Query management in a sensor environment

Traditional sensor network deployments consisted of fixed infrastructures and were relatively small in size. More and more, we see the deployment of ad-hoc sensor networks with heterogeneous devices on a larger scale, posing new challenges for device management and query processing. In this paper, we present our design and prototype implementation of XSense, an architecture supporting metadata and query services for an underlying large scale dynamic P2P sensor network. We cluster sensor devices into manageable groupings to optimise the query process and automatically locate appropriate clusters based on keyword abstraction from queries. We present experimental analysis to show the benefits of our approach and demonstrate improved query performance and scalability

Innervation patterns of the canine masticatory muscles in comparison to human

The aim of this study was to clarify the nerve distribution of the masseter, temporalis, and zygomaticomandibularis (ZM) muscles to elucidate the phylogenetic traits of canine mastication. A detailed dissection was made of 15 hemisectioned heads of adult beagle dogs. The innervations of the masticatory nerve twigs exhibited a characteristic pattern and were classified into seven groups. Twig innervating the anterior portion of the temporalis (aTM) was defined as the anterior temporal nerve (ATN). Anterior twig of ATN branched from the buccal nerve and innervated only the aTM, whereas posterior twig of ATN innervated both of the aTM and deep layer of the tempolaris (dTM). From this and morphological observations, it was proposed that the action of the canine aTM is more independent than that of the human. The middle temporal nerve ran superoposteriorly within the dTM and superficial layer of the temporalis (sTM) innervating both of them, whereas the posterior temporal nerve innervated only the posterior region of the sTM. The masseteric nerve (MSN) innervated the ZM and the three layers of the masseter. Deep twig of MSN was also observed innervating sTM after entering the ZM in all cases. The major role played by the canine ZM might thus underlie the differential arrangement of the distribution of the masticatory nerve bundles in dogs and humans. Although the patterns of innervation to the canine and human masticatory muscles were somewhat similar, there were some differences that might be due to evolutionary adaptation to their respective feeding stylesope

CAREER: Data Management for Ad-Hoc Geosensor Networks

This project explores data management methods for geosensor networks, i.e. large collections of very small, battery-driven sensor nodes deployed in the geographic environment that measure the temporal and spatial variations of physical quantities such as temperature or ozone levels. An important task of such geosensor networks is to collect, analyze and estimate information about continuous phenomena under observation such as a toxic cloud close to a chemical plant in real-time and in an energy-efficient way. The main thrust of this project is the integration of spatial data analysis techniques with in-network data query execution in sensor networks. The project investigates novel algorithms such as incremental, in-network kriging that redefines a traditional, highly computationally intensive spatial data estimation method for a distributed, collaborative and incremental processing between tiny, energy and bandwidth constrained sensor nodes. This work includes the modeling of location and sensing characteristics of sensor devices with regard to observed phenomena, the support of temporal-spatial estimation queries, and a focus on in-network data aggregation algorithms for complex spatial estimation queries. Combining high-level data query interfaces with advanced spatial analysis methods will allow domain scientists to use sensor networks effectively in environmental observation. The project has a broad impact on the community involving undergraduate and graduate students in spatial database research at the University of Maine as well as being a key component of a current IGERT program in the areas of sensor materials, sensor devices and sensor. More information about this project, publications, simulation software, and empirical studies are available on the project\u27s web site (http://www.spatial.maine.edu/~nittel/career/)

Progressive Processing of Continuous Range Queries in Hierarchical Wireless Sensor Networks

