Abstract
Vehicular nodes are equipped with more and more sensing units, and a large amount of sensing data is generated. Recently, more and more research considers cooperative urban sensing as the heart of intelligent and green city traffic management. The key components of the platform will be a combination of a pervasive vehicular sensing system, as well as a central control and analysis system, where data-gathering is a fundamental component. However, the data-gathering and monitoring are also challenging issues in vehicular sensor networks because of the large amount of data and the dynamic nature of the network. In this paper, we propose an efficient continuous event-monitoring and data-gathering framework based on fog nodes in vehicular sensor networks. A fog-based two-level threshold strategy is adopted to suppress unnecessary data upload and transmissions. In the monitoring phase, nodes sense the environment in low cost sensing mode and generate sensed data. When the probability of the event is high and exceeds some threshold, nodes transfer to the event-checking phase, and some nodes would be selected to transfer to the deep sensing mode to generate more accurate data of the environment. Furthermore, it adaptively adjusts the threshold to upload a suitable amount of data for decision making, while at the same time suppressing unnecessary message transmissions. Simulation results showed that the proposed scheme could reduce more than 84 percent of the data transmissions compared with other existing algorithms, while it detects the events and gathers the event data.
Highlights
With the development of vehicular and communication technologies, there emerges a new technology called vehicular ad hoc networks (VANETs) that integrates the capabilities of new generation wireless networks to vehicles [1,2,3]
TPEG adaptively adjusts the threshold to upload a suitable amount of data for decision making, while at the same time suppressing unnecessary message transmissions
Kai et al [31] gave a survey about some opportunities and challenges related to the context of fog computing in VANETs; and Zeng et al [12] proposed a three-layer framework based on a fog structure for uploading data from sensor readings to the cloud
Summary
With the development of vehicular and communication technologies, there emerges a new technology called vehicular ad hoc networks (VANETs) that integrates the capabilities of new generation wireless networks to vehicles [1,2,3]. Vehicular nodes are equipped with more and more sensing units, and large amounts of sensing data such as GPS locations, speeds and video clips are generated [9] These data are shared or uploaded as input for applications aiming at more intelligent transportation, emergency response and reducing pollution and fuel consumption. The main contributions of this paper are as follows: By integrating the concept of fog nodes and VANETs, we propose an efficient scheme to efficiently monitor the events and gather data based on VANETs. The sensing operators are roughly classified into the low cost sensing (LCS) mode and the high cost sensing (HCS) mode, and by taking full. Advantage of the fog nodes, our scheme strikes a good balance between these two modes to achieve better efficiency; The “two-level threshold adjustment” (2LTA) is proposed to avoid unnecessary event-checking and data upload. The rest of the paper is structured as follows: Section 2 describes the related work; Section 3 introduces some preliminaries and defines the network model and metrics; Section 4 presents the detailed description of the TPEG algorithm, including monitoring, event-checking, data upload and threshold adjustment; Section 5 describes the environmental setup and analyzes the simulation results; Section 6 concludes the paper
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