智慧城市协同移动数据采集

I. Senturk
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引用次数: 0

摘要

智能城市是由部署在城市各处的传感器收集的大量数据驱动的。传感器通常与基站(BS)组成多跳网络,以便将其数据发送到指挥和控制中心。然而,传感器的稀疏部署可能会使网络的子集与网络的其余部分分开。在这种情况下,隔离的分区无法将其数据转发到BS。因此,网络覆盖率和数据保真度下降。连接分区和提供连接的一个可能的解决方案是使用移动数据收集器(mdc)。支持无线通信的智能汽车可以充当MDC,在传感器和BS之间传输数据。使用单个MDC可以延长平均行程长度。为了最小化最大行程长度,可以使用多个mdc。为了识别每个MDC要访问的传感器,本文按照MDC的数量进行集群分区,并为每个集群分配一个MDC。然后基于mdc间数据交换的可用性,考虑了两种不同的协同数据收集方案。如果mdc在数据交付方面进行协作,它们在某些会议点举行会议以进行数据交换。这样的合作避免了一些mdc访问BS的要求,缩短了行程。另一方面,由于累积数据量较大,靠近BS的mdc可能会由于缓冲区溢出而丢失数据。提出的方法在最大行程长度、数据延迟和数据丢失方面进行了评估。通过在某些设施类型上部署传感器来模拟智能城市应用。地理数据是从一个自愿的地理信息系统中获得的,MDC的移动性受到路网的限制。得到的结果表明,MDC协作减少了最大行程长度,但代价是增加了数据丢失率和数据延迟。
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Cooperative mobile data collection in smart cities
Smart cities are driven by huge amount of data collected from sensors deployed across the city. Sensors typically form a multi-hop network with a base station (BS ) in order to send their data to the command and control center. However, sparse deployment of sensors can leave subsets of the network partitioned from the rest of the network. In such a case, isolated partitions cannot forward their data to the BS . Consequently, network coverage and data fidelity decline. A possible solution to link partitions and provide connectivity is employing mobile data collectors (MDCs). A smart vehicle supporting wireless communication can act as an MDC and carry data between sensors and the BS . Using a single MDC extends the average tour length. To minimize the maximum tour length, multiple MDCs can be employed. To identify sensors to be visited by each MDC, this paper clusters partitions as many as the number of MDCs and assigns an MDC for each cluster. Then two different cooperative data collection schemes are considered based on the availability of inter-MDC data exchange. If MDCs collaborate in data delivery, they meet at certain meeting points for data exchange. Such a cooperation avoids the requirement of visiting the BS for some MDCs and reduces tour lengths. On the other hand, MDCs closer to the BS can experience data loss due to buffer overflow given the higher volume of the accumulated data. Presented approaches are evaluated in terms of maximum tour length, data latency, and data loss. The smart city application is simulated with deployment of sensors on certain amenity types. Geographic data is obtained from a volunteered geographic information system and MDC mobility is restricted with the road network. Obtained results indicate that MDC cooperation decreases maximum tour length at the expense of increased rate of data loss and data latency.
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