Skip to Main content Skip to Navigation
Conference papers

A Data Stream Processing Optimisation Framework for Edge Computing Applications

Abstract : Data Stream Processing (DSP) is a widely used programming paradigm to process an unbounded event stream. Often, DSP frameworks are deployed on the cloud with a scalable resource model. One of the key requirements of DSP is to produce results with low latency. With the emergence of IoT, many event sources have been located outside the cloud which can result in higher end-to-end latency due to communication overhead. However, due to the abundance of resources at the IoT layer, Edge computing has emerged as a viable computational paradigm. In this paper, we devise an optimisation framework, consisting of a constraint satisfaction formulation and a system model, that aims to minimise end-to-end latency through appropriate placement of DSP operators either on cloud nodes or edge devices, i.e. deployed in an edge-cloud integrated environment. We test our optimisation framework using OMNeT++, with realistic topologies and power consumption data, and show that it is capable of achieving ≈ 1.65 times reduction of latency compared to edge-only and cloud-only placements, which in turn also reduces the energy consumption per event by up to ≈ 4% at the edge layer. To the best of our knowledge our optimisation framework is the first of its kind to integrate power, bandwidth and CPU constraints with latency minimisation.
Document type :
Conference papers
Complete list of metadatas

Cited literature [24 references]  Display  Hide  Download

https://hal.inria.fr/hal-01862063
Contributor : Marcos Dias de Assuncao <>
Submitted on : Sunday, August 26, 2018 - 7:51:16 PM
Last modification on : Wednesday, November 20, 2019 - 2:52:38 AM
Document(s) archivé(s) le : Tuesday, November 27, 2018 - 12:42:12 PM

File

isorc2018.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Gayashan Amarasinghe, Marcos Dias de Assuncao, Aaron Harwood, Shanika Karunasekera. A Data Stream Processing Optimisation Framework for Edge Computing Applications. ISORC 2018 - IEEE 21st International Symposium on Real-Time Distributed Computing, May 2018, Singapore, Singapore. pp.91-98, ⟨10.1109/ISORC.2018.00020⟩. ⟨hal-01862063⟩

Share

Metrics

Record views

127

Files downloads

363