In this paper, we study the problem of processing continuous range queries in a hierarchical wireless sensor network. Contrasted with the traditional approach of building networks in a "flat" structure using sensor devices of the same capability, the hierarchical approach deploys devices of higher capability in a higher tier, i.e., a tier closer to the server. While query processing in flat sensor networks has been widely studied, the study on query processing in hierarchical sensor networks has been inadequate. In wireless sensor networks, the main costs that should be considered are the energy for sending data and the storage for storing queries. There is a trade-off between these two costs. Based on this, we first propose a progressive processing method that effectively processes a large number of continuous range queries in hierarchical sensor networks. The proposed method uses the query merging technique proposed by Xiang et al. as the basis and additionally considers the trade-off between the two costs. More specifically, it works toward reducing the storage cost at lower-tier nodes by merging more queries, and toward reducing the energy cost at higher-tier nodes by merging fewer queries (thereby reducing "false alarms"). We then present how to build a hierarchical sensor network that is optimal with respect to the weighted sum of the two costs. It allows for a cost-based systematic control of the trade-off based on the relative importance between the storage and energy in a given network environment and application. Experimental results show that the proposed method achieves a near-optimal control between the storage and energy and reduces the cost by 0.989~84.995 times compared with the cost achieved using the flat (i.e., non-hierarchical) setup as in the work by Xiang et al.Comment: 41 pages, 20 figure

On Atomic Batch Executions in Stream Processing

AbstractStream processing is about processing continuous streams of data by programs in a workflow. Continuous execution is discretized by grouping input stream tuples into batches and using one batch at a time for the execution of programs. As source input batches arrive continuously, several batches may be processed in the workflow simultaneously. A general requirement is that each batch be processed completely in the workflow. That is, all the programs triggered by the batch, directly and transitively, in the workflow must be executed successfully. Executing only a prefix of the workflow amounts to dropping (discarding) the batches that were derived by the executed part and were supposed to be input to the rest of the workflow. In some cases, such partial executions may not be acceptable and may have to be rolled back, amounting to dropping the source input batches that were processed by the partial execution. We refer to this property of processing the batches either completely or not at all as atomic execution of the batches. We also attribute the property to the batches themselves, calling them atomic batches, meaning that the property applies to the set of transactions that are executed due to that batch. If batches are processed in isolation in the workflow, preserving atomicity is fairly straightforward. When batches are split or merged along the workflow computation, the problem becomes complicated. In this paper, we study issues relating to the atomicity of batches. We illustrate that, in general, preserving atomicity of some batches may affect the atomicity of some other batches, and suggest trade-offs

A Transaction Model for Executions of Compositions of Internet of Things Services

AbstractInternet of Things (IoT) is about making “things” smart in some functionality, and connecting and enabling them to perform complex tasks by themselves. The functionality can be encapsulated as services and the task executed by composing the services. Two noteworthy functionalities of IoT services are monitoring and actuation. Monitoring implies continuous executions, and actuation is by triggering. Continuous executions typically involve stream processing. Stream input data are accumulated into batches and each batch is subjected to a sequence of computations, structured as a dataflow graph. The composition may be processing several batches simultaneously. Additionally, some non-stream OLTP transactions may also be executing concurrently. Thus, several composite transactions may be executing concurrently. This is in contrast to a typical Web services composition, where just one composite transaction is executed on each invocation. Therefore, defining transactional properties for executions of IoT service compositions is much more complex than for those of conventional Web service compositions. In this paper, we propose a transaction model and a correctness criterion for executions of IoT service compositions. Our proposal defines relaxed atomicity and isolation properties for transactions in a flexible manner and can be adapted for a variety of IoT applications

Power efficiency through tuple ranking in wireless sensor network monitoring

In this paper, we present an innovative framework for efficiently monitoring Wireless Sensor Networks (WSNs). Our framework, coined KSpot, utilizes a novel top-k query processing algorithm we developed, in conjunction with the concept of in-network views, in order to minimize the cost of query execution. For ease of exposition, consider a set of sensors acquiring data from their environment at a given time instance. The generated information can conceptually be thought as a horizontally fragmented base relation R. Furthermore, the results to a user-defined query Q, registered at some sink point, can conceptually be thought as a view V . Maintaining consistency between V and R is very expensive in terms of communication and energy. Thus, KSpot focuses on a subset V′ (⊆ V ) that unveils only the k highest-ranked answers at the sink, for some user defined parameter k. To illustrate the efficiency of our framework, we have implemented a real system in nesC, which combines the traditional advantages of declarative acquisition frameworks, like TinyDB, with the ideas presented in this work. Extensive real-world testing and experimentation with traces from University of California-Berkeley, the University of Washington and Intel Research Berkeley, show that KSpot provides an up to 66% of energy savings compared to TinyDB, minimizes both the size and number of packets transmitted over the network (up to 77%), and prolongs the longevity of a WSN deployment to new scales

