DGRO: Diameter-Guided Ring Optimization for Integrated Research Infrastructure Membership
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866929543188578304 |
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| author | Wu, Shixun Raghavan, Krishnan Di, Sheng Chen, Zizhong Cappello, Franck |
| author_facet | Wu, Shixun Raghavan, Krishnan Di, Sheng Chen, Zizhong Cappello, Franck |
| contents | Logical ring is a core component in membership protocol. However, the logic ring fails to consider the underlying physical latency, resulting in a high diameter. To address this issue, we introduce Diameter-Guided Ring Optimization (DGRO), which focuses on constructing rings with the smallest possible diameter, selecting the most effective ring configurations, and implementing these configurations in parallel. We first explore an integration of deep Q-learning and graph embedding to optimize the ring topology. We next propose a ring selection strategy that assesses the current topology's average latency against a global benchmark, facilitating integration into modern peer-to-peer protocols and substantially reducing network diameter. To further enhance scalability, we propose a parallel strategy that distributes the topology construction process into separate partitions simultaneously. Our experiment shows that: 1) DGRO efficiently constructs a network topology that achieves up to a 60% reduction in diameter compared to the best results from an extensive search over $10^5$ topologies, all within a significantly shorter computation time, 2) the ring selection of DGRO reduces the diameter of state-of-the-art methods Chord, RAPID, and Perigee by 10%-40%, 44%, and 60%. 3) the parallel construction can scale up to $32$ partitions while maintaining the same diameter compared to the centralized version. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_11142 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | DGRO: Diameter-Guided Ring Optimization for Integrated Research Infrastructure Membership Wu, Shixun Raghavan, Krishnan Di, Sheng Chen, Zizhong Cappello, Franck Distributed, Parallel, and Cluster Computing Logical ring is a core component in membership protocol. However, the logic ring fails to consider the underlying physical latency, resulting in a high diameter. To address this issue, we introduce Diameter-Guided Ring Optimization (DGRO), which focuses on constructing rings with the smallest possible diameter, selecting the most effective ring configurations, and implementing these configurations in parallel. We first explore an integration of deep Q-learning and graph embedding to optimize the ring topology. We next propose a ring selection strategy that assesses the current topology's average latency against a global benchmark, facilitating integration into modern peer-to-peer protocols and substantially reducing network diameter. To further enhance scalability, we propose a parallel strategy that distributes the topology construction process into separate partitions simultaneously. Our experiment shows that: 1) DGRO efficiently constructs a network topology that achieves up to a 60% reduction in diameter compared to the best results from an extensive search over $10^5$ topologies, all within a significantly shorter computation time, 2) the ring selection of DGRO reduces the diameter of state-of-the-art methods Chord, RAPID, and Perigee by 10%-40%, 44%, and 60%. 3) the parallel construction can scale up to $32$ partitions while maintaining the same diameter compared to the centralized version. |
| title | DGRO: Diameter-Guided Ring Optimization for Integrated Research Infrastructure Membership |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2410.11142 |