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Scaling the Ethereum Network
On-chain scaling techniques are upgrades made to a blockchain’s base layer to improve scalability. Ethereum’s long-term, on-chain scaling solution is called sharding which actually splits the base layer into 64 chains with shared security ensured by the Beacon Chain.
Off-chain scaling refers to scaling solutions that use external execution layers rather than the base layer. These Layer 2s, or “L2s” are secondary layers that sit on top of the base layer, providing more transactional capacity for the blockchain overall. Ethereum is pursuing both off-chain and on-chain scaling strategies.
Ethereum’s eventual transition to Proof of Stake is a response to these challenges. It’s a massive upgrade to the entire Ethereum ecosystem to accommodate continued growth and an increasing workload, consume less electric power in its verification process, and to be more secure from attacks. In essence, the Ethereum upgrade will make the network more scalable, sustainable, and secure.
Any human enterprise which is highly successful early on will quickly have to address how to do more to keep up with demand. This is a good problem to have, but not an easy one to solve because scaling up often challenges the core values that made the enterprise successful.
Ethereum, as we know it today, won't scale. Meaning, the Ethereum L1 is designed to remain a highly decentralized, global settlement layer above all else. However, Ethereum's web of L2s will be responsible for scaling Ethereum and serving as its execution layer. These layers will absorb much of the existing value on Ethereum mainnet plus future inflows as Ethereum adoption grows. It's important to understand that Ethereum's web of L2s is a marketplace of independent projects competing with each other to help scale Ethereum.
The Scalability Trilemma
Ethereum’s ability to process transactions is (partially) constrained by the amount of computing power, bandwidth, and storage on the network. The scalability trilemma is a well-known issue among all blockchains.
The scalability trilemma, illustrated. Credits: Vitalik Buterin
A blockchain can achieve two of these traits but at the expense of the third. Many alternative layer 1 (L1) chains have chosen to sacrifice decentralization for scalability and security. However, it’s important to remember why decentralization is important. It provides the chain anti-fragility, robustness, reliability, and censorship resistance.
The goal is to increase the number of transactions while retaining sufficient decentralization. What are the decentralization sacrifices (tradeoffs) other smart contract L1s have made? Other chains typically make two sacrifices. They either design their network to be run/secured with high-powered, expensive nodes, which reduces the number of people that may participate in network consensus by pricing them out. Obviously, a network that can only be verified if you have X amount of dollars in computing budget is not an ideal, permissionless system.
Another tradeoff often considered is for the network to use fewer nodes to achieve consensus in les time. However, this makes the chain more vulnerable and centralized. It is easier to corrupt or destroy 10 nodes rather than 10,000 all over the globe.
Although often discussed as such, blockchain scalability does not just pertain to TPS. Many L1s, like BINANCE Smart Chain (BSC), currently boast high TPS numbers but suffer from “chain bloat” and ever-increasing hardware requirements just to keep the chain running. L1s must be able to process more transactions without creating more problems down the road. A node in a technically sustainable blockchain has to do three things:
- Keep up with the tip of the chain (most recent block) while syncing with other nodes.
- Be able to sync from genesis in a reasonable time (days as opposed to weeks).
- Avoid state bloat.
Requirement 1 above is a physical limitation based on computing power (RAM, CPU, etc.) and bandwidth. These are bottlenecks for every node which means there are upper, finite limits to how far you can push the network.
One way for Ethereum to increase its workload could be to increase the size of the computers participating in the Ethereum network (participating computers are called “nodes”). But larger, more expensive, and fewer computers in the network (like Solana) is clearly a form of centralization. Having a small number of bigger players involved in maintaining Ethereum is not Ethereum’s goal.
Fewer computers in the network also creates security issues. A hacker attacking just a few computers, or a single central computer will have an easier time than attacking a huge number of computers all in agreement about the data they are using and creating. Just as with Bitcoin, more computers participating in the Ethereum network enhance the security and permanence of the data on the Ethereum blockchain.
Transitioning from PoW to PoS (“The Merge”)
The Merge is the term used for when Ethereum switches from Proof-of-Work (PoW) to a Proof-of-Stake (PoS) blockchain. This is slated to occur in Q2 2022 and bring with it many benefits that were not previously possible with PoW.
PoS removes the energy consumption often cited in the mainstream media. While PoW is not inherently a bad thing, it’s inarguable that the world is highly critical of energy consumption and now, with the transition to PoS, Ethereum will have eliminated this one enormous criticism. Estimates from Ethereum core developers hypothesize that Ethereum’s energy use will drop by up to ~99%. Without the need for so much physical mining hardware and infrastructure, Ethereum can become a more energy-efficient, geographically-distributed, and nimble blockchain.
