RTIC-C: A Big Data System for Massive Traffic Information Mining

Yu, Jianjun; Jiang, Fuchun; Zhu, Tongyu

doi:10.1109/cloudcom-asia.2013.91

Cited by 33 publications

(13 citation statements)

References 23 publications

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“…Hyperdex [19] proposes hyperspace hashing method to isolate data into groups of many subspaces to enable searching through different data dimensions. However, this solution requires a lot of extra memory space when the number of subspace increases.…”

Section: Related Workmentioning

confidence: 99%

S4STRD: A Scalable in Memory Storage System for Spatio-temporal Real-Time Data

Pham

Nguyen

Doan

2015

2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)

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The popularity of applications that use spatiotemporal data in real-time has brought about the need for efficient storage systems. There exist different systems for storing data such as the traditional relational database management systems, NoSQL databases, RAM-based, and Hadoop/MapReduce based systems. However, due to the special characteristics of spatio-temporal data used in real-time applications, these available systems do not well match their performance requirements. This paper introduces a distributed RAM-based storage system that works in combination with an NoSQL database to provide better performance for real-time applications that uses huge volume of spatio-temporal data. Experiment results show that the proposed system gives better performance than disk-based NoSQL databases, and scales well when the volume of data is increased.

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Section: Related Workmentioning

confidence: 99%

S4STRD: A Scalable in Memory Storage System for Spatio-temporal Real-Time Data

Pham

Nguyen

Doan

2015

2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)

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“…Therefore, it is essential to develop modern system abstractions that allow us to efficiently process large and new data streams. Even though the number of studies on Big Data in transport has considerably increased, most of the systems deployed so far in order to support Big Data analytics in ITS rely on ad-hoc architecture solutions [4][5]. They focus on satisfying specific predefined goals (mining GPS data, predicting traffic flow, etc.)…”

Section: Introductionmentioning

confidence: 99%

Analytic architecture to overcome real time traffic control as an intelligent transportation system using big data

Nagesh³

2018

IJET

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Big data is a term that describes the large volume of data – both structured and unstructuredthat includes a business on a day-to-day basis including Intelligent Transportation Systems (ITS). The emerging connected technologies created around ubiquitous digital devices have opened unique opportunities to enhance the performance of the ITS. However, magnitude and heterogeneity of the Big Data are beyond the capabilities of the existing approaches in ITS. Therefore, there is a crucial need to develop new tools and systems to keep pace with the Big Data proliferation. In this paper, we propose a comprehensive and flexible architecture based on distributed computing platform for real-time traffic control. The architecture is based on systematic analysis of the requirements of the existing traffic control systems. In it, the Big Data analytics engine informs the control logic. We have partly realized the architecture in a prototype platform that employs Kafka, a state-of-the-art Big Data tool for building data pipelines and stream processing. We demonstrate our approach on a case study of controlling the opening and closing of a freeway hard shoulder lane in microscopic traffic simulation.

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“…With the explosive growth of data size and the highly complicated of data patterns, the network has entered the era of big data [1,2]. Due to the openness, anonymity and interactive of network, it leads to the difficulty of its supervision and management for large-scale data.…”

Section: Introductionmentioning

confidence: 99%

Incremental Learning for Compressed Pornographic Image Recognition

Wang

Zhang

Liu

2015

2015 IEEE International Conference on Multimedia Big Data

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A compressed pornographic image recognition method is proposed by using incremental learning. For describing pornographic image, visual words are created from lowresolution (LR) image reconstructed from the compressed stream of the pornographic image. Covering algorithm is utilized to train and recognize the visual words in order to build the initial classification model of pornographic image. At last, incremental learning is adopted to continuously adjust the classification rules to recognize the new pornographic image samples. The experimental results show that the proposed incremental learning method for compressed pornographic image has higher recognition rate as well as costs less recognition time.

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RTIC-C: A Big Data System for Massive Traffic Information Mining

Cited by 33 publications

References 23 publications

S4STRD: A Scalable in Memory Storage System for Spatio-temporal Real-Time Data

S4STRD: A Scalable in Memory Storage System for Spatio-temporal Real-Time Data

Analytic architecture to overcome real time traffic control as an intelligent transportation system using big data

Incremental Learning for Compressed Pornographic Image Recognition

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