Spatial data is pervasive. Large amount of spatial produced every day from GPS-enabled devices such as cell phones, cars, sensors, and various consumer based applications Uber, location-tagged posts in Facebook, In-stagram, Snapchat, etc. This growth coupled with the fact that queries, analytical or transactional, can be computationally extensive has attracted enormous interest research community to develop systems efficiently process analyze this data. In recent years a lot analytics have...

Active data mining is becoming prevalent in applications requiring focused sampling of relevant to a high-level objective. It especially pertinent scientific and engineering where we seek characterize configuration space or design terms spatial aggregates, collection can become costly. Examples abound domains such as aircraft design, wireless system simulation, fluid dynamics, sensor networks. This paper develops an active mechanism, using Gaussian processes, for uncovering aggregates from...

In the past few years, massive amounts of location-based data has been captured. Numerous datasets containing user location information are readily available to public. Analyzing such can lead fascinating insights into mobility patterns and behaviors users. Moreover, in recent times a number geospatial data-driven companies like Uber, Lyft, Foursquare have emerged. Real-time analysis is essential enables an emerging class applications. Database support for operations turning necessity...

Spatial data is ubiquitous. Massive amounts of are generated every day from billions GPS-enabled devices such as cell phones, cars, sensors, and various consumer-based applications Uber, Tinder, location-tagged posts in Facebook, Twitter, Instagram, etc. This exponential growth spatial has led the research community to focus on building systems that can process efficiently. In meantime, recent introduced learned index structures. this work, we use techniques proposed a state-of-the art...

Engineering high-performance query execution engines is a challenging task. Query compilation provides excellent performance, but at the same time introduces significant system complexity, as it makes engine hard to build, debug, and maintain. To overcome this we propose Nautilus, framework that combines ease of use interpretation performance compilation. On one hand, Nautilus an interpretation-based operator interface enables engineers implement operators using imperative C++ code ensure...

Geospatial joins are a core building block of connected mobility applications. An especially challenging problem between streaming points and static polygons. Since not known beforehand, they cannot be indexed. Nevertheless, need to mapped polygons with low latencies enable real-time feedback. We present an approximate geospatial join that guarantees user-defined precision. Our technique uses quadtree-based hierarchical grid stores these approximations in specialized radix tree. approach can...

Abstract Many applications today like Uber, Yelp, Tinder, etc. rely on spatial data or locations from its users. These and services either build their own management systems existing solutions. JTS Topology Suite (JTS), C++ port GEOS, Google S2, ESRI Geometry API, Java Spatial Index (JSI) are some of the processing libraries that these upon. depend indexing capabilities available in for high-performance query processing. In this work, we compare qualitatively quantitatively based four...

Today’s streaming applications demand increasingly high event throughput rates and are often subject to strict latency constraints. To allow for more complex workloads, such as window-based aggregations, systems need support stateful processing. This introduces new challenges engines the state needs be maintained in a consistent durable manner simultaneously accessed by queries real-time analytics. Modern systems, Apache Flink, do not efficiently exposing analytical queries. Thus, data...

Connected mobility applications rely heavily on geospatial joins that associate point data, such as locations of Uber cars, to static polygonal regions, city neighborhoods. These typically involve expensive geometric computations, which makes it hard provide an interactive user experience. In this paper, we propose adaptive polygon index leverages true hit fltering avoid computations in most cases. particular, our approach closely approximates polygons by combining quadtrees with filtering,...

Sensor data streams occur widely in various real-time applications the context of Internet Things (IoT). However, sensor feature missing values due to factors such as failures, communication errors, or depleted batteries. Missing can compromise quality analytics tasks and downstream applications. Existing imputation methods either make strong assumptions about have low efficiency. In this study, we aim accurately efficiently impute that satisfy only general characteristics order benefit more...

An attempt has been made to delineate and identify the alignment of a new route between two important cities north India, Haridwar & Roorkee using Geoinformatics techniques. Geo-engineering parameters like slope, aspect, geology, land use, drainage soil along with some techno-economical have used for this purpose. Multi-criteria weight method applied. Five weighting methods (AHP - Analytical Hierarchy Process, Rank Sum, Reciprocal, Exponent Ratio Estimation) were applied simultaneously...

Developments in the gas turbine technology have caused widespread usage of Turbomachines for power generation. With increase demand and a drop availability fuel, turbines with higher efficiencies has become imperative. This is only possible an inlet temperature (TIT) gas. However, limit TIT governed by metallurgical boundary conditions set material used to manufacture blades. Hence, blade cooling helps drastically controlling allows temperature. The could be cooled from leading edge, entire...

We present here the results of our investigation a transactional model parallel programming on cluster computing systems. This is specifically targeted for graph applications with goal harnessing unstructured parallelism inherently in many such problems. In this model, tasks vertex-centric computations are executed optimistically as serializable transactions. A key-value based globally shared object store implemented main memory nodes storing data. Task read and modify data distributed...

Spatial approximations have been traditionally used in spatial databases to accelerate the processing of complex geometric operations. However, are typically only a first filtering step determine set candidate objects that may fulfill query condition. To provide accurate results, exact geometries tested against condition, which is an expensive operation. Nevertheless, many emerging applications (e.g., visualization tools) require interactive responses, while needing approximate results....

Spatial data is ubiquitous. Massive amounts of are generated every day from a plethora sources such as billions GPS-enabled devices (e.g., cell phones, cars, and sensors), consumer-based applications Uber Strava), social media platforms location-tagged posts on Facebook, Twitter, Instagram). This exponential growth in spatial has led the research community to build systems for efficient processing. In this study, we apply recently developed machine-learned search technique single-dimensional...

Geospatial joins are a core building block of connected mobility applications. An especially challenging problem between streaming points and static polygons. Since not known beforehand, they cannot be indexed. Nevertheless, need to mapped polygons with low latencies enable real-time feedback. We present an adaptive geospatial join that uses true hit filtering avoid expensive geometric computations in most cases. Our technique quadtree-based hierarchical grid approximate stores these...