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This paper considers the single source shortest path (SSSP) problem, which is the key for many applications such as navigation, mapping, routing, and social networking. Existing SSSP algorithms are designed mostly for shared-memory systems. Nevertheless, with the prevalence of diverse smart devices like drones, there is a growing interest in deploying SSSP algorithms over distributed computing systems so that they can run efficiently onboard of smart devices via Mobile Ad Hoc Computing or at the network edges via Mobile Edge Computing. In this paper, we introduce a communication-efficient ∆-stepping algorithm for distributed computing systems. The proposed algorithm is featured by 1) a message coordination architecture for reducing message exchanges between workers, 2) a pruning technique for reducing redundant computations, and 3) an aggregation technique for further reducing message exchanges when communication delay is significant. Theoretical analyses and experimental studies on real-world graph datasets demonstrate the promising performance of proposed algorithm.
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Leveraging RF Power for Intelligent Tag Networks
A novel framework and related methodologies are described to leverage RF power for building intelligent and battery-free devices with communication and computation capabilities. These passive devices are envisioned to make significant impact for the popular vision of smart dust due to extreme low power operation. The communication framework relies on tag-to-tag backscattering with very limited energy resources. The computing framework relies on a novel AC computing methodology that facilitates local data processing with an order of magnitude less power consumption. These enabling technologies, as described in this paper, revitalize the concept of smart dust with significant impact on various application domains such as smart spaces, implantable devices, and environmental/structural monitoring.
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- Award ID(s):
- 1646318
- PAR ID:
- 10073298
- Date Published:
- Journal Name:
- Proceedings of the Great Lakes Symposium on VLSI
- Page Range / eLocation ID:
- 329 to 334
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3194554.3194621
