论文标题
单个机器人云系统的最佳算法分配
Optimal Algorithm Allocation for Single Robot Cloud Systems
论文作者
论文摘要
为了使机器人执行任务，有时需要同时执行几种算法。算法可以在机器人本身上运行，也可以根据要求在云基础架构上执行。术语云基础架构用于描述与云计算有关的硬件，存储，抽象资源和网络资源。根据关于执行算法的决定的决定，机器人的总体执行时间和必要的内存空间将相应地更改。机器人的价格取决于其内存能力和计算能力。我们回答了如何通过为云基础架构分配计算任务来保持给定性能并使用更便宜的机器人（较低资源）的问题，具体取决于内存，计算能力和通信约束。同样，对于固定机器人，我们的模型提供了一种获得最佳总体性能的方法。我们为在某些约束下算法分配的最佳决策提供了一个通用模型。我们以模拟结果为模型举例说明了模型。我们模型的主要优点是它为内存和时间提供了同时提供最佳任务分配。
In order for a robot to perform a task, several algorithms need to be executed, sometimes, simultaneously. Algorithms can be run either on the robot itself or, upon request, be performed on cloud infrastructure. The term cloud infrastructure is used to describe hardware, storage, abstracted resources, and network resources related to cloud computing. Depending on the decisions on where to execute the algorithms, the overall execution time and necessary memory space for the robot will change accordingly. The price of a robot depends, among other things, on its memory capacity and computational power. We answer the question of how to keep a given performance and use a cheaper robot (lower resources) by assigning computational tasks to the cloud infrastructure, depending on memory, computational power, and communication constraints. Also, for a fixed robot, our model provides a way to have optimal overall performance. We provide a general model for the optimal decision of algorithm allocation under certain constraints. We exemplify the model with simulation results. The main advantage of our model is that it provides an optimal task allocation simultaneously for memory and time.
