Distributed Load Orchestration for Vision Computing in Multi-Access Edge Computing
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2022
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866910668878249984 |
|---|---|
| author | Boing, Ricardo N. Sampaio, Hugo Vaz Koch, Fernando Cruz, Rene N. S. Westphall, Carlos B. |
| author_facet | Boing, Ricardo N. Sampaio, Hugo Vaz Koch, Fernando Cruz, Rene N. S. Westphall, Carlos B. |
| contents | Multi-access Edge Computing (MEC) is a type of network architecture that provides cloud computing capabilities at the edge of the network. We consider the use case of video surveillance for an university campus running on a 5G-MEC environment. A key issue is the eventual overloading of computing resources on the MEC nodes during peak demand. We propose a new strategy for distributed orchestration in MEC environments based on how load balancing strategies organize processing queue. Then, we elaborated a strategy for deadline-aware queueing prioritization that organizes requests based on pre-established thresholds. We introduce a simulation-based experimentation environment and conduct a number of tests demonstrating the benefit of our approach by reducing the number of referrals and improving the effectiveness in meeting deadlines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2212_03802 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Distributed Load Orchestration for Vision Computing in Multi-Access Edge Computing Boing, Ricardo N. Sampaio, Hugo Vaz Koch, Fernando Cruz, Rene N. S. Westphall, Carlos B. Distributed, Parallel, and Cluster Computing Multi-access Edge Computing (MEC) is a type of network architecture that provides cloud computing capabilities at the edge of the network. We consider the use case of video surveillance for an university campus running on a 5G-MEC environment. A key issue is the eventual overloading of computing resources on the MEC nodes during peak demand. We propose a new strategy for distributed orchestration in MEC environments based on how load balancing strategies organize processing queue. Then, we elaborated a strategy for deadline-aware queueing prioritization that organizes requests based on pre-established thresholds. We introduce a simulation-based experimentation environment and conduct a number of tests demonstrating the benefit of our approach by reducing the number of referrals and improving the effectiveness in meeting deadlines. |
| title | Distributed Load Orchestration for Vision Computing in Multi-Access Edge Computing |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2212.03802 |