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Practical Aggregation in the Edge
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Orientador(es)
Resumo(s)
Due to the increasing amounts of data produced by applications and devices, cloud infrastructures
are becoming unable to timely process and provide answers back to users.
This has led to the emergence of the edge computing paradigm that aims at moving
computations closer to end user devices. Edge computing can be defined as performing
computations outside the boundaries of cloud data centres. This however, can be materialised
across very different scenarios considering the broad spectrum of devices that can
be leveraged to perform computations in the edge.
In this thesis, we focus on a concrete scenario of edge computing, that of multiple
devices with wireless capabilities that collectively form a wireless ad hoc network to perform
distributed computations. We aim at devising practical solutions for these scenarios
however, there is a lack of tools to help us in achieving such goal. To address this first
limitation we propose a novel framework, called Yggdrasil, that is specifically tailored to
develop and execute distributed protocols over wireless ad hoc networks on commodity
devices.
As to enable distributed computations in such networks, we focus on the particular
case of distributed data aggregation. In particular, we address a harder variant of this
problem, that we dub distributed continuous aggregation, where input values used for
the computation of the aggregation function may change over time, and propose a novel
distributed continuous aggregation protocol, called MiRAge.
We have implemented and validated both Yggdrasil and MiRAge through an extensive
experimental evaluation using a test-bed composed of 24 Raspberry Pi’s. Our results
show that Yggdrasil provides adequate abstractions and tools to implement and execute
distributed protocols in wireless ad hoc settings. Our evaluation is also composed of a
practical comparative study on distributed continuous aggregation protocols, that shows
that MiRAge is more robust and achieves more precise aggregation results than competing
state-of-the-art alternatives.
Descrição
Palavras-chave
Edge Computing Wireless Ad Hoc Networks Aggregation Frameworks