Abstract
Microservices are a way of splitting the logic of an application into small blocks that can be run on different computing units and used by other applications. It has been successful for cloud applications and is now increasingly used for edge applications. This new architecture brings many benefits but it makes deciding where a given service request should be executed (i.e. its placement) more complex as every small block needed for the request has to be placed. In this paper, we investigate energy-centric request placement for services that use the microservice architecture, and specifically whether using different energy metrics for optimization leads to different placement strategies. We consider the problem as an instance of a traveling purchaser problem and propose an integer linear programming formulation. This formulation aims at minimizing energy consumption while respecting latency requirements. We consider two different energy consumption metrics, namely overall or marginal energy, when applied as a measure to determine a placement. Our simulations show that using different energy metrics indeed results in different request placements.
| Original language | English |
|---|---|
| Title of host publication | ICPE '25 |
| Subtitle of host publication | Proceedings of the 16th ACM/SPEC International Conference on Performance Engineering |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 347-354 |
| Number of pages | 8 |
| ISBN (Electronic) | 9798400710735 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 16th ACM/SPEC International Conference on Performance, ICPE 2025 - Toronto, Canada Duration: 5 May 2025 → 9 May 2025 |
Conference
| Conference | 16th ACM/SPEC International Conference on Performance, ICPE 2025 |
|---|---|
| Country/Territory | Canada |
| City | Toronto |
| Period | 5/05/25 → 9/05/25 |
Bibliographical note
Publisher Copyright:© 2025 Copyright held by the owner/author(s).
Funding
This work is supported by the Swedish national graduate school in computer science (CUGS). The second author was supported by ELLIIT, Excellence Center at Link\u00F6ping-Lund on Information Technology.
| Funders |
|---|
| National Graduate School in Computer Science |
| Excellence Center at Linköping – Lund in Information Technology |
Keywords
- edge/fog computing
- energy metrics
- optimization
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