Decentralized systems such as the electric network and World Wide Web scaled by solving communication bottlenecks. Blockchains, a triumph of decentralized design, should follow the same pattern, but early technical limitations led many to equate decentralization with inefficiency and sluggish performance.
When Ethereum turns 10 years in July, it develops from a developer playground to the backbone of Onchain Finance. As institutions such as Blackrock and Franklin Templeton launch tokenized funds, and banks roll stablecoins, the question now is whether it can scale to meet global demand-where heavy workloads and Millisecond-level response times matter.
For all this development, an assumption still hangs: that blockchains must exchange between decentralization, scalability and security. This “blockchain trilemma” has shaped protocol designs since Ethereum’s Genesis block.
The trilemma is not a physics law; It is a design problem that we finally learn to solve.
Lay of the Land on scalable Blockchains
Ethereum-Med Founder Vitalik Barterin identified three properties of blockchain performance: decentralization (many autonomous nodes), safety (resistance to malicious actions) and scalability (transaction speed). He introduced “Blockchain Trilemma”, suggesting that improving two typically weakens the third, especially scalability.
This framing formed Ethereum’s path: the ecosystem prioritized decentralization and security, building for robustness and fault tolerance across thousands of nodes. But the performance is limp with delays in blockage, consensus and finality.
To maintain decentralization during scaling, some protocols about Ethereum reduces the participation of the validator or Shard Network responsibility; Optimistic Rollups, Change Off-Chain and Relying on Fraud Evidence To Maintain Integrity; Layer-2 design aims to compress thousands of transactions into a single person obliged to the head chain, where he reads scalability pressure, but introduces dependencies on reliable hubs.
Security remains crucial as financial efforts rise. The error stems from downtime, collision or message propagation error, causing agreement to stop or double-use. Still, most scales depend on best performance instead of protocol-level guarantees. Validators are incentive to increase computing power or rely on quick networks, but lack warranties that transactions will implement.
This raises important questions to Ethereum and the industry: Can we be sure that any transaction ends under load? Are likely approaches enough to support applications on a global scale?
As Ethereum enters its second decade, answering these questions will be crucial to developers, institutions and billions of end users who depend on blockchains to deliver.
Decentralization as a strength, not a limitation
Decentralization was never the cause of sluggish ux at Ethereum, network coordination was. With the right technique, decentralization becomes a benefit advantage and a catalyst for scale.
It feels intuitive that a centralized command center would surpass a fully distributed. How couldn’t it be better to have an omniscient controller that oversees the network? This is exactly where we would like to demystify assumptions.
Read more: Martin Burgherr – why ‘expensive’ Ethereum will dominate institutional defi
This faith began decades ago in Professor Medard’s laboratory at MIT to make decentralized communication systems provenly optimal. Today, with random linear network coding (RLNC), this vision can finally be implemented in scale.
Let’s get technically.
To address scalability, we must first understand where latency occurs: In blockchain systems, each node must observe the same operations in the same order to observe the same series of state changes that start from the original state. This requires consensus – a process where all nodes agree on a single suggested value.
Blockchains like Ethereum and Solana, use leader -based consensus with predetermined time tracks, where nodes should come to an agreement, let’s call it, let’s call it “d”. Choose D For Large and Finality slows down; Choose that too small and consensus fails; This creates a sustained trade -off in performance.
In Ethereum’s consensus algorithm, each node tries to communicate its local value to the others through a series of message exchanges via gossip. However, due to network disorders, such as overload, bottlenecks, buffer overflow; Some messages may be lost or delayed and some can be duplicated.
Such events increase the time of information dissemination and thus result in consensus inevitably in large D -slots, especially in larger networks. In scale, many blockchain’s decentralization limits.
These blockchains require attesting from a particular threshold for participants, such as two -thirds of the effort, for each consensus round. In order to achieve scalability, we need to improve the effectiveness of communications.
With random network linear coding (RLNC), we aim to improve the scalability of the protocol directly addressing the limitations imposed on current implementations.
Decentralize to scale: the force in RLNC
Random linear network coding (RLNC) is different from traditional network codes. It is stateless, algebraic and completely decentralized. Instead of trying to micromanage traffic, each knot mixes coded messages independently; Still, optimal results are achieving a central controller orchestrated network. It has been proven mathematically that no centralized planning would exceed this method. It is not common in system design, and that is what makes this approach so powerful.
Instead of forwarding raw messages, RLNC-activated nodes share and transmit message data to coded elements using algebraic equations over final fields. RLNC allows nodes to restore the original message by using only a subgroup of these coded pieces; There is no need for any message to arrive.
It also avoids double work by letting each knot mix what it receives in new, unique linear combinations on the go. This makes any exchange more informative and resistant to network delays or losses.
With Ethereum -Validators, which now tests RLNC through Optimump2p – including oven, p2p.org and everstake – this shift is no longer hypothetical. It’s already moving.
Next, RLNC-powered architectures and PUB-Sub-Protocols will be connected to other existing blockchains to help them scale with higher flow and lower latency.
A call to a new industry benchmark
If Ethereum is to serve as the basis for global funding in the second decade, it must move beyond outdated assumptions. Its future will not be defined by trade -offs, but by proving performance. The trilemma is not a law of nature, it is a limitation of old design that we now have the power to overcome.
To meet the requirements for the adoption of the real world, we need systems designed with scalability as a first -class principle, supported by proving performance guarantees, not varies. RLNC offers a path forward. With mathematically grounded flow guarantees in decentralized environments, it is a promising foundation for a more performing, responsive ethereum.
Read more: Paul Brody – Ethereum has already won
