Article: Intelligent workload optimisation based on a protocol-fused cloud robotics physical framework with integrated multi-sensors Journal: International Journal of Embedded Systems (IJES) 2025 Vol.18 No.2 pp.99 - 112 Abstract: Cloud computing significantly improves the performance of robots in data processing and storage, but still faces problems such as high computational loads and high energy requirements for local robots. To address these issues, a protocol-fused physical framework integrating multiple sensors is proposed to simplify sensoring data integration and device deployment. Cloud robotics intelligent workload optimisation has also been achieved through accurate sensoring data collection based on this framework. First, a middleware called ProtoFusion is introduced to manage the robot's local services, facilitating protocol conversion and transmission of multimodal sensory information. Next, the cloud robot's physical framework, based on ProtoFusion, enables sensing, perception, and control. Finally, ProtoFusion's task division (e.g., receiving, sending, and controlling) is scheduled using uC/OS-III, optimising system resource utilisation. The effectiveness of the optimisation is verified experimentally. Resource efficiency was improved, energy consumption was reduced and system reliability was enhanced. Inderscience Publishers - linking academia, business and industry through research

Title: Intelligent workload optimisation based on a protocol-fused cloud robotics physical framework with integrated multi-sensors

Authors: Songshuang Li; Shengyu Zhu; Kui Qian; Nannan Dong

Addresses: School of Automation, Nanjing Institute of Technology, Nanjing 211167, Jiangsu, China ' School of Automation, Nanjing Institute of Technology, Nanjing 211167, Jiangsu, China ' School of Automation, Nanjing Institute of Technology, Nanjing 211167, Jiangsu, China ' School of Automation, Nanjing Institute of Technology, Nanjing 211167, Jiangsu, China

Abstract: Cloud computing significantly improves the performance of robots in data processing and storage, but still faces problems such as high computational loads and high energy requirements for local robots. To address these issues, a protocol-fused physical framework integrating multiple sensors is proposed to simplify sensoring data integration and device deployment. Cloud robotics intelligent workload optimisation has also been achieved through accurate sensoring data collection based on this framework. First, a middleware called ProtoFusion is introduced to manage the robot's local services, facilitating protocol conversion and transmission of multimodal sensory information. Next, the cloud robot's physical framework, based on ProtoFusion, enables sensing, perception, and control. Finally, ProtoFusion's task division (e.g., receiving, sending, and controlling) is scheduled using uC/OS-III, optimising system resource utilisation. The effectiveness of the optimisation is verified experimentally. Resource efficiency was improved, energy consumption was reduced and system reliability was enhanced.

Keywords: cloud computing; ProtoFusion; data driven; robotics physical framework; intelligent workload optimisation.

DOI: 10.1504/IJES.2025.149244

International Journal of Embedded Systems, 2025 Vol.18 No.2, pp.99 - 112

Received: 04 Jul 2024
Accepted: 08 Feb 2025
Published online: 20 Oct 2025 *

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Title: Intelligent workload optimisation based on a protocol-fused cloud robotics physical framework with integrated multi-sensors

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