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Static Algorithm Allocation With Duplication in Robotic Network Cloud Systems
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AI
DOI：10.1109/TPDS.2023.3267293.png)
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Robotic networks can be used to accomplish tasks that exceed the capacity of a single robot. In a robotic network, robots can work together to accomplish a common task. Cloud robotics allows robots to benefit from the massive storage and computing power of the cloud. Previous studies mainly focus on minimizing the cost of resource retrieval by robots by knowing the resource allocation in advance. Duplicating algorithms on multiple nodes can reduce the total time required to execute a task. We address the question of which algorithms should be duplicated and where the duplicates should be placed to improve overall performance. We have developed a procedure to answer wherein a robotic network cloud system should algorithms be executed and whether they should be duplicated to achieve optimal performance in terms of overall task execution time for all robots. Our proposed duplication procedure is optimal in the sense that the number of duplicated algorithms is minimal, while the result provides minimal overall completion time for all robots.
Keyword:
Task analysis
Robots
Resource management
Heuristic algorithms
Cloud computing
Dynamic scheduling
Service robots
Human-robot collaboration
job completion time
monitoring
quality metric
task scheduling
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6
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5.2K
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1.1W
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A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems基于分层拍卖的云机器人系统实时资源分配机制
PREAI
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