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Data-Centric Distributed Computing on Networks of Mobile Devices

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Euro-Par 2020: Parallel Processing (Euro-Par 2020)

Abstract

In the last few years, we have seen a significant increase both in the number and capabilities of mobile devices, as well as in the number of applications that need more and more computing and storage resources. Currently, in order to deal with this growing need for resources, applications make use of cloud services. This raises some problems, namely high latency, considerable use of energy and bandwidth, and the unavailability of connectivity infrastructures. Given this context, for some applications it makes sense to do part, or all, of the computations locally on the mobile devices themselves. In this paper we present Oregano, a framework for distributed computing on mobile devices, capable of processing batches or streams of data generated on mobile device networks, without requiring centralized services. Contrary to current state-of-the-art, where computations and data are sent to worker mobile devices, Oregano performs computations where the data is located, significantly reducing the amount of exchanged data.

This work was supported by FCT-MCTES via project DeDuCe (PTDC/CCI-COM/32166/2017) and NOVA LINCS (UID/CEC/04516/2019).

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Correspondence to Hervé Paulino .

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Sanches, P., Silva, J.A., Teófilo, A., Paulino, H. (2020). Data-Centric Distributed Computing on Networks of Mobile Devices. In: Malawski, M., Rzadca, K. (eds) Euro-Par 2020: Parallel Processing. Euro-Par 2020. Lecture Notes in Computer Science(), vol 12247. Springer, Cham. https://doi.org/10.1007/978-3-030-57675-2_19

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  • DOI: https://doi.org/10.1007/978-3-030-57675-2_19

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