JOURNAL ARTICLE

Auto-scaling Applications in Edge Computing

Abstract

<p>The perspective of online services such as Internet of Things (IoT) applications has impressively evolved over the last recent years as they are becoming more and more time-sensitive, maintained at decentralized locations and easily affected by the changing workload intensity at runtime. As a consequence, an up-and-coming trend has been emerging from previously centralized computation to distributed edge computing in order to address these new concerns. The goal of the present paper is therefore twofold. At first, to analyze modern types of edge computing applications and their auto-scaling challenges to offer desirable performance in conditions where the workload dynamically changes. Secondly, to present a new taxonomy of auto-scaling applications. This taxonomy thoroughly considers edge computing paradigm and its complementary technologies such as container-based visualization.</p>

Keywords:
Computer science Edge computing Workload Container (type theory) Enhanced Data Rates for GSM Evolution Distributed computing Visualization Scaling Taxonomy (biology) The Internet Data science Edge device Cloud computing World Wide Web Telecommunications Operating system Artificial intelligence Engineering

Metrics

24
Cited By
2.80
FWCI (Field Weighted Citation Impact)
15
Refs
0.92
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications

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Correction to: AMAS: Adaptive auto-scaling for edge computing applications

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