Data management in the CarTel mobile sensor computing system

Bychkovsky, Vladimir; Chen, K.; Goraczko, Michel; Hu, Honglin; Hull, Bret; Miu, Allen; Shih, Eugene; Zhang, Y.; Balakrishnan, Hari; Madden, Sam

doi:10.1145/1142473.1142569

Cited by 15 publications

(6 citation statements)

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“…The data management on the vehicle network is studied in CarTel project [1] or TrafficView system [7]. CarTel is an intermittently connected database.…”

Section: Related Workmentioning

confidence: 99%

Road Network Based Adaptive Query Evaluation in VANET

Gao¹,

Han

Yang³

et al. 2008

The Ninth International Conference on Mobile Data Management (Mdm 2008)

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In the Vehicle Ad-hoc NETwork(VANET), moving vehicles organize into a mobile wireless Ad-hoc network to share online traffic information. Each vehicle can issue a declarative query for aggregating the traffic information from others in order to facilitate the navigation and avoid traffic jam. Existing query methods suffer from high latency, incomplete results, and large messages due to the movement of the vehicles in VANET. In this paper, we propose an adaptive query evaluation method based on the road network. In order to overcome the problems incurred by the movement, a relative static query evaluation plan is constructed based on the road network, and each vehicle can participate in the query evaluation plan autonomously. We also introduce control messages to notify the changed location of the query originator to other vehicles involved in the evaluation plan. In addition, we propose an one time message transferring based results collecting method to reduce the message cost. The optimization over the multiple queries is also discussed to reduce the messages further. We evaluate the performance of our method by extensive simulations. Experimental results show that our method can provide complete results within a short response time and small traffic overhead.

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“…The data management on the vehicle network is studied in CarTel project [1] or TrafficView system [7]. CarTel is an intermittently connected database.…”

Section: Related Workmentioning

confidence: 99%

Road Network Based Adaptive Query Evaluation in VANET

Gao¹,

Han

Yang³

et al. 2008

The Ninth International Conference on Mobile Data Management (Mdm 2008)

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show abstract

“…Another framework for collision avoidance is proposed in [4] where the hardware components (including a mini-PC) are integrated into the car and linked to the dashboard display. In [5] a querying model for collecting and sharing information about vehicles and roads status is described. A possible use of mobile devices and OBD systems for providing failure assistance to the driver is presented in [6].…”

Section: Related Workmentioning

confidence: 99%

Multimodal PDA Interfaces to Assist Drivers in Monitoring Their Vehicles

Ghiani

Paternò

2007

Lecture Notes in Computer Science

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Abstract. In this paper we present a new hardware/software solution, which allows users to easily interact with their cars' components through the OBD-II system. We propose a multimodal interface for PDAs supporting vocal and graphical commands. Our aim is to provide a safe and usable way to access the sensed engine data and vehicular status while driving. The retrieved information, which can be presented through different modalities, is used to alert the driver about some events, such as surpassing the speed limit.

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“…Over the past decades, we have witnessed the development of automotive electronics [1] and IoTs [2]. Nowadays, modern vehicles have already equipped with dozens or even hundreds of sensors onboard, like oxygen sensor, speedometer, temperature sensor and etc [3]. Undoubtedly, the sensory data can contribute useful information to many emerging intelligent transportation system and urban computing applications [4] [5], such as traffic congestion detection [6], vehicle emission and environmental pollution monitoring [7].…”

Section: Introductionmentioning

confidence: 99%

Cost-efficient traffic-aware data collection protocol in VANET

Zhang

2017

Ad Hoc Networks

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Data from running vehicles are invaluable to numerous ITS and urban computing applications. This paper studies the issue of collecting data from multiple vehicles to a roadside base station via vehicle-to-vehicle and vehicle-toinfrastructure communications. Existing data collection approaches in VANET have mainly focused on the network problems, such as packet loss, network clustering or data aggregation, but the impact of real-time traffic condition is barely considered. In this paper, we investigate the data collection problem in VANETs under rapid evolving traffic conditions. Our approach can adaptively choose to carry or forward the data packet, based on current traffic information. The objective is to minimize the network communication overhead while satisfying the data collection time constraint. We formulate the data collection problem as a scheduling optimization problem and prove it is NP-complete. An optimal dynamic programming solution and a genetic algorithm based heuristic solution are developed to solve the problem under different application scenarios. Extensive evaluations validate that our proposed solution outperforms some existing ones in terms of effectiveness and efficiency.

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Data management in the CarTel mobile sensor computing system

Cited by 15 publications

References 0 publications

Road Network Based Adaptive Query Evaluation in VANET

Road Network Based Adaptive Query Evaluation in VANET

Multimodal PDA Interfaces to Assist Drivers in Monitoring Their Vehicles

Cost-efficient traffic-aware data collection protocol in VANET

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