Real-Time Data Analytics in Sensor Networks

Abstract. The proliferation of Wireless Sensor Networks (WSNS) in the past decade has provided the bridge between the physical and digital worlds, enabling the monitoring and study of physical phenomena at a granularity and level of detail that was never before possible. In this study, we review the efforts of the research community with respect to two important problems in the context of WSNS: real-time collection of the sensed data, and real-time processing of these data series

Integración de la minería genómica y la metabolómica para descifrar el potencial de producción de metabolitos bioactivos en cepas de Streptomyces de Uruguay

El género Streptomyces es reconocido por su versatilidad metabólica y capacidad de producción de metabolitos bioactivos. A pesar de décadas de investigación, se siguen descubriendo nuevos productos naturales derivados de Streptomyces, lo que destaca la importancia de continuar explorando este género en busca de compuestos con potencial terapéutico y aplicaciones biotecnológicas. El presente trabajo de tesis permitió la caracterización de una colección de 235 cepas de Streptomyces aisladas en Uruguay en cuanto a su potencial de producción de metabolitos bioactivos. En primer lugar, se determinaron los compuestos fitotóxicos responsables de la patogenicidad en papa de diferentes especies de Streptomyces a partir de los perfiles metabolómicos por 1H RMN de los sobrenadantes de cultivo de algunas cepas de Streptomyces de la colección. Se estableció un modelo metabolómico capaz de clasificar las cepas en función de su fitotoxicidad, estableciendo correlaciones entre los perfiles metabólicos y las relaciones filogenéticas de las especies de Streptomyces patógenas. Por otro lado, se evaluaron otras actividades de interés para lo cual se optimizaron nuevas metodologías de screening como la actividad nematicida y de promoción de crecimiento vegetal. Se identificaron 17 cepas de Streptomyces con actividad nematicida frente a C. elegans. Por otra parte, se identificaron varias cepas con propiedades de actividad promotora de crecimiento vegetal, como la producción de compuestos que solubilizan el fósforo, de sideróforos y de hormonas vegetales. Posteriormente, se profundizó en la determinación de los metabolitos responsables de estas actividades en cinco de estas cepas abordando un enfoque genómico y metabolómico.En cuanto a los estudios de minería genómica, se encontraron varios grupos de genes biosintéticos (BGCs) de diversos tipos entre las cepas analizadas, donde la mayoría presentan nula o muy baja similitud con otros BGCs reportados, evidenciando la existencia de BGCs desconocidos. El estudio metabolómico se basó en el uso de cromatografía líquida acoplada a detector de masas en tándem y plataformas de análisis asociadas a bases de datos para determinar los compuestos presentes en las muestras. Los resultados obtenidos permitieron contar con posibles candidatos, y además revelaron una alta proporción de estructuras químicas desconocidas. Por último, se realizó un análisis genético funcional en una de las cepas con actividad nematicida para evaluar el rol de la antimicina como compuesto responsable de su actividad. Para ello, se construyó un mutante knock out del gen antC mediante la estrategia CRISPR-Cas9. No se detectaron diferencias claras entre el fenotipo nematicida de la cepa salvaje y mutante, por lo que se sugiere la presencia de otros compuestos responsables de la actividad. La ejecución de esta tesis fue clave para la implementación de nuevas herramientas de análisis metabolo genómicos que serán de gran utilidad para futuros proyectos. Además, se cuenta con un repertorio de cepas bioactivas caracterizadas y con un gran volumen de datos sobre sus perfiles metabólicos y genómicos que sugieren la existencia de nuevas moléculas sobre las cuales continuar profundizando.CAPÍTULO 1: INTRODUCCIÓN GENERAL. 1.1 Los actinomicetos y el género Streptomyces. 1.2 Productos naturales del género Streptomyces. 1.3 Principales clases de productos naturales producidos por Streptomyces y su biosíntesis. 1.4 Un nuevo concepto: metabolismo especializado. 1.5 El particular genoma de los actinomicetos. 