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面向物联网的群组与赞助为中心的绿色覆盖模型

Grouping and Sponsoring Centric Green Coverage Model for Internet of Things.

机构信息

School of Computer and Systems Sciences, Jawaharlal Nehru University (JNU), New Delhi 110067, India.

Computer Science Department, Faculty of Information Technology, Al al-Bayt University, Mafraq 25113, Jordan.

出版信息

Sensors (Basel). 2021 Jun 8;21(12):3948. doi: 10.3390/s21123948.

Abstract

Recently, green computing has received significant attention for Internet of Things (IoT) environments due to the growing computing demands under tiny sensor enabled smart services. The related literature on green computing majorly focuses on a cover set approach that works efficiently for target coverage, but it is not applicable in case of area coverage. In this paper, we present a new variant of a cover set approach called a grouping and sponsoring aware IoT framework (GS-IoT) that is suitable for area coverage. We achieve non-overlapping coverage for an entire sensing region employing sectorial sensing. Non-overlapping coverage not only guarantees a sufficiently good coverage in case of large number of sensors deployed randomly, but also maximizes the life span of the whole network with appropriate scheduling of sensors. A deployment model for distribution of sensors is developed to ensure a minimum threshold density of sensors in the sensing region. In particular, a fast converging grouping (FCG) algorithm is developed to group sensors in order to ensure minimal overlapping. A sponsoring aware sectorial coverage (SSC) algorithm is developed to set off redundant sensors and to balance the overall network energy consumption. GS-IoT framework effectively combines both the algorithms for smart services. The simulation experimental results attest to the benefit of the proposed framework as compared to the state-of-the-art techniques in terms of various metrics for smart IoT environments including rate of overlapping, response time, coverage, active sensors, and life span of the overall network.

摘要

近年来,由于物联网 (IoT) 环境下智能服务对计算能力的需求不断增长,绿色计算受到了广泛关注。关于绿色计算的相关文献主要集中在覆盖集方法上,该方法在目标覆盖方面效率很高,但在区域覆盖方面不适用。在本文中,我们提出了一种新的覆盖集方法,称为分组和赞助感知的物联网框架 (GS-IoT),它适用于区域覆盖。我们采用扇形感知来实现整个感知区域的非重叠覆盖。非重叠覆盖不仅保证了在大量随机部署的传感器的情况下具有足够好的覆盖范围,而且通过适当的传感器调度来最大化整个网络的寿命。我们开发了一种传感器分布的部署模型,以确保在感知区域中具有最小的传感器密度阈值。特别是,我们开发了一种快速收敛分组 (FCG) 算法来对传感器进行分组,以确保最小重叠。我们还开发了一种感知扇形覆盖 (SSC) 算法来关闭冗余传感器并平衡整个网络的能量消耗。GS-IoT 框架有效地将这两种算法结合在一起,为智能服务提供支持。与现有的最先进技术相比,仿真实验结果证明了该框架在智能物联网环境的各种指标方面的优势,包括重叠率、响应时间、覆盖范围、活动传感器以及整个网络的寿命。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20db/8226805/009bcdd601de/sensors-21-03948-g001.jpg

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