A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks
Using mobile vehicles as “data mules” to collect data generated by a huge number of sensing devices that are widely spread across smart city is considered to be an economical and effective way of obtaining data about smart cities. However, currently most research focuses on the feasibility of the pr...
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MDPI AG
2017-04-01
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Online Access: | http://www.mdpi.com/1424-8220/17/4/888 |
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author | Yixuan Xu Xi Chen Anfeng Liu Chunhua Hu |
author_facet | Yixuan Xu Xi Chen Anfeng Liu Chunhua Hu |
author_sort | Yixuan Xu |
collection | DOAJ |
description | Using mobile vehicles as “data mules” to collect data generated by a huge number of sensing devices that are widely spread across smart city is considered to be an economical and effective way of obtaining data about smart cities. However, currently most research focuses on the feasibility of the proposed methods instead of their final performance. In this paper, a latency and coverage optimized data collection (LCODC) scheme is proposed to collect data on smart cities through opportunistic routing. Compared with other schemes, the efficiency of data collection is improved since the data flow in LCODC scheme consists of not only vehicle to device transmission (V2D), but also vehicle to vehicle transmission (V2V). Besides, through data mining on patterns hidden in the smart city, waste and redundancy in the utilization of public resources are mitigated, leading to the easy implementation of our scheme. In detail, no extra supporting device is needed in the LCODC scheme to facilitate data transmission. A large-scale and real-world dataset on Beijing is used to evaluate the LCODC scheme. Results indicate that with very limited costs, the LCODC scheme enables the average latency to decrease from several hours to around 12 min with respect to schemes where V2V transmission is disabled while the coverage rate is able to reach over 30%. |
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language | English |
last_indexed | 2024-04-11T14:06:27Z |
publishDate | 2017-04-01 |
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spelling | doaj.art-ea4c7a7196d14cdc9d096e5dfee67fb42022-12-22T04:19:52ZengMDPI AGSensors1424-82202017-04-0117488810.3390/s17040888s17040888A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc NetworksYixuan Xu0Xi Chen1Anfeng Liu2Chunhua Hu3School of Information Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaKey Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Commerce, Changsha 410205, ChinaUsing mobile vehicles as “data mules” to collect data generated by a huge number of sensing devices that are widely spread across smart city is considered to be an economical and effective way of obtaining data about smart cities. However, currently most research focuses on the feasibility of the proposed methods instead of their final performance. In this paper, a latency and coverage optimized data collection (LCODC) scheme is proposed to collect data on smart cities through opportunistic routing. Compared with other schemes, the efficiency of data collection is improved since the data flow in LCODC scheme consists of not only vehicle to device transmission (V2D), but also vehicle to vehicle transmission (V2V). Besides, through data mining on patterns hidden in the smart city, waste and redundancy in the utilization of public resources are mitigated, leading to the easy implementation of our scheme. In detail, no extra supporting device is needed in the LCODC scheme to facilitate data transmission. A large-scale and real-world dataset on Beijing is used to evaluate the LCODC scheme. Results indicate that with very limited costs, the LCODC scheme enables the average latency to decrease from several hours to around 12 min with respect to schemes where V2V transmission is disabled while the coverage rate is able to reach over 30%.http://www.mdpi.com/1424-8220/17/4/888smart citydata collectionVANETopportunistic routingdata mining |
spellingShingle | Yixuan Xu Xi Chen Anfeng Liu Chunhua Hu A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks Sensors smart city data collection VANET opportunistic routing data mining |
title | A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks |
title_full | A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks |
title_fullStr | A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks |
title_full_unstemmed | A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks |
title_short | A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks |
title_sort | latency and coverage optimized data collection scheme for smart cities based on vehicular ad hoc networks |
topic | smart city data collection VANET opportunistic routing data mining |
url | http://www.mdpi.com/1424-8220/17/4/888 |
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