1.6 Estrategias para el descubrimiento de nuevos metabolitos especializados de Streptomyces. 1.6.1 Minería genómica. 1.6.2 Metabolómica. 1.6.3 Integración metabologenómica. 1.7 Antecedentes de trabajo y justificación. 1.8 Objetivos y descripción de la tesis. 1.8.1 Objetivo general. 1.8.2 Objetivos específicos:. 1.8.3 Descripción de la Tesis. CAPÍTULO 2: CARACTERIZACIÓN DE COMPUESTOS FITOTÓXICOS PRODUCIDOS POR CEPAS DE STREPTOMYCES PATÓGENAS MEDIANTE UN ABORDAJE METABOLÓMICO Y FILOGENÉTICO. 2.1 Introducción. 2.2 Materiales y métodos. 2.2.1 Cepas bacterianas y condiciones de cultivo. 2.2.2 Bioensayo de fitotoxicidad en rabanito. 2.3 Análisis por HPLC-UV. 2.2.4 Análisis filogenético de las cepas. 2.2.5 Detección molecular de genes específicos de DMSN y TXT. 2.2.6 Espectroscopía por RMN. 2.2.7 Análisis estadístico multivariado. 2.3 Resultados. 2.3.1 La mayoría de los sobrenadantes de las cepas de Streptomyces patógenas presentaron actividad fitotóxica. 2.3.2 Correlación de la fitotoxicidad con fitotoxinas ya conocidas producidas por Streptomyces. 2.3.3 Conectando el perfil metabólico con el potencial patogénico y la filogenia de las cepas. 2.4 Discusión. CAPÍTULO 3: EVALUACIÓN DE ACTIVIDAD NEMATICIDA Y DE PROMOCIÓN DE CRECIMIENTO VEGETAL EN CEPAS DE STREPTOMYCES AISLADAS EN URUGUAY. 3.1 Introducción. 3.1.1 Actividad antiparasitaria. 3.1.2 Actividad de promoción de crecimiento vegetal. 3.2 Materiales y métodos. 3.2.1 Optimización de las condiciones del ensayo de actividad nematicida. 3.2.2 Metodología optimizada para la evaluación de actividad nematicida en sobrenadantes de cultivo. 3.2.3 Pre-screening de actividad nematicida. 3.2.4 Screening de actividad nematicida. 3.2.5 Identificación molecular de las cepas con actividad nematicida. 3.2.6 Preparación de extractos orgánicos y acuosos a partir de sobrenadantes de cepas seleccionadas con actividad nematicida. 3.2.7 Screening de propiedades de promoción de crecimiento vegetal in vitro. 3.3 Resultados. 3.3.1 Optimización de las condiciones del ensayo de actividad nematicida. 3.3.2 Selección de cepas de Streptomyces productoras de compuestos con actividad nematicida. 3.3.3 Actividad nematicida en extractos acuosos y orgánicos de las cepas seleccionadas. 3.3.4 Identificación molecular de las cepas de Streptomyces seleccionadas con actividad nematicida. 3.3.5 Screening de propiedades directas de PCV en cepas de Streptomyces seleccionada. 3.4 Discusión. CAPÍTULO 4: ESTUDIO METABOLOGENÓMICO DE UNA SELECCIÓN DE CEPAS DE STREPTOMYCES SPP. BIOACTIVAS. 4.1 Introducción. 4.1.1 Minería de genomas. 4.1.2 Minería metabolómica. 4.2 Materiales y métodos. 4.2.1 Cepas bacterianas y condiciones de cultivo. 4.2.2 Análisis genómico. 4.2.3 Análisis metabolómico. 4.3 Resultados. 4.3.1 Secuenciación del genoma completo de cepas de Streptomyces seleccionadas 111 4.3.2 Ensamblaje de los genomas. 4.3.3 Anotación de los genomas ensamblados. 4.3.4 Identificación y relaciones taxonómicas de las cepas. 4.3.5 Minería genómica. 4.3.6 Análisis de BGCs desde una perspectiva global: BiG-SCAPE. 4.3.7 Análisis metabolómico: construcción de redes moleculares. 4.3.8 Compuestos bioactivos candidatos en base a coincidencias obtenidas con bilbliotecas de GNPS y su conexión con sus BGCs. 4.3.9 Búsqueda de compuestos nematicidas en la base de datos del NPAtlas. 4.4 Discusión. CAPÍTULO 5: EVALUACIÓN DE LA ACTIVIDAD NEMATICIDA DE ANTIMICINAS MEDIANTE LA CONSTRUCCIÓN DE UN MUTANTE KNOCK-OUT. 5.1 Introducción. 5.2 Materiales y métodos. 5.2.1 Búsqueda de antimicinas en la cepa MAI 2237. 5.2.2 Construcción del mutante de Streptomyces MAI 2237ΔantC utilizando la metodología CRISPR-Cas9. 5.2.3 Evaluación de la actividad nematicida frente a C. elegans en la cepa Streptomyces MAI 2237 y el mutanteΔantC. 5.3 Resultados. 5.3.1 Análisis del BGC de antimicina de la cepa MAI 2237 y verificación de su expresión. 5.3.2 Evaluación de la capacidad de conjugación y sensibilidad a antibióticos de la cepa a modificar. 5.3.3 Construcción del plásmido pCRISPR con los elementos necesarios para realizar la edición genética. 5.3.4 Conjugación y edición genómica de MAI 2237. 5.3.5 Curado del plásmido. 5.3.6 Evaluación de la actividad nematicida de la cepa MAI 2237ΔantC. 5.4 Discusión - CAPÍTULO 6: CONSIDERACIONES FINALES Y PERSPECTIVAS - BIBLIOGRAFÍA - ANEXO

