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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.04193 |
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| _version_ | 1866917946990788608 |
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| author | Sedlak, Boris Morichetta, Andrea Raith, Philipp Pujol, Víctor Casamayor Dustdar, Schahram |
| author_facet | Sedlak, Boris Morichetta, Andrea Raith, Philipp Pujol, Víctor Casamayor Dustdar, Schahram |
| contents | This paper proposes a hierarchical solution to scale streaming services across quality and resource dimensions. Modern scenarios, like smart cities, heavily rely on the continuous processing of IoT data to provide real-time services and meet application targets (Service Level Objectives -- SLOs). While the tendency is to process data at nearby Edge devices, this creates a bottleneck because resources can only be provisioned up to a limited capacity. To improve elasticity in Edge environments, we propose to scale services in multiple dimensions -- either resources or, alternatively, the service quality. We rely on a two-layer architecture where (1) local, service-specific agents ensure SLO fulfillment through multi-dimensional elasticity strategies; if no more resources can be allocated, (2) a higher-level agent optimizes global SLO fulfillment by swapping resources. The experimental results show promising outcomes, outperforming regular vertical autoscalers, when operating under tight resource constraints. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_04193 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Multi-dimensional Elasticity for Pervasive Stream Processing Services Sedlak, Boris Morichetta, Andrea Raith, Philipp Pujol, Víctor Casamayor Dustdar, Schahram Performance This paper proposes a hierarchical solution to scale streaming services across quality and resource dimensions. Modern scenarios, like smart cities, heavily rely on the continuous processing of IoT data to provide real-time services and meet application targets (Service Level Objectives -- SLOs). While the tendency is to process data at nearby Edge devices, this creates a bottleneck because resources can only be provisioned up to a limited capacity. To improve elasticity in Edge environments, we propose to scale services in multiple dimensions -- either resources or, alternatively, the service quality. We rely on a two-layer architecture where (1) local, service-specific agents ensure SLO fulfillment through multi-dimensional elasticity strategies; if no more resources can be allocated, (2) a higher-level agent optimizes global SLO fulfillment by swapping resources. The experimental results show promising outcomes, outperforming regular vertical autoscalers, when operating under tight resource constraints. |
| title | Towards Multi-dimensional Elasticity for Pervasive Stream Processing Services |
| topic | Performance |
| url | https://arxiv.org/abs/2503.04193 |