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spatialSSJP: QoS-Aware Adaptive Approximate Stream-Static spatial Join Processor

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2024年第1期35卷 73-88页

作者： Al Jawarneh, Isam Mashhour Bellavista, Paolo Corradi, Antonio Foschini, Luca Montanari, Rebecca Univ Bologna Dipartimento Informat Scienzae & Ingn DISI I-40136 Bologna Italy

The widespread adoption of Internet of Things (IoT) motivated the emergence of mixed workloads in smart cities, where fast arriving geo-referenced big data streams are joined with archive tables, aiming at enriching streams with descriptive attributes that enable insightful analytics. Applications are now relying on finding, in real-time, to which geographical regions data streaming tuples belong. This problem requires a computationally intensive stream-static join for joining a dynamic stream with a disk-resident static table. In addition, the time-varying nature of fluctuation in geospatial data arriving online calls for an approximate solution that can trade-off QoS constraints while ensuring that the system survives sudden spikes in data loads. In this paper, we present spatialSSJP, an adaptive spatial-aware approximate query processing system that specifically focuses on stream-static joins in a way that guarantees achieving an agreed set of Quality-of-Service goals and maintains geo-statistics of stateful online aggregations over stream-static join results. spatialSSJP employs a state-of-art stratified-like sampling design to select well-balanced representative geospatial data stream samples and serve them to a stream-static geospatial join operator downstream. We implemented a prototype atop Spark Structured Streaming. Our extensive evaluations on big real datasets show that our system can survive and mitigate harsh join workloads and outperform state-of-art baselines by significant magnitudes, without risking rigorous error bounds in terms of the accuracy of the output results. spatialSSJP achieves a relative accuracy gain against plain Spark joins of approximately 10% in worst cases but reaching up to 50% in best case scenarios.

关键词： Algorithms for data and knowledge management Data Architecture spatial databases and gis QoS Data Management spatial Join spatial Indexes Geospatial Analysis Apache Spark Query Processing Big Data Applications

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Using Augmented and Virtual Reality (AR/VR) to Support Safe Navigation on Inland and Coastal Water Zones

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REMOTE SENSING 2022年第6期14卷 1520页

作者： Templin, Tomasz Popielarczyk, Dariusz Gryszko, Marcin Univ Warmia & Mazury Dept Geodesy Inst Geodesy & Civil Engn Fac Geoengn Oczapowskiego 2 PL-10719 Olsztyn Poland INFEO Marcin Marek Gryszko Krolewny Sniezki 18 PL-10696 Olsztyn Poland

The aim of this research is to propose a new solution to assist sailors in safe navigation on inland shallow waters by using Augmented and Virtual Reality. Despite continuous progress in the methodology of displaying bathymetric data and 3D models of the bottoms, there is still a lack of solutions promoting these data and their widespread use. Most existing products present navigation content on 2D/3D maps onscreen. Augmented Reality (AR) technology revolutionises the way digital content is displayed. This paper presents the solution for the use of AR on inland and coastal waterways to increase the safety of sailing and other activities on the water (diving, fishing, etc.). The real-time capability of AR in the proposed mobile application also allows other users to be observed on the water in limited visibility and even at night. The architecture and the prototype Mobile Augmented Reality (MAR) applications are presented. The required AR, including the preparation methodology supported by the Virtual Reality Geographic Information System (VRgis), is also shown. The prototype's performance has been validated in water navigation, specifically for exemplary lakes of Warmia and Mazury in Poland. The performed tests showed the great usefulness of AR in the field of content presentation during the navigation process.

关键词： Digital Elevation Model (DEM) geo-information services Mobile Augmented Reality (MAR) inland and coastal water zones navigation spatial databases and gis Virtual Reality Geographic Information System (VRgis)

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Comparing Implementation Variants Of Distributed spatial Join on Spark

Comparing Implementation Variants Of Distributed Spatial Joi...

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IEEE International Conference on Big Data (Big Data)

作者： Heiler, Georg Hanbury, Allan Complex Sci Hub Vienna Austria TU Wien Inst Informat Syst Engn Vienna Austria

ISBN: (纸本)9781728108582

As an increasing number of sensor devices (Internet of Things) is used, more and more spatio-temporal data becomes available. Being able to process and analyze large quantities of such datasets is therefore critical. spatial joins in classical geo-information systems do not scale well. Nevertheless, distributed implementations are promising to solve this. Various implementation variants for distributed spatial joins are documented in literature, with some being only suitable for specific use cases. We compared broadcast and multiple variants of a distributed spatially partitioned join. We anticipate that this comparison will give guidance to when to use which implementation strategy.

关键词： spatial databases and gis Data Architecture Distributed databases

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Optimal Pick up Point Selection for Effective Ride Sharing

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IEEE TRANSACTIONS ON BIG DATA 2017年第2期3卷 154-168页

作者： Goel, Preeti Kulik, Lars Ramamohanarao, Kotagiri Univ Melbourne Dept Comp & Informat Syst Melbourne Vic 3010 Australia

Car occupancy rates (travelers per vehicle) are currently very low in most developed countries, for example, on average between 1.15 and 1.25 in Australia. Enabling shared rides on short notice can be an effective solution to counter the problem of increasing traffic through the use of the untapped transportation capacity. Common inhibitors for the uptake of ride sharing services are privacy and safety concerns. We present an approach to ride sharing where the pick up/drop off locations for passengers are selected from a fixed set, which has the advantage of increased safety through video surveillance. We present a scheme that chooses optimally fixed locations of Pick up Points (PuPs) and aims to maximize the car occupancy rates while preserving user privacy and safety. Our method enhances privacy as the users do not need to provide their precise home/work locations. We have extended the well studied 1-coverage problem, i. e., to cover an area with the minimum number of circles of a given radius [1], to road networks. The challenges for road networks are the varying population densities of suburbs which requires circles of different radii. The aim is to ensure that every point of a city's area is covered by at least one PuP while minimizing the total number of PuPs. By ensuring that we have different circle radii for PuPs the anonymity of individuals is the same throughout. Using Voronoi diagrams we present a k-anonymity model that guarantees a minimum number of individuals covered by every PuP. Our problem is a multi objective problem where we aim to maximize coverage, k-anonymity and privacy provided by the system to its users while facilitating ride sharing. Through greedy randomized adaptive search procedure (GRASP) we find out the Pareto front of solutions and evaluate their impact on ride sharing.

关键词： Privacy optimization spatial databases and gis dynamic ride sharing

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Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS Tracking

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2016年第8期15卷 2124-2136页

作者： Musa, A