SchEdge: A Dynamic, Multi-agent, and Scalable Scheduling Simulator for IoT Edge
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866915231478841344 |
|---|---|
| author | Hamedi, Ali Ghaedi, Amirali Soltanbeigi, Amin Abdi, Athena |
| author_facet | Hamedi, Ali Ghaedi, Amirali Soltanbeigi, Amin Abdi, Athena |
| contents | This paper presents a dynamic, adaptive, and scalable framework for simulating task scheduling on the edge of the Internet of Things called "SchEdge". This simulator is designed to be highly configurable to reflect the detailed characteristics of real-world IoT. This framework focuses on online task scheduling and its multi-agent nature provides multiple schedulers to implement various scheduling schemes in parallel. SchEdge consists of two main parts the workflow and data flow. The workflow manages the schedulers' interaction with the application and environment while the data flow deals with the input application and its preprocessing. Combining these sections provides scalability, adaptability, and efficiency in the SchEdge. To validate the efficiency of this simulator, several experiments categorized as behavioral and technical analysis are performed to show its efficiency, scalability, and robustness. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_04555 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SchEdge: A Dynamic, Multi-agent, and Scalable Scheduling Simulator for IoT Edge Hamedi, Ali Ghaedi, Amirali Soltanbeigi, Amin Abdi, Athena Distributed, Parallel, and Cluster Computing This paper presents a dynamic, adaptive, and scalable framework for simulating task scheduling on the edge of the Internet of Things called "SchEdge". This simulator is designed to be highly configurable to reflect the detailed characteristics of real-world IoT. This framework focuses on online task scheduling and its multi-agent nature provides multiple schedulers to implement various scheduling schemes in parallel. SchEdge consists of two main parts the workflow and data flow. The workflow manages the schedulers' interaction with the application and environment while the data flow deals with the input application and its preprocessing. Combining these sections provides scalability, adaptability, and efficiency in the SchEdge. To validate the efficiency of this simulator, several experiments categorized as behavioral and technical analysis are performed to show its efficiency, scalability, and robustness. |
| title | SchEdge: A Dynamic, Multi-agent, and Scalable Scheduling Simulator for IoT Edge |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2504.04555 |