Scheduling Latency-Sensitive Applications in Edge Computing

Vincenzo Scoca, Atakan Aral, Ivona Brandic, Rocco De Nicola, Rafael Brundo Uriarte

Abstract

Edge computing is an emerging technology that aims to include latency-sensitive and data-intensive applications such as mobile or IoT services, into the cloud ecosystem by placing computational resources at the edge of the network. Close proximity to producers and consumers of data brings significant benefits in latency and bandwidth. However, edge resources are, by definition, limited in comparison to cloud counterparts, thus, a trade-off exists between deploying a service closest to its users and avoiding resource overload. We propose a score-based edge service scheduling algorithm that evaluates both network and computational capabilities of edge nodes and outputs the maximum scoring mapping between services and resources. Our extensive simulation based on a live video streaming service, demonstrates significant improvements in both network delay and service time. Additionally, we compare edge computing technology with the state-of-the-art cloud computing and content delivery network solutions within the context of latency-sensitive and data-intensive applications. Our results show that edge computing enhanced with suggested scheduling algorithm is a viable solution for achieving high quality of service and responsivity in deploying such applications.

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Paper Citation


in Harvard Style

Scoca V., Aral A., Brandic I., De Nicola R. and Uriarte R. (2018). Scheduling Latency-Sensitive Applications in Edge Computing.In Proceedings of the 8th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-295-0, pages 158-168. DOI: 10.5220/0006706201580168


in Bibtex Style

@conference{closer18,
author={Vincenzo Scoca and Atakan Aral and Ivona Brandic and Rocco De Nicola and Rafael Brundo Uriarte},
title={Scheduling Latency-Sensitive Applications in Edge Computing},
booktitle={Proceedings of the 8th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2018},
pages={158-168},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006706201580168},
isbn={978-989-758-295-0},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Scheduling Latency-Sensitive Applications in Edge Computing
SN - 978-989-758-295-0
AU - Scoca V.
AU - Aral A.
AU - Brandic I.
AU - De Nicola R.
AU - Uriarte R.
PY - 2018
SP - 158
EP - 168
DO - 10.5220/0006706201580168