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Abstract: Modern urban areas are influenced by numerous inter-related human and natural factors and present extremely complicated non-linear and dynamic properties. As a bridge between the physical world and the cyber space, pervasive sensing technologies make it possible to have a deep understanding of urban environments. There are two inter-related technical planes to achieve it, namely, sensing and computing. In this paper, we introduce our work progress on the urban dynamics study for each technical plane, respectively. First, we design and implement a prototype urban sensing system based on automobiles as mobile agents, performing information-rich data collection. Then, we propose a Spatial–Temporal-Entangled Analysis (STEA) algorithm based on semi-supervised manifold learning and the regularized optimization to extract semantic information from incomplete sensing data, aiming for better understanding of the spatial–temporal correlation of a complex physical process and the correlation between human activities and environmental changes via incomplete sensing data. Finally, we evaluate STEA in a real urban sensing application. Specifically, the proposed prototype is used to collect traffic and air pollution data in Beijing, and such real-world datasets are used to evaluate the effectiveness of STEA. The results obtained are very promising and show an implicit correlation between the traffic density and the air pollution, demonstrating the potential of this technique in environmental studies for urban areas. [Copyright &y& Elsevier]

Abstract: A considerable amount of research on distributed hash table (DHT) based mobility support schemes, which are highly user scalable and load balanced, has been done. But these schemes have shortcomings in query performances and network scalability. It is because although routing of overlay is effective, there is inconsistency between logical and physical topologies, so the actual physical network performances are not necessarily efficient. In this paper, we introduce a replication technology based DHT-based mobility support. Then all queries from any subnet can get responses as early as possible, i.e., the query distances are reduced, and the scopes of the effect of topological inconsistency are limited. We investigate the effect of the number of mapping replicas on query performances for DHT-based mobility support. And we find that replicating mobile nodes’ mappings in proportion to their call-mobility-rates minimizes the query delay and ensures fairness in the query load distribution. Moreover, we combine the hierarchical structure with the domain-level DHT-based (dDHT) structure, to reduce the expense of replication on update performances. We propose a hierarchical DHT and proportional replication based mobility management (HDPRMM) scheme. The numerical results show HDPRMM optimizes the query and update performances of dDHT, and achieves better fairness and network scalability than MIP and dDHT. [Copyright &y& Elsevier]