On the Efficiency of Dynamic Transaction Scheduling in Blockchain Sharding
Fuente:
arXiv
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866911103329501184 |
|---|---|
| author | Adhikari, Ramesh Busch, Costas Popovic, Miroslav |
| author_facet | Adhikari, Ramesh Busch, Costas Popovic, Miroslav |
| contents | Sharding is a technique to speed up transaction processing in blockchains, where the $n$ processing nodes in the blockchain are divided into $s$ disjoint groups (shards) that can process transactions in parallel. We study dynamic scheduling problems on a shard graph $G_s$ where transactions arrive online over time and are not known in advance. Each transaction may access at most $k$ shards, and we denote by $d$ the worst distance between a transaction and its accessing (destination) shards (the parameter $d$ is unknown to the shards). To handle different values of $d$, we assume a locality sensitive decomposition of $G_s$ into clusters of shards, where every cluster has a leader shard that schedules transactions for the cluster. We first examine the simpler case of the stateless model, where leaders are not aware of the current state of the transaction accounts, and we prove a $O(d \log^2 s \cdot \min\{k, \sqrt{s}\})$ competitive ratio for latency. We then consider the stateful model, where leader shards gather the current state of accounts, and we prove a $O(\log s\cdot \min\{k, \sqrt{s}\}+\log^2 s)$ competitive ratio for latency. Each leader calculates the schedule in polynomial time for each transaction that it processes. We show that for any $ε> 0$, approximating the optimal schedule within a $(\min\{k, \sqrt{s}\})^{1 -ε}$ factor is NP-hard. Hence, our bound for the stateful model is within a poly-log factor from the best possibly achievable. To the best of our knowledge, this is the first work to establish provably efficient dynamic scheduling algorithms for blockchain sharding systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_07472 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On the Efficiency of Dynamic Transaction Scheduling in Blockchain Sharding Adhikari, Ramesh Busch, Costas Popovic, Miroslav Distributed, Parallel, and Cluster Computing Sharding is a technique to speed up transaction processing in blockchains, where the $n$ processing nodes in the blockchain are divided into $s$ disjoint groups (shards) that can process transactions in parallel. We study dynamic scheduling problems on a shard graph $G_s$ where transactions arrive online over time and are not known in advance. Each transaction may access at most $k$ shards, and we denote by $d$ the worst distance between a transaction and its accessing (destination) shards (the parameter $d$ is unknown to the shards). To handle different values of $d$, we assume a locality sensitive decomposition of $G_s$ into clusters of shards, where every cluster has a leader shard that schedules transactions for the cluster. We first examine the simpler case of the stateless model, where leaders are not aware of the current state of the transaction accounts, and we prove a $O(d \log^2 s \cdot \min\{k, \sqrt{s}\})$ competitive ratio for latency. We then consider the stateful model, where leader shards gather the current state of accounts, and we prove a $O(\log s\cdot \min\{k, \sqrt{s}\}+\log^2 s)$ competitive ratio for latency. Each leader calculates the schedule in polynomial time for each transaction that it processes. We show that for any $ε> 0$, approximating the optimal schedule within a $(\min\{k, \sqrt{s}\})^{1 -ε}$ factor is NP-hard. Hence, our bound for the stateful model is within a poly-log factor from the best possibly achievable. To the best of our knowledge, this is the first work to establish provably efficient dynamic scheduling algorithms for blockchain sharding systems. |
| title | On the Efficiency of Dynamic Transaction Scheduling in Blockchain Sharding |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2508.07472 |