Invited: Context-aware energy-efficient communication for IoT sensor nodes
Invited: Context-aware energy-efficient communication for IoT sensor nodes
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受邀：物联网传感器节点的上下文感知节能通信
DOI：
10.1145/2897937.2905005
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Shreyas Sen
中科院分区：
文献类型：
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作者：
Shreyas Sen
物联网（IoT）时代传感器节点的广泛扩散，加上传感器保真度和数据采集方式的提高，预计到2020年每月将产生30+ eb的数据。在这个数据驱动的物联网世界中，无线通信是一个重要的能源消耗者，仔细注意本地和远程计算之间的平衡对整体能源使用至关重要。处理大量物联网工作负载的通信结构需要在不断变化的环境下保持节能，例如信道条件、应用程序、QoS、数据速率要求等。此外，物联网设备通常包括多个并行通信结构；例如有线、近距离、毫米波、5G等。我们将讨论自我学习如何在这种通信系统中实现上下文感知操作，从而为任何给定的通信场景提供最小的能量/比特和能量/信息。在未来的物联网工作负载中，对多个物理层（物理层）内部和之间的上下文感知操作的需求将得到强调。这种节能通信（香农定律）和低功耗计算（摩尔定律）有望利用物联网革命的真正潜力，并产生巨大的社会影响。
The widespread proliferation of sensor nodes in the era of Internet of Things (IoT) coupled with increasing sensor fidelity and data-acquisition modality is expected to generate 30+ Exabytes of data per month by 2020. In this data driven IoT world, wireless communication is a significant consumer of energy, and paying careful attention to the balance between local and remote computation is critical to overall energy usage. The communication fabrics that will handle this enormous amount of IoT workload will need to be energy-efficient under changing contexts such as channel conditions, applications, QoS, data-rate requirements etc. Moreover, the IoT devices will often include multiple parallel communication fabrics; e.g. wired, proximity, mm-wave, 5G etc. We will discuss how self-learning can enable context-aware operation in such communication systems to allow minimum energy/bit and energy/information for any given communication scenario. The need for context-aware operation within and among multiple physical layers (PHYs) in future IoT workloads will be highlighted. Such energy-efficient communication (Shannon's Law) along with low-power computing (Moore's Law), is expected to harness the true potential of the IoT revolution and produce dramatic societal impact.