Mind the Gap: Autonomous Detection of Partitioned MANET Systems using Opportunistic Aggregation
(2018) 2018 IEEE 37th Symposium on Reliable Distributed Systems (SRDS) — Location: Salvador, Brazil (2.October.2018)
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- Abstract
- Mobile Ad-hoc Networks (MANETs) use limited- range wireless communications and are thus exposed to partitions when nodes fail or move out of reach of each other. Detecting partitions in MANETs is unfortunately a nontrivial task due to their inherently decentralized design and limited resources such as power or bandwidth. In this paper, we propose a novel and fully decentralized approach to detect partitions (and other large membership changes) in MANETs that is both accurate and resource efficient. We monitor the current composition of a MANET using the lightweight aggregation of compact membership-encoding filters. Changes in these filters allow us to infer the likelihood of a partition with a quantifiable level of confidence. We first present an analysis of our approach, and show that it can detect close to 100% of partitions under realistic settings, while at the same time being robust to false positives due to churn or dropped packets. We perform a series of simulations that compare against alternative approaches and confirm our theoretical results, including above 90% accurate detection even under a 40% message loss rate.
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Citations
Simon Bouget, Yerom-David Bromberg, Hugues Mercier, Riviere, E., & Francois Taiani. (2018). Mind the Gap: Autonomous Detection of Partitioned MANET Systems using Opportunistic Aggregation. 2018 IEEE 37th Symposium on Reliable Distributed Systems (SRDS). Published. 2018 IEEE 37th Symposium on Reliable Distributed Systems (SRDS), Salvador, Brazil. https://doi.org/10.1109/srds.2018.00025