Ayoub, Fatima and Villing, Rudi
(2023)
Evaluating Distributed Computation Offloading Scalability for Multiple Robots.
In: 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), 2023, Tartu, Estonia.
Abstract
Perception in robotics using modern deep learning approaches is often computationally expensive. Cloud robotics and edge robotics provide possible solutions to this. In particular, computation offloading permits compute-constrained robots to offload compute tasks from the robot itself to more capable servers (the remote brain). However, the scalability of computation offloading for robots sharing a WiFi network has typically not been considered. In this work, we investigated the scalability of offloading to the cloud and edge for deployments of multiple robots in real-world settings and network conditions. We interpret typical network performance metrics such as latency, throughput, and packet loss in terms of their effect on robot computations to help to understand this question. To characterize the problem further, we introduce three different static offloading profiles based on the sensing capabilities of currently available robot platforms and examined these in a number of experiments on both simulated and physical wireless networks. Our results show that WiFi network capacity is much less than advertised when subjected to offloading data traffic and indicates limitations on the number of robots that can concurrently use computation offloading in a given space and the amount of data that they can transfer. This has significant implications for the dense deployment of robots that depend on computation offloading to meet their required service level.
| Item Type: |
Conference or Workshop Item
(Paper)
|
| Keywords: |
Wireless sensor networks;
Scalability;
Wireless networks;
Packet loss;
Quality of service;
Robot sensing systems;
Throughput; |
| Academic Unit: |
Faculty of Science and Engineering > Electronic Engineering |
| Item ID: |
18049 |
| Depositing User: |
Rudi Villing
|
| Date Deposited: |
22 Jan 2024 14:56 |
| Publisher: |
IEEE |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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