Proactive and Reactive Autoscaling Techniques for Edge Computing
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arXiv
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| Format: | Preprint |
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2025
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| author | Gupta, Suhrid Islam, Muhammed Tawfiqul Buyya, Rajkumar |
| author_facet | Gupta, Suhrid Islam, Muhammed Tawfiqul Buyya, Rajkumar |
| contents | Edge computing allows for the decentralization of computing resources. This decentralization is achieved through implementing microservice architectures, which require low latencies to meet stringent service level agreements (SLA) such as performance, reliability, and availability metrics. While cloud computing offers the large data storage and computation resources necessary to handle peak demands, a hybrid cloud and edge environment is required to ensure SLA compliance. Several auto-scaling algorithms have been proposed to try to achieve these compliance challenges, but they suffer from performance issues and configuration complexity. This chapter provides a brief overview of edge computing architecture, its uses, benefits, and challenges for resource scaling. We then introduce Service Level Agreements, and existing research on devising algorithms used in edge computing environments to meet these agreements, along with their benefits and drawbacks. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2510_10166 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Proactive and Reactive Autoscaling Techniques for Edge Computing Gupta, Suhrid Islam, Muhammed Tawfiqul Buyya, Rajkumar Distributed, Parallel, and Cluster Computing Edge computing allows for the decentralization of computing resources. This decentralization is achieved through implementing microservice architectures, which require low latencies to meet stringent service level agreements (SLA) such as performance, reliability, and availability metrics. While cloud computing offers the large data storage and computation resources necessary to handle peak demands, a hybrid cloud and edge environment is required to ensure SLA compliance. Several auto-scaling algorithms have been proposed to try to achieve these compliance challenges, but they suffer from performance issues and configuration complexity. This chapter provides a brief overview of edge computing architecture, its uses, benefits, and challenges for resource scaling. We then introduce Service Level Agreements, and existing research on devising algorithms used in edge computing environments to meet these agreements, along with their benefits and drawbacks. |
| title | Proactive and Reactive Autoscaling Techniques for Edge Computing |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2510.10166 |