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A Vision of Fog Systems with Integrating FPGAs and BLE Mesh Network

机译:集成了FPGA和BLE Mesh网络的Fog系统的愿景

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This paper presents a novel integrated field-programmable gate arrays (FPGA) and Bluetooth Low Energy (BLE) mesh system in the field of fog computing. Combining the merits of 1) programmability of FPGAs, and 2) wide-area communication and low-energy consumption of BLE mesh technology, this platform will create a diverse range of applications such as low-latency computation at the network edge, as well as showing a demo for Internet-of-Things (IoT) connections to cover an entire building. By integrating FPGAs, more important, the fog node can offer a great potential for flexible acceleration of many workloads and improve power efficiency with more hardware parallelism than CPUs and GPUs. These advantages are going to move FPGAs into the mainstream of fog computing for the foreseeable future. The preliminary results of a BLE mesh network is demonstrated on http://sceweb.sce.uhcl.edu/xiaokun/#-> project. Generally we provide three test cases: to control the mesh network by local device, local server, and cloud server. It can be observed that the feedback control from the local device achieves the lowest latency, and the response delay from the cloud server is the highest. Therefore, it is necessary to pre-process more than 90% raw data from sensor network at the proximity of the network edge/fog, particularly with the number of IoT devices in tens of billions levels.
机译:本文介绍了雾计算领域中的新型集成现场可编程门阵列(FPGA)和低功耗蓝牙(BLE)网格系统。结合以下优点:1)FPGA的可编程性,以及2)BLE网格技术的广域通信和低能耗,该平台将创建各种应用,例如网络边缘的低延迟计算以及展示了物联网(IoT)连接覆盖整个建筑物的演示。通过集成FPGA,更重要的是,与CPU和GPU相比,雾节点具有更大的潜力,可以灵活加速许多工作负载,并通过更多的硬件并行性提高电源效率。这些优势将使FPGA在可预见的将来成为雾计算的主流。 BLE网状网络的初步结果已在http://sceweb.sce.uhcl.edu/xiaokun/#->项目中进行了演示。通常,我们提供三个测试用例:通过本地设备,本地服务器和云服务器控制网状网络。可以看到,来自本地设备的反馈控制实现了最低的延迟,而来自云服务器的响应延迟最高。因此,有必要对网络边缘/雾附近的来自传感器网络的90%以上的原始数据进行预处理,尤其是在IoT设备数量达到数百亿级的情况下。

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