Middleware for Mobile Sensing Applications in Urban Environments

Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.

Accumulation of point mutations and reassortment of genomic RNA segments are involved in the microevolution of Puumala hantavirus in a bank vole (Myodes glareolus) population

"The genetic diversity of Puumala hantavirus (PUUV) was studied in a local population of its natural host, the bank vole (Myodes glareolus). The trapping area (2.5x2.5 km) at Konnevesi, Central Finland, included 14 trapping sites, at least 500 m apart; altogether, 147 voles were captured during May and October 2005. Partial sequences of the S, M and L viral genome segments were recovered from 40 animals. Seven, 12 and 17 variants were detected for the S, M and L sequences, respectively; these represent new wild-type PUUV strains that belong to the Finnish genetic lineage. The genetic diversity of PUUV strains from Konnevesi was 0.2-4.9% for the S segment, 0.2-4.8% for the M segment and 0.2-9.7% for the L segment. Most nucleotide substitutions were synonymous and most deduced amino acid substitutions were conservative, probably due to strong stabilizing selection operating at the protein level. Based on both sequence markers and phylogenetic clustering, the S, M and L sequences could be assigned to two groups, 'A' and 'B'. Notably, not all bank voles carried S, M and L sequences belonging to the same group, i.e. SAMALA or SBMBLB.. A substantial proportion (8/40, 20%) of the newly characterized PUUV strains possessed reassortant genomes such as SBMALA, SAMBLB or SBMALB. These results suggest that at least some of the PUUV reassortants are viable and can survive in the presence of their parental strains."