Edge Computing in Network-based Systems: Enhancing Latency-Sensitive Applications

Relocating data storage and processing to the network’s periphery has revolutionized latency-sensitive applications with edge computing. This study examines how edge computing may boost network-based application performance. For applications with severe latency requirements, we explore how system loads, resource allocation mechanisms, and bandwidth limits across edges affect application response times. We introduce the Enhanced Capacity Edge Cloud Network (ECON) and compare it to a baseline scenario to evaluate its efficacy in different network scenarios. To optimize resource allocation for latency-sensitive applications, we mathematically describe and simulate a city-scale hybrid edge cloud system’s capacity. The study’s results may help build and implement edge computing technologies to enhance real-world application performance.

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/ic3i61595.2024.10828607
Citations
4
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
1.40
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article

Edge Computing in Network-based Systems: Enhancing Latency-Sensitive Applications

Anuj Tyagi, Doddavarapu Sreenu Babu, Siddini Venkatesh Prabhu, A. Roniboss et al.
4 citations
IoT and Edge/Fog Computing
1.40
article

Edge Computing in Network-based Systems: Enhancing Latency-Sensitive Applications

Anuj Tyagi, Doddavarapu Sreenu Babu, Siddini Venkatesh Prabhu, A. Roniboss, K. Rajchandar, Maneesha Vinodini Ramesh
article en
4 citations

Abstract

Relocating data storage and processing to the network’s periphery has revolutionized latency-sensitive applications with edge computing. This study examines how edge computing may boost network-based application performance. For applications with severe latency requirements, we explore how system loads, resource allocation mechanisms, and bandwidth limits across edges affect application response times. We introduce the Enhanced Capacity Edge Cloud Network (ECON) and compare it to a baseline scenario to evaluate its efficacy in different network scenarios. To optimize resource allocation for latency-sensitive applications, we mathematically describe and simulate a city-scale hybrid edge cloud system’s capacity. The study’s results may help build and implement edge computing technologies to enhance real-world application performance.

Boston University (US), Northeastern University (US), Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), Ion Exchange (India) (IN), Karpagam Academy of Higher Education (IN)
Openalex Percentile: Top 16%
IoT and Edge/Fog Computing
1.40
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Edge Computing in Network-based Systems: Enhancing Latency-Sensitive Applications — Anuj Tyagi, Doddavarapu Sreenu Babu, et al. · (2024) | TGRS Research Map | TGRS