Byzantine-Resilient Distributed Computation via Task Replication and Local Computations
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866916855408492544 |
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| author | Rajesh, Aayush Karamchandani, Nikhil Prabhakaran, Vinod M. |
| author_facet | Rajesh, Aayush Karamchandani, Nikhil Prabhakaran, Vinod M. |
| contents | We study a distributed computation problem in the presence of Byzantine workers where a central node wishes to solve a task that is divided into independent sub-tasks, each of which needs to be solved correctly. The distributed computation is achieved by allocating the sub-task computation across workers with replication, as well as solving a small number of sub-tasks locally, which we wish to minimize due to it being expensive. For a general balanced job allocation, we propose a protocol that successfully solves for all sub-tasks using an optimal number of local computations under no communication constraints. Closed-form performance results are presented for cyclic allocations. Furthermore, we propose a modification to this protocol to improve communication efficiency without compromising on the amount of local computation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_16014 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Byzantine-Resilient Distributed Computation via Task Replication and Local Computations Rajesh, Aayush Karamchandani, Nikhil Prabhakaran, Vinod M. Information Theory Distributed, Parallel, and Cluster Computing We study a distributed computation problem in the presence of Byzantine workers where a central node wishes to solve a task that is divided into independent sub-tasks, each of which needs to be solved correctly. The distributed computation is achieved by allocating the sub-task computation across workers with replication, as well as solving a small number of sub-tasks locally, which we wish to minimize due to it being expensive. For a general balanced job allocation, we propose a protocol that successfully solves for all sub-tasks using an optimal number of local computations under no communication constraints. Closed-form performance results are presented for cyclic allocations. Furthermore, we propose a modification to this protocol to improve communication efficiency without compromising on the amount of local computation. |
| title | Byzantine-Resilient Distributed Computation via Task Replication and Local Computations |
| topic | Information Theory Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2507.16014 |