Vehicular mobility and connectivity vary significantly over space and time when vehicular crowd sensing covers a city-wide area for a long time period, but it is important to achieve sufficiently uniform data coverage to satisfy the requirements of an environmental monitoring scenario. Our goal is thus to ensure uniform spatial-temporal coverage of sensed data over a city-wide area despite such vehicle dynamics. For a large area, trajectory-based approaches must deal with a great number and variety of participant mobility patterns. Hence, we propose a probabilistic control mechanism that adaptively adjusts the incentive to each participant, without using any prior information about participants. We provide a mathematical analysis that ensures stability of the number of participants with assigned tasks (called workers), and we evaluate the mechanism's robustness by using 24-hr vehicle trace data from a city-wide area. Our results demonstrate that, when the number of participants is up to 1500 times higher than the required number of workers, sensing actions result in a distribution with a mean of about 1 and an interquartile range of around 4 for a required sensing interval; moreover, the mean increases by 2% when 30% of communication messages are randomly lost.

In a multitenant data center, nodes and links of tenants' virtual networks (VNs) share a single component of the physical substrate network (SN). A failure of the single SN component can thereby cause simultaneous failures of multiple nodes and links in a VN, this complex of failures must significantly disrupt the services offered on the VN. In the present paper, we clarify how the fault tolerance of a VN is affected by a SN failure, especially from the perspective of VN allocation in the SN. We propose a VN allocation model for multitenant data centers and formulate a problem that deals with the bandwidth loss in the VN due the SN failure. We conduct numerical simulations with the setting that has 1.7 × 108bit/s bandwidth demand on each VN. The results show that the bandwidth loss can be reduced to 5.3 × 102bit/s per VN, but the required bandwidth between physical servers in the SN increases to 1.0 × 109bit/s per VN when each node in the VN is mapped to an individual physical server. The balance between the bandwidth loss and the required bandwidth between physical servers can be optimized by assigning every four nodes of the VN to each physical server, meaning that we minimize the bandwidth loss without providing too sufficient bandwidth in the core area of the SN.

Describes a method for recognizing Japanese handwritten characters, including touching ones. The touching characters are segmented by cutting the connected components in a pre-segmentation process. The proposed segmentation method consists of the following steps: (1) identification of the touching components by checking the size of candidate character patterns; (2) estimation of the breakpoint and cutting of the components; and (3) generation of candidate character patterns by merging the components with adjacent patterns. The proposed method has the feature that the touching components can be identified even if they are comprised of relatively small patterns. The touching components are cut by using stroke width analysis and projection image analysis. This cut-and-merge procedure was able to segment 134 (88.2%) address lines correctly out of 152 Japanese address lines having touching portions, and could generate correct candidate character patterns.