Symbiotic Robotics Network for Efficient Task Offloading in Smart Industry
| Autor: | Muhammad Ali, Asad Waqar Malik, Anis Rahman, Max Mauro Dias Santos |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science Distributed computing 020208 electrical & electronic engineering Network delay Cloud computing Robotics Workload 02 engineering and technology Computer Science Applications Task (project management) Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering Task analysis Robot Resource management Artificial intelligence Electrical and Electronic Engineering business Information Systems |
| Zdroj: | IEEE Transactions on Industrial Informatics. 17:4594-4601 |
| ISSN: | 1941-0050 1551-3203 |
| Popis: | Collaborative robots are an emerging area where robots share resources among each other for mutual benefit. They are particularly becoming popular in a modern industrial environment, primarily to improve production efficiency. This often involves some sort of decision making at the robots. Traditionally, the robots are connected to the cloud infrastructure and edge locations to offload compute-intensive tasks. But due to the dynamic workload generated and additional network delay, cloud, and edge locations are deemed unsuitable computing paradigms for use in industrial robots. In this article, we propose a symbiotic robotics framework where robots share their onboard computing capabilities for effective task offloading and its execution. Furthermore, the underlying symbiotic paradigm incorporates the concept of repute based on every successful task offloading and execution. The experimental results demonstrate a significant performance gain in terms of offloading time, task completion time, and overall efficiency when compared to two classical task offloading schemes. |
| Databáze: | OpenAIRE |
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