4.7 Article

Internode Mobility Correlation for Group Detection and Analysis in VANETs

Journal

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 62, Issue 9, Pages 4590-4601

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2013.2264689

Keywords

Correlated mobility; group detection; vehicular ad hoc networks

Funding

  1. National Science Foundation [CCF-0830680, CNS-1018447]

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Recent studies on mobility-assisted schemes for routing and topology control and on mobility-induced link dynamics have presented significant findings on the properties of a pair of nodes (e. g., the intermeeting time and link life time) or a group of nodes (e. g., network connectivity and partitions). In contrast to the study on the properties of a set of nodes rather than individuals, many works share a common ground with respect to node mobility, i.e., independent mobility in multihop wireless networks. Nonetheless, in vehicular ad hoc networks (VANETs), mobile devices installed on vehicles or held by humans are not isolated; however, they are dependent on each other. For example, the speed of a vehicle is influenced by its close-by vehicles, and vehicles on the same road move at similar speeds. Therefore, the gap between our understanding of the impact of independent mobility and our interest in the properties of correlated mobility in VANETs, along with the real systems altogether, declare an interesting question. How can we measure the internode mobility correlation, such as to uncover the node groups and network components, and explore their impact on link dynamics and network connectivity? Bearing this question in mind, we first examine several traces and find that node mobility exhibits spatial locality and temporal locality correlations, which are closely related to node grouping. To study the properties of these groups on the fly, we introduce a new metric, i.e., dual-locality ratio (DLR), which quantifies mobility correlation of nodes. In light of taking spatial and temporal locality dimensions into account, the DLR can be used to effectively identify stable user groups, which in turn can be used for network performance enhancement.

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