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| Content Provider | ACM Digital Library |
|---|---|
| Author | Dulman, Stefan Pauwels, Eric |
| Copyright Year | 2015 |
| Abstract | In this article, we explore the topic of extending aggregate computation in distributed networks with self-stabilizing properties to withstand network dynamics. Existing research suggests that fast gossiping algorithms, based on the properties of order statistics applied to families of exponential random variables, are a viable solution for computing functions of the values stored in the network. We focus on the specific case in which network changes and failures occur in batches with a minimum frequency in the order of the diameter of the network. Our contribution consists in two self-stabilizing mechanisms, allowing fast gossiping algorithms to be applicable to dynamic networks with minor increase in resources usage. The resulting algorithms can be deployed in networks exhibiting churn, node stop-failures and resets, and random topological changes. The theoretical results are verified with simulations on synthetic data, showcasing desirable properties for large-scale network designers such as scalability, lack of single points of failure, and anonymity. |
| Starting Page | 1 |
| Ending Page | 20 |
| Page Count | 20 |
| File Format | |
| ISSN | 15564665 |
| e-ISSN | 15564703 |
| DOI | 10.1145/2816819 |
| Volume Number | 10 |
| Issue Number | 4 |
| Journal | ACM Transactions on Autonomous and Adaptive Systems (TAAS) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-12-31 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Self-stabilization Distributed network Gossiping algorithm |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Systems Engineering Software |
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