Performance Engineering in Cloud Computing

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Systems".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 329

Special Issue Editor


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Guest Editor
Computer Science Department, Universitat de les Illes Balears, 07022 Palma de Mallorca, Spain
Interests: performance engineering; wirtualization; cloud computing; energy efficiency

Special Issue Information

Dear Colleagues,

Performance in cloud systems is a key factor in ensuring the efficiency and availability of digital services. It refers to the responsiveness, processing speed, and scalability of resources in distributed environments. Optimizing cloud performance depends on several factors, such as network architecture, workload management, and operating systems in server configuration.

Performance issues in cloud systems can impact the availability, speed, and efficiency of digital services. Key challenges include latency, network congestion, inefficient resource usage, and performance variability due to virtualization and infrastructure sharing.

To mitigate these issues, strategies such as code optimization, efficient load distribution, caching, and continuous monitoring must be implemented. Still, planning and constant tuning are essential to ensure stable cloud performance.

This Special Issue aims to cover topics related to performance in cloud systems, as well as their improvements, optimizations, load balancing, new metrics, as well as performance evaluation in cloud systems.

Dr. Belén Bermejo
Guest Editor

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Keywords

  • performance
  • system performance
  • metrics
  • performance evaluation
  • workload

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Published Papers (1 paper)

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Research

14 pages, 2383 KiB  
Article
Performance Variability in Public Clouds: An Empirical Assessment
by Sanjay Ahuja, Victor H. Lopez Chalacan and Hugo Resendez
Information 2025, 16(5), 402; https://doi.org/10.3390/info16050402 - 14 May 2025
Viewed by 154
Abstract
Cloud computing is now established as a viable alternative to on-premise infrastructure from both a system administration and cost perspective. This research provides insight into cluster computing performance and variability in cloud-provisioned infrastructure from two popular public cloud providers, Amazon Web Services (AWS) [...] Read more.
Cloud computing is now established as a viable alternative to on-premise infrastructure from both a system administration and cost perspective. This research provides insight into cluster computing performance and variability in cloud-provisioned infrastructure from two popular public cloud providers, Amazon Web Services (AWS) and Google Cloud Platform (GCP). In order to evaluate the perforance variability between these two providers, synthetic benchmarks including Memory bandwidth (STREAM), Interleave or Random (IoR) performance, and Computational CPU performance by NAS Parallel Benchmarks-Embarrassingly Parallel (NPB-EP) were used. A comparative examination of the two cloud platforms is provided in the context of our research methodology and design. We conclude with a discussion of the results of the experiment and an assessment of the suitability of public cloud platforms for certain types of computing workloads. Both AWS and GCP have their strong points, and this study provides recommendations depending on user needs for high throughput and/or performance predictability across CPU, memory, and Input/Output (I/O). In addition, the study discusses other factors to help users decide between cloud vendors such as ease of use, documentation, and types of instances offered. Full article
(This article belongs to the Special Issue Performance Engineering in Cloud Computing)
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