Authors:
Vincenzo Scoca
1
;
Atakan Aral
2
;
Ivona Brandic
2
;
Rocco De Nicola
1
and
Rafael Brundo Uriarte
1
Affiliations:
1
IMT School for Advanced Studies Lucca, Italy
;
2
Vienna University of Technology, Austria
Keyword(s):
Edge Computing, Scheduling, Latency-Sensitive Services, Live Video Streaming, Resource Selection.
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 deli
very 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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