Explainable and Resource-Efficient Stream Processing Through Provenance and Scheduling

In our era of big data, information is captured at unprecedented volumes and velocities, with technologies such as Cyber-Physical Systems making quick decisions based on the processing of streaming, unbounded datasets. In such scenarios, it can be beneficial to process the data in an online manner, using the stream processing paradigm implemented by Stream Processing Engines (SPEs). While SPEs enable high-throughput, low-latency analysis, they are faced with challenges connected to evolving deployment scenarios, like the increasing use of heterogeneous, resource-constrained edge devices together with cloud resources and the increasing user expectations for usability, control, and resource-efficiency, on par with features provided by traditional databases.This thesis tackles open challenges regarding making stream processing more user-friendly, customizable, and resource-efficient. The first part outlines our work, providing high-level background information, descriptions of the research problems, and our contributions. The second part presents our three state-of-the-art frameworks for explainable data streaming using data provenance, which can help users of streaming queries to identify important data points, explain unexpected behaviors, and aid query understanding and debugging. (A) GeneaLog provides backward provenance allowing users to identify the inputs that contributed to the generation of each output of a streaming query. (B) Ananke is the first framework to provide a duplicate-free graph of live forward provenance, enabling easy bidirectional tracing of input-output relationships in streaming queries and identifying data points that have finished contributing to results. (C) Erebus is the first framework that allows users to define expectations about the results of a streaming query, validating whether these expectations are met or providing explanations in the form of why-not provenance otherwise. The third part presents techniques for execution efficiency through custom scheduling, introducing our state-of-the-art scheduling frameworks that control resource allocation and achieve user-defined performance goals. (D) Haren is an SPE-agnostic user-level scheduler that can efficiently enforce user-defined scheduling policies. (E) Lachesis is a standalone scheduling middleware that requires no changes to SPEs but, instead, directly guides the scheduling decisions of the underlying Operating System. Our extensive evaluations using real-world SPEs and workloads show that our work significantly improves over the state-of-the-art while introducing only small performance overheads