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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.20974 |
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Table of Contents:
- Peer-to-peer networks, as a key enabler of modern networked and distributed systems, rely on peer-selection algorithms to optimize their scalability and performance. Peer-selection methods have been studied extensively in various aspects, including routing mechanisms and communication overhead. However, many state-of-the-art algorithms are oblivious to application-specific data traffic. This mismatch between design and demand results in underutilized connections, which inevitably leads to longer paths and increased latency. In this work, we propose a novel demand-aware peer-selection algorithm, called Binary Search in Buckets (BSB). Our demand-aware approach adheres to a local and greedy XOR-based routing mechanism, ensuring compatibility with existing protocols and mechanisms. We evaluate our solution against two prior algorithms by conducting simulations on real-world and synthetic communication network traces. The results of our evaluations show that BSB can offer up to a 43% improvement compared to two selected algorithms from the literature.