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End-to-end energy models for Edge Cloud-based IoT platforms: Application to data stream analysis in IoT

机译:基于边缘云的物联网平台的端到端能源模型:在物联网数据流分析中的应用

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Internet of Things (IoT) is bringing an increasing number of connected devices that have a direct impact on the growth of data and energy-hungry services. These services are relying on Cloud infrastructures for storage and computing capabilities, transforming their architecture into more a distributed one based on edge facilities provided by Internet Service Providers (ISP). Yet, between the IoT device, communication network and Cloud infrastructure, it is unclear which part is the largest in terms of energy consumption. In this paper, we provide end-to-end energy models for Edge Cloud-based IoT platforms. These models are applied to a concrete scenario: data stream analysis produced by cameras embedded on vehicles. The validation combines measurements on real test-beds running the targeted application and simulations on well-known simulators for studying the scaling-up with an increasing number of IoT devices. Our results show that, for our scenario, the edge Cloud part embedding the computing resources consumes 3 times more than the loT part comprising the loT devices and the wireless access point. (C) 2017 Elsevier B.V. All rights reserved.
机译:物联网(IoT)带来了越来越多的互联设备,这些设备直接影响数据和耗能服务的增长。这些服务依赖于云基础架构来实现存储和计算功能,并根据Internet服务提供商(ISP)提供的边缘设施将其架构转变为分布式的架构。然而,在物联网设备,通信网络和云基础设施之间,尚不清楚哪一部分在能耗方面最大。在本文中,我们提供了基于边缘云的物联网平台的端到端能源模型。这些模型适用于具体场景:由嵌入在车辆中的摄像机生成的数据流分析。该验证将运行目标应用程序的真实测试台上的测量结果与知名仿真器上的仿真结果进行了结合,以研究随着越来越多的IoT设备而扩大规模。我们的结果表明,对于我们的方案,嵌入计算资源的边缘云部分的功耗是构成loT设备和无线接入点的loT部分的三倍。 (C)2017 Elsevier B.V.保留所有权利。

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