The Tradeoff Between Coverage and Computation in Wireless Networks
The Tradeoff Between Coverage and Computation in Wireless Networks
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DOI：
10.1109/icc40277.2020.9148830
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
Erdem Koyuncu
中科院分区：
文献类型：
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作者：
Erdem Koyuncu
我们考虑一个分布式边缘计算的情况下，由几个无线节点，位于感兴趣的区域。具体地，一些“主”节点的任务是感测环境（例如，通过经由摄像机获取图像或视频）并处理相应的传感数据，而其他节点被分配为“工作者”以帮助主节点的计算密集型处理任务。一个新的权衡，以前没有在现有的文献中探索出现在这样的配方：一方面，希望分配尽可能多的主节点，以覆盖大面积的准确监测。另一方面，人们也希望分配尽可能多的工作节点，以最大化感测数据的计算速率。正是在这种权衡的背景下，这项工作提出。通过利用无线通信系统的基本物理层原理，我们制定和分析空间网络的覆盖和计算性能之间的权衡。我们还提出了一个算法，找到最佳的权衡，并通过数值模拟证明其性能。
We consider a distributed edge computing scenario consisting of several wireless nodes that are located over an area of interest. Specifically, some of the “master” nodes are tasked to sense the environment (e.g., by acquiring images or videos via cameras) and process the corresponding sensory data, while the other nodes are assigned as “workers” to help the computationally-intensive processing tasks of the masters. A new tradeoff that has not been previously explored in the existing literature arises in such a formulation: On one hand, one wishes to allocate as many master nodes as possible to cover a large area for accurate monitoring. On the other hand, one also wishes to allocate as many worker nodes as possible to maximize the computation rate of the sensed data. It is in the context of this tradeoff that this work is presented. By utilizing the basic physical layer principles of wireless communication systems, we formulate and analyze the tradeoff between the coverage and computation performance of spatial networks. We also present an algorithm to find the optimal tradeoff and demonstrate its performance through numerical simulations.