Vehicles joint UAVs to acquire and analyze data for topology discovery in large-scale IoT systems
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Vehicles joint UAVs to acquire and analyze data for topology discovery in large-scale IoT systems Haojun Teng 1 & Kaoru Ota 2 & Anfeng Liu 1
&
Tian Wang 3 & Shaobo Zhang 4
Received: 31 August 2019 / Accepted: 16 January 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Billions of sensing devices have been connected to the Internet of Things (IoT), generating a large volume of data that can be turned into valuable insights for many applications. Location information is critical for many IoT applications. However, most sensor devices are randomly deployed and locations are unknown. Thus, it is a challenging issue to discover the physical topology of the IoT system consisted of thousands of low-cost sensor devices. In this paper, a Vehicles joint UAVs Topology Discovery (VUTD) scheme is proposed that can discover the physical topology with low-cost and accuracy. There are two main steps in VUTD scheme: (1) Vehicles are used as mobile anchors to assist adjacent sensor devices in positioning. They are also used to collect logical topology information of the IoT system. The collected logical topology information and location information can be combined into physical topology information that will be sent to the cloud platform through vehicles. (2) The cloud platform analyzes the received information to determine the area where the physical topology discovery is not completed. Then, the cloud platform dispatches the UAVas a flight anchor to locate these points. Experiments based on realworld taxi trajectory are conducted to verify the effectiveness of VUTD scheme. The experimental results show that the VUTD scheme has better performance. Compared with the VTD scheme, the localization ratio is increased by up to 13.6%, and the mean localization error is reduced by up to 90.78%. Compared with UTD, the cost of location discovery is reduced by up to 77.7%. Keywords Internet of things . Unmanned aerial vehicles . Topology discovery . Multi-objective optimization . Cost
1 Introduction In the coming era of Internet of Things (IoTs), billions of sensing devices will be connected to the Internet of Things (IoT). They continuously generate a large volume of data which can be turned into valuable insights for many applications [1, 2].
According to previous researches, the global mobile data traffic is expected to reach 49 EB by 2021 [3]. This causes a huge change of current computation pattern. In the earlier time, a centralized cloud computing pattern is proposed for the computation-intensive and data-Intensive applications [4, 5]. However, with the development of microprocessors, a large
This article is part of the Topical Collection: Special Issue on Emerging Trends on Data Analytics at the Network Edge Guest Editors: Deyu Zhang, Geyong Min, and Mianxiong Dong * Anfeng Liu [email protected] Haojun Teng [email protected] Kaoru Ota [email protected] Tian Wang [email protected] Shaobo Zhang [email protected]
1
School of Computer Science and Engineering, Central S
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