Ethereum’s eventual transition from Proof of Work (PoW) to Proof of Stake (PoS) will represent the culmination of the original Ethereum protocol design, 5+ years of technical research and associated game theory design. It is designed, ultimately, for a simpler, more robust, stable, and secure base layer protocol with full lite client verifiability. After the full implementation is complete, the base layer can then “ossify” while leaving the flexibility for innovation on higher protocol levels like Layer 2. The Beacon Chain serves as the epicenter of the future architecture and network consensus. PoS aims to lower the cost of participating in securing the network by allowing anyone with ETH to stake rather than needing a giant million-dollar mining farm as is the case in most PoW networks.
With PoS, the Ethereum base layer will be managed by validators rather than PoW miners. A validator is a person or entity who locks up (stakes) 32 ETH in order to run a validating node and secure the Ethereum blockchain. This means rather than relying on energy/electricity for security as is the case in PoW, Ethereum security will rely upon capital instead. With PoS and staking rewards, ETH becomes a productive capital asset with yield as well as a the money underpinning network transactions and executing smart contracts.
Beacon Chain
Key takeaways from the early instantiations of the Beacon Chain are:
- Introducing the ETH Proof of Stake consensus layer;
- Tracks ETH validators and balances;
- One-way ETH deposit to stake on the Beacon Chain; and
- No state management (transactions, smart contracts).
The Beacon Chain will be the center of Ethereum’s new consensus mechanism, assuming the full transition goes ahead. The Beacon Chain will be responsible for the liveness, veracity, and consensus on the new chain. Future sharded layers (shards) will all connect back to the Beacon Chain with many validators across all 64 shards. The Beacon Chain will provide the foundation for hundreds of thousands of validators, distributed across thousands of nodes globally. It will organize validators into committees and apply the consensus rules that dictate the network.
A slot is when a block is added to the Beacon chain. Every 12 seconds there is a slot and 32 slots (6.4 min) are grouped into an epoch. Casper FFG decides on which blocks become part of the chain, finalizing an epoch. Every epoch, one validator is pseudo-randomly assigned by a beacon to a slot and shard. At least one committee, a group of validators (minimum of 128) is also chosen to attest the epoch.
Additionally, PoS is a predecessor for sharding, another critical Ethereum protocol change that will separate the chain into many concurrent threads.
Sharding
Sharding is the term for horizontally partitioning a database and does not create more burden for the average user. In this sharding model, validators are assigned to specific shards and only process and validate transactions in that shard. In Ethereum's planned sharding model, validators are randomly selected. Every shard has a (pseudo) randomly-chosen committee of validators that ensures it is (nearly) impossible for an attacker controlling less than ? of all validators to attack a single shard.
??After the switch to Proof-of-Stake, sharding is the next significant hard fork upgrade on Ethereum’s roadmap. Just like the Merge, the sharding plan has evolved over time and may continue to change between now and implementation.
Sharding is the partitioning of a database (or blockchain) into subsections. Rather than building layers atop one another (e.g. L2s or Bitcoin’s Lightning Network), sharding scales out or horizontally without a hierarchy or layered structure. Doing so does not create more burden for the average user.
Shards will be divided among nodes so that every individual node is doing less work. But collectively, all of the necessary work is getting done—and more quickly. More than one node will process each individual data unit, but no single node has to process all of the data anymore.
Original diagram by Hsiao-wei Wang, design by Quantstamp
In Ethereum’s vision of a sharded chain, a (pseudo) randomly-chosen committee of validators are randomly selected and assigned to specific shards. This means they are only responsible for processing and validating transactions in those specific shards, not the entirety of the network. The randomness of the validator selection process ensures it’s (nearly) impossible for a nefarious actor to successfully attack the network.
Initially, prior to the breakthrough in rollups, Ethereum’s plan was to do sharded computation. However, now with rollups providing the much-needed network scalability, sharding will focus on data availability to provide throughput for the rollups. This is because the bottleneck for rollup scalability is data availability capacity rather than execution capacity. This will give L2s more space to store the chain’s data and offer additional data capacity for rollups.
In a sense, shards will serve as data storage “buckets” for new network data storage demand from rollups. This enables tremendous scalability gains on the rollup execution layer. Just as significant, shards will also help avoid putting overly-onerous demand on full nodes, allowing the network to maintain decentralization.
Sharding will be released in a multi-step process to provide immediate data availability for rollups before releasing the ultimate but more complex vision. A small subset of data shards (four) will initially be released to keep complexity low, i.e. a slow, controlled rollout.
Earlier, we outlined one reason why Ethereum transaction fees were so high was due to all nodes in the network having to process all transactions and reach consensus. Sharding is the answer to the question, “What if each node did not have to process every operation at the same time?” What if, instead, the network was divided into subsections (shards), that operated semi-independently until finally reaching consensus through a central hub (Beacon Chain)?
Shard 1 could process one batch of transactions, while Shard B processes another batch. This would effectively double the transaction throughput of a blockchain, since our limit is now what can be processed by two nodes at the same time. If we can split a blockchain into many different sections, then we can increase the throughput of a blockchain by many multiples.
Ethereum will be split into different shards, each one independently processing transactions. Sharding is often referred to as a Layer 1 scaling solution because it’s implemented at the base-level protocol of Ethereum itself.
