Learn More
Moving object gathering pattern represents a group event or incident that involves congregation of moving objects, enabling the prediction of anomalies in traffic system. However, effectively and efficiently discovering the specific gathering pattern turns to be a remaining challenging issue since the large number of moving objects will generate high volume(More)
In vehicular sensor networks, probe vehicles can act as mobile sensors to monitor physical world and report to an urban sensing center. However, the distribution of probe vehicles is uneven over space and time. Data redundancy and vacancy are common phenomena for different spatiotemporal positions, which seriously degrade sensing efficiency and accuracy. To(More)
Log for PaaS cloud computing system is important to provide information to manage systems. In this paper, we design and implement a PaaS log system by providing log recording ability to other parts of PaaS system as a webservice. This system uses Log4j as log frame and CouchDB as database to analyze logs due to its data structure, efficient log analysis(More)
Determining the location of depots of car sharing systems is a fundamental problem in car sharing systems. Existing methods to determine the location of depots mainly use qualitative method and do not take real demand into account. This paper proposes a novel optimization approach to determine the depot location in car sharing systems scientifically. To(More)
A challenging problem that taxi service faces is to fulfill all passenger requests in different regions of a city and different time periods. Taxicab service rate of a region calculated from existing trajectory data can indicate the utilization rate of taxicabs in the region and help solving the problem. However, as trajectory data often contain corrupt or(More)
Taxicab companies want a solution for undersupply (oversupply) problem to boost profits. Finding regional taxicab demand is the key for reducing this disequilibrium. In this paper we investigate a taxicab demand model characterized by estimating demand distribution and recovering sparse data. When more and more trajectories accumulate, statistical(More)
Complex event processing (CEP) is a technique that handles massive data in the Internet of Things (IoT). A lot of researches have been done in RFID. However, most of the existing CEP engines are centralized which result in the resources of sensors are underutilized and wireless network overload. In this paper, wireless sensor network (WSN) will be organized(More)
Clustering is useful for discovering underlying groups and identifying interesting patterns in scientific data and engineering systems. Affinity propagation (AP) is an effective clustering algorithm which has been successfully applied to broad areas of computer science. To generate high quality clusters, AP iteratively performs information propagation on(More)
Mobile data offloading is a feasible and cost-effective solution to ease the burden of cellular networks. In Internet of Vehicles, however, existing offloading techniques are hardly applicable to the ubiquitous location-dependent services, which impose strict spatiotemporal constraints on content delivery. Particularly, the spatiotemporal constraints cause(More)