Advancing Ethereum's scalability through experimental blockchain parameters
Bloatnet is an ambitious effort to create a new Ethereum-like chain with altered parameters that enable greater throughput through bigger gas limits and smaller slot times.
Know when state growth becomes a critical issue → prioritize statelessness
Ethereum's state continues to grow with every transaction, contract deployment, and storage operation. This accumulation creates an invisible but mounting pressure on the network's sustainability. Without precise monitoring, we risk reaching critical thresholds where client synchronization becomes prohibitively slow and hardware requirements exclude everyday participants.
Bloatnet provides real-world stress testing by intentionally accelerating state growth in a controlled environment. We measure performance degradation at specific size milestones (500GB, 1TB, 2TB+) to identify the exact points where statelessness transitions from "nice to have" to "mission critical" for Ethereum's survival.
This research directly informs Ethereum's roadmap priorities. By knowing precisely when state growth becomes problematic, core developers can allocate resources effectively and implement statelessness solutions before the network experiences degradation. The data we collect today prevents future network emergencies.
Gather extensive performance data with high gas limits
Current Ethereum testnets operate within conservative parameters that don't stress-test the boundaries of what's possible. Bloatnet breaks these constraints by running with significantly higher gas limits and accelerated block times, creating a laboratory for extreme conditions that mainnet may face in the future.
Our comprehensive data collection spans client performance metrics, memory consumption patterns, disk I/O bottlenecks, network propagation delays, and synchronization times. We track how different client implementations (Geth, Nethermind, Besu, Erigon, Reth) behave under identical extreme conditions, identifying implementation-specific optimizations and vulnerabilities.
This data becomes invaluable for client teams optimizing their implementations, researchers modeling network behavior, and protocol developers designing future upgrades. The extreme conditions we test today help prepare Ethereum for the demanding applications of tomorrow - from high-frequency DeFi to massive on-chain gaming ecosystems.
Understand when and how clients will struggle with state growth
EIP-7938 proposes a methodical approach to increasing Ethereum's gas limits over time, enabling higher throughput while maintaining network stability. However, implementing this requires deep understanding of how each increment affects network performance and what safety mechanisms need to be in place.
When do clients start experiencing sync failures? At what state size do hardware requirements become prohibitive for home validators? How do different attack vectors scale with increased throughput? Bloatnet provides empirical answers to these questions through controlled experimentation rather than theoretical modeling.
Our findings directly shape the implementation timeline and safety measures for EIP-7938. By identifying specific client vulnerabilities and performance cliffs, we help establish safe increment schedules, necessary client optimizations, and early warning systems. This ensures that when mainnet gas limits increase, the network remains robust and accessible.
Success here means Ethereum can scale sustainably without compromising decentralization. We're not just increasing numbers - we're charting a careful path toward higher throughput that preserves Ethereum's core values while meeting growing demand from users and applications worldwide.
Identified critical bottlenecks in state access patterns when approaching 650GB threshold.
Direct correlation between state size and sync time degradation observed. Network participants experience longer initial sync times and increased hardware requirements.
Implement state pruning mechanisms and optimize memory management strategies before reaching 1TB threshold.
Additional research findings will appear here as we progress through larger state sizes.
Dive into critical data and attack vector analysis for Ethereum's scaling future
