MFLOPS (megaflops, or millions of floating-point operations per second), while high-end GPUs clock in at thousands of GFLOPS (gigaflops, or billions of FLOPS), a factor of 10,000 greater computing power. So in our hypothetical scenario, an attacker with ~10 GPUs could out-compute the entire network. Throw in another factor of 10 because I was being sloppy–maybe integer operations are a bit slower on the GPUs than floating-point operations, for example–and you still only need 100 GPUs to execute the attack.
I’m sure there are plenty of holes to poke in this analysis. Perhaps IOTA won’t run on devices all the way at the edge of the network, for example. Instead, it might run on the gateways and routers that those IoT devices connect to, which are typically much more powerful.
Still, the point I’m trying to make is that PoW successfully secures blockchains like Bitcoin and Ethereum because it isn’t tied to the transaction rate, or any other factor besides the economic value of the network. As the value of the mining reward (in fiat currency) increases with the price of Bitcoin, miners add more hardware and consume more electricity to mine it. The economic incentive to mine ensures that the amount of hashpower securing the network increases with the network’s monetary value.
With IOTA, in contrast, there is no economic incentive to secure the network. Moreover, the hashpower securing the network is tied directly to the transaction rate, which naturally has some upper limit dependent on bandwidth and network topology.
On this last point, the IOTA developers have made a creative argument, not included in the white paper, that bandwidth limitations and network topology actually improve the security of the network. I haven’t found an official statement of it anywhere, but after some digging I stumbled upon this Slack conversation, which is the most complete defense I could find.
Essentially, one of the IOTA developers (specifically Come-from-Beyond, a.k.a. Sergey Ivancheglo, possibly a.k.a. BCNext, also one of the original creators of Nxt), argues that the IOTA network will consist of IoT devices peered exclusively with their nearest neighbors in a meshnet topology, and that an attacker will not even have the option of peering with more than a very small number of devices on each such mesh. That is, the vast majority of devices will not be accessible from the internet or some other “backbone” of the network, and the only way to send messages to them will be through the mesh of other devices.
The general idea is that the mesh as a whole will be capable of achieving a high throughput, but each individual link in the mesh has a low enough bandwidth that an attacker would easily saturate it by trying to add enough transactions to convince the network to follow his parasitic subtangle. Since the attacker only has a few entry points into the mesh, he saturates all of them before his parasitic tangle accumulates enough weight for his attack to succeed.
I’ll let you draw your own conclusions about this argument. I personally don’t think the IOTA team has made enough details public to thoroughly evaluate it.
Speaking of bandwidth limitations, let’s talk about scaling.
Because each node must validate two other transactions before submitting its own transaction, the IOTA team likes to point out that spam actually tends to make the network more efficient. Other members of the IOTA community get carried away with this point, sometimes even making the absurd claim that IOTA is “infinitely scalable.”
Every node on the IOTA network must eventually receive every transaction in order to maintain a globally consistent tangle. Broadcasting transactions to remote nodes takes time, though, and if the transaction rate is high enough that a node receives a lot of transactions from nearby nodes before it receives the next transactions from distant nodes, the MCMC algorithm will continue to select tips submitted by nearby nodes. Eventually the tangle splits, with only nearby nodes transacting on the local copy of the tangle and remote nodes transacting on their own, divergent copy.
So bandwidth and network topology must place some limitations on the transaction rate of IOTA if the tangle is to be consistent across the entire network. We will have to wait for more stress tests to learn what these limitations are.
Additionally, like all distributed ledgers, IOTA must grapple with bloat. Each transaction on IOTA is approximately 1.6 kB in size, so a transaction rate of 100 tps would grow the tangle at a rate of 160 kB per second, or about 14 GB per day. Needless to say, that’s an unrealistic storage requirement for an IoT device.
IOTA currently solves this problem by taking periodic snapshots of the tangle, which map its current state into a new genesis transaction, allowing the transaction history to be pruned away. In the limit of very frequent pruning, a node would only have to store enough of the tangle to be able to run the MCMC algorithm.
Syncing a new node with the network is a different story, though. Either the node must download the latest snapshot from a trusted peer, or it must start at the original genesis transaction and work its way forward through the entire tangle. There is no way to trustlessly and efficiently join the network.
Finally, it’s worth noting that the IOTA team has proposed a type of horizontal partitioning of the tangle that they call a “swarm,” where many nodes together store the complete tangle but no one node stores all of it. Unfortunately, there aren’t many details yet on how this works.
Compared to Ardor
So what does any of this have to do with Ardor?
In my opinion, there are two main comparisons to draw, namely on the issues of security and scalability.
Regarding security, it isn’t clear to me that IOTA could possibly reach a high enough transaction rate to be considered secure without the Coordinator, given the monetary value of even the current network, without choosing a very high PoW requirement.
Ardor, in contrast, has the advantage that its child chains are all secured by the single parent chain.
A “small” child chain wouldn’t need a trusted node like IOTA’s Coordinator to protect it because consensus is established by the entire network and recorded (via hashes of child chain blocks) by forgers on the parent chain.
On scalability, IOTA and Ardor both currently share the requirement that each node of the network process all transactions. With IOTA, this simply means adding transactions to the tangle, which is computationally cheap, whereas, with Ardor, every node must validate every transaction. Moreover, the clever design of the tangle ensures that the confirmation time for a transaction actually decreases as the network gets busier. I would not be surprised to see IOTA achieve higher throughput than Ardor as both networks grow.
On the other hand, IOTA faces a tremendous challenge in combating tangle bloat if it is ever to achieve hundreds of transactions per second, whereas Ardor has largely solved this problem.
Finally, it’s worth noting that a proposal on the Ardor roadmap would delegate child chain transaction processing to dedicated subnets of the network. This would potentially achieve a computational gain similar to IOTA’s “swarming” proposal, possibly allowing similarly high throughput.
If you’ve read this far (thank you!!) and were already familiar with IOTA, then you’ve undoubtedly noticed that I left out a lot of details, including its homebuilt hashing algorithm, the deliberate flaw in this algorithm that Come-from-Beyond included as a copy-protection mechanism, the use of ternary encoding, and the mysterious Jinn processor that will provide hardware support for IOTA in IoT devices. In the course of my research, I’ve formed fairly strong opinions on all of these things, but I was reluctant to share them here for two reasons.
First, I don’t have sufficient information to make objective statements on these issues. I’m not a cryptographer, and I know next to nothing about ternary computing or Jinn. The best I could do would be to offer subjective judgments of the design decisions the IOTA team made, but that would have simultaneously weakened the focus of this article and opened it to criticism from people who have made different subjective judgments.
Secondly, and more importantly, I’m more interested in the fundamental concepts behind the tangle than IOTA’s specific implementation of it. Regardless of whether IOTA succeeds or fails, the tangle is a beautiful idea and deserves all the attention we can muster.
So what can we say about the tangle, then? While I’m positively enamored with the elegance of its design and the nuances of its consensus mechanism, at the end of the day I’m afraid I’m quite skeptical of its suitability for the Internet of Things. Drop that aspect, increase the PoW requirement by several orders of magnitude, and find a way to tie the PoW threshold to the monetary value of the network without cutting ordinary users off from their funds, and I think the tangle has tremendous potential as a distributed ledger.
The last missing piece is how to cope trustlessly and efficiently with bloat, a problem that Ardor have solved extremely well. Perhaps somebody will find a way to combine the best elements of both designs at some point in the future. A lot could happen by then, especially in cryptoland.
P.S. – I promise the next article will be shorter. 🙂