Cooperative Sensing and Compression in Vehicular Sensor Networks for Urban Monitoring

Yu, Xiaoxiao; Zhao, Hang; Zhang, L.; Wu, Shaohua; Krishnamachari, Bhaskar; Li, V. O. K.

doi:10.1109/icc.2010.5502562

Cited by 48 publications

(20 citation statements)

References 12 publications

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“…A vehicle sensor network was developed to monitor the CO 2 concentration in areas of interest [5]. The compressed sensing approach was proposed to recover the sensing map from random and incomplete samples more effectively [3], [4]. The relationship between the sensing delay of an urban vehicular sensing system and the number of vehicles was analyzed based on taxis mobility traces [26].…”

Section: People-centric Sensingmentioning

confidence: 99%

“…Recent advancements in mobile sensing and communication technologies, especially the proliferation of smart phones, offers novel, efficient ways to opportunistically collect data, enabling numerous monitoring applications for obtaining sensing maps of air quality [1], noise [2], [3], temperature [4], CO 2 concentration [5], etc. The application scenario is illustrated in Fig.…”

Section: Introductionmentioning

confidence: 99%

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COUPON: A Cooperative Framework for Building Sensing Maps in Mobile Opportunistic Networks

Zhang

Tang

et al. 2015

IEEE Trans. Parallel Distrib. Syst.

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Abstract-Human-carried or vehicle-mounted sensors can be exploited to collect data ubiquitously for building various sensing maps. Most of existing mobile sensing applications consider users reporting and accessing sensing data through the Internet. However, this approach cannot be applied in the scenarios with poor network coverage or expensive network access. Existing data forwarding schemes for mobile opportunistic networks are not sufficient for sensing applications as spatial-temporal correlation among sensory data has not been explored. In order to build sensing maps satisfying specific sensing quality with low delay and energy consumption, we design COUPON, a novel cooperative sensing and data forwarding framework. We first notice that cooperative sensing scheme can eliminate sampling redundancy and hence save energy. Then we design two cooperative forwarding schemes by leveraging data fusion: Epidemic Routing with Fusion (ERF) and Binary Spray-and-Wait with Fusion (BSWF). Different from previous work assuming that all packets are propagated independently, we consider that packets are spatial-temporal correlated in the forwarding process, and derive the dissemination law of correlated packets. Both the theoretic analysis and simulation results show that our cooperative forwarding schemes can achieve better tradeoff between delivery delay and transmission overhead by both by theory and simulation analysis. We also evaluate our proposed framework and schemes with real mobile traces. Extensive simulations demonstrate that the cooperative sensing scheme can reduce the number of samplings by 93% compared with the non-cooperative scheme; ERF can reduce the transmission overhead by 78% compared with Epidemic Routing (ER); BSWF can increase the delivery ratio by 16%, and reduce the delivery delay and transmission overhead by 5% and 32% respectively, compared with Binary Spray-and-Wait (BSW).

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Section: People-centric Sensingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

COUPON: A Cooperative Framework for Building Sensing Maps in Mobile Opportunistic Networks

Zhang

Tang

et al. 2015

IEEE Trans. Parallel Distrib. Syst.

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“…First, a real WSN implementation for city-wide environmental sensing, called MASON (Metropolitan Area Sensing and Operating Networks) [15], [16], will be introduced, which collects fine-grained environmental data within the city of Beijing. Afterwards, a business process within an enterprise system of power production companies in and around Beijing is illustrated, whereby focus is put on their prediction process for future energy consumption in Beijing.…”

Section: Application Example For Dinam Paasmentioning

confidence: 99%

A Platform-as-a-Service for in-situ development of wireless sensor network applications

Ding

Neumann

Gordon

et al. 2012

2012 Ninth International Conference on Networked Sensing (INSS)

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Abstract-In this paper we present a Platform-as-a-Service (PaaS) approach for rapid development of wireless sensor network (WSN) applications based on the dinam-mite concept, i.e. an embedded web-based development environment and run-time platform for WSN systems integrated in a single information appliance. The PaaS is hosted by a cloud of dinam-mite nodes which facilitates the on-demand development, deployment and integration of WSN applications. We introduce the dinam Cloud architecture and focus, in this paper, on the PaaS layer established by the dinam-mite nodes. In addition to the description of this so-called dinam PaaS, a performance analysis of the dinammite node towards its applicability to forming a dinam PaaS layer is demonstrated. We then present the MASON mobile vehicular network as an example of such a WSN which delivers spatially and temporally fine-grained environmental measurements within the city of Beijing, and illustrate how to utilize the dinam PaaS for integrating the data from the MASON network into its back-end business system. Finally, we discuss the five essential properties of the Cloud Computing stack, according to the NIST definition, with respect to the dinam PaaS and illustrate the benefits of the dinam PaaS for system integration as well as WSN application development.

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“…Recently, in [8,9] Gaussian processes are used to model the monitored phenomena and consequently sensor placement. Moving sensors are studied recently to improve the coverage compared to static sensors [19].…”

Section: Related Workmentioning

confidence: 99%

A Case Study of Participatory Data Transfer for Urban Temperature Monitoring

Shirani-Mehr

Banaei-Kashani

Shahabi

et al. 2011

Web and Wireless Geographical Information Systems

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Abstract. The sensing systems that monitor physical environments rely on communication infrastructures (wired or wireless) to collect data from the sensors embedded in the environment. However, in many urban environments pre-existing communication infrastructures are not available, and installing new infrastructures is unjustifiably expensive and/or technically infeasible. For such environments, we envision Participatory Data Transfer (PDT ) as an alternative communication medium that leverages users participation for data transfer. With PDT, users use mobile devices to receive data from sensors, and forward the sensed data through the ad hoc network of the mobile devices until the data is received by the data aggregators (i.e., data sinks). Sensor deployment and ad hoc routing/networking are two related problems that are both extensively studied in the literature. However, to enable efficient deployment of PDT for sensing applications one needs to consider the requirements of the two aforementioned problems in conjunction. In this paper, we present a case study of PDT with which we explore the performance of PDTbased data transfer with a sample urban sensing application, namely, an urban temperature monitoring application. Our experimental case study is by simulation based on real datasets including GPS track data for more than 2000 vehicles in the city of Beijing. We discuss our observations based on this case study which can serve as directions to design application-specific optimal PDT mechanisms.

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Cooperative Sensing and Compression in Vehicular Sensor Networks for Urban Monitoring

Cited by 48 publications

References 12 publications

COUPON: A Cooperative Framework for Building Sensing Maps in Mobile Opportunistic Networks

COUPON: A Cooperative Framework for Building Sensing Maps in Mobile Opportunistic Networks

A Platform-as-a-Service for in-situ development of wireless sensor network applications

A Case Study of Participatory Data Transfer for Urban Temperature Monitoring

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