{"ID":2892439,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.16014","arxiv_id":"2507.16014","title":"Byzantine-Resilient Distributed Computation via Task Replication and Local Computations","abstract":"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.","short_abstract":"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 replicati...","url_abs":"https://arxiv.org/abs/2507.16014","url_pdf":"https://arxiv.org/pdf/2507.16014v1","authors":"[\"Aayush Rajesh\",\"Nikhil Karamchandani\",\"Vinod M. Prabhakaran\"]","published":"2025-07-21T19:25:24Z","proceeding":"cs.IT","tasks":"[\"cs.IT\",\"cs.DC\"]","methods":"[]","has_code":false}