Introduction

The rapid adoption of Decentralized Finance (DeFi) has transformed the financial landscape, introducing innovative ways for users to lend, borrow, trade, and stake their assets in permissionless and decentralized environments. At the heart of many DeFi protocols lies staking, a mechanism that supports PoS blockchain networks by incentivizing users to lock their tokens to secure the network and validate transactions. Traditional staking, while effective, often comes with the trade-off of illiquidity—once tokens are staked, users are unable to use them in other financial operations without undergoing a lengthy unbonding period.

Liquid Staking Tokens (LSTs) address this limitation by providing a tokenized representation of staked assets, enabling users to retain liquidity while earning staking rewards. LSTs, such as stSOL and mSOL on the Solana blockchain, have become integral to DeFi ecosystems, allowing users to seamlessly integrate staking with other financial activities. Despite their advantages, the manual process of restaking rewards—where users periodically claim and reinvest their earnings—remains a bottleneck. This manual process is not only time-intensive but also costly, as it incurs gas fees for each transaction and often results in missed opportunities for compounding returns.

Problem Statement

The inefficiencies of manual restaking hinder the broader adoption and effectiveness of staking as a financial instrument. For users, the process requires regular monitoring of rewards, active management of multiple staking positions, and repeated interactions with blockchain networks. For networks, the lack of automated restaking mechanisms leads to suboptimal asset allocation, as staked tokens may not be compounded efficiently, reducing their overall contribution to network security and liquidity.

Research Objectives

This paper aims to address these challenges by exploring the potential of automated restaking mechanisms. These systems automate the process of compounding staking rewards, offering users a "set-and-forget" solution that maximizes returns and reduces operational costs. The research focuses on:

• The design and implementation of automated restaking mechanisms for LSTs.

• Mathematical modeling of the efficiency and scalability benefits of automation.

• An empirical analysis of existing automated restaking protocols in DeFi ecosystems.

• Recommendations for integrating automated restaking mechanisms into DeFi platforms, with a focus on their application within the Solana blockchain.