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Main Authors: Augustine, John, Cruciani, Antonio, Gillani, Iqra Altaf
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2409.10235
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author Augustine, John
Cruciani, Antonio
Gillani, Iqra Altaf
author_facet Augustine, John
Cruciani, Antonio
Gillani, Iqra Altaf
contents We study robust and efficient distributed algorithms for building and maintaining distributed data structures in dynamic Peer-to-Peer (P2P) networks. P2P networks are characterized by a high level of dynamicity with abrupt heavy node \emph{churn} (nodes that join and leave the network continuously over time). We present a novel algorithm that builds and maintains with high probability a skip list for $poly(n)$ rounds despite $\mathcal{O}(n/\log n)$ churn \emph{per round} ($n$ is the stable network size). We assume that the churn is controlled by an oblivious adversary (that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm). Moreover, the maintenance overhead is proportional to the churn rate. Furthermore, the algorithm is scalable in that the messages are small (i.e., at most $polylog(n)$ bits) and every node sends and receives at most $polylog(n)$ messages per round. Our algorithm crucially relies on novel distributed and parallel algorithms to merge two $n$-elements skip lists and delete a large subset of items, both in $\mathcal{O}(\log n)$ rounds with high probability. These procedures may be of independent interest due to their elegance and potential applicability in other contexts in distributed data structures. To the best of our knowledge, our work provides the first-known fully-distributed data structure that provably works under highly dynamic settings (i.e., high churn rate). Furthermore, they are localized (i.e., do not require any global topological knowledge). Finally, we believe that our framework can be generalized to other distributed and dynamic data structures including graphs, potentially leading to stable distributed computation despite heavy churn.
format Preprint
id arxiv_https___arxiv_org_abs_2409_10235
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Highly Dynamic and Fully Distributed Data Structures
Augustine, John
Cruciani, Antonio
Gillani, Iqra Altaf
Distributed, Parallel, and Cluster Computing
We study robust and efficient distributed algorithms for building and maintaining distributed data structures in dynamic Peer-to-Peer (P2P) networks. P2P networks are characterized by a high level of dynamicity with abrupt heavy node \emph{churn} (nodes that join and leave the network continuously over time). We present a novel algorithm that builds and maintains with high probability a skip list for $poly(n)$ rounds despite $\mathcal{O}(n/\log n)$ churn \emph{per round} ($n$ is the stable network size). We assume that the churn is controlled by an oblivious adversary (that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm). Moreover, the maintenance overhead is proportional to the churn rate. Furthermore, the algorithm is scalable in that the messages are small (i.e., at most $polylog(n)$ bits) and every node sends and receives at most $polylog(n)$ messages per round. Our algorithm crucially relies on novel distributed and parallel algorithms to merge two $n$-elements skip lists and delete a large subset of items, both in $\mathcal{O}(\log n)$ rounds with high probability. These procedures may be of independent interest due to their elegance and potential applicability in other contexts in distributed data structures. To the best of our knowledge, our work provides the first-known fully-distributed data structure that provably works under highly dynamic settings (i.e., high churn rate). Furthermore, they are localized (i.e., do not require any global topological knowledge). Finally, we believe that our framework can be generalized to other distributed and dynamic data structures including graphs, potentially leading to stable distributed computation despite heavy churn.
title Highly Dynamic and Fully Distributed Data Structures
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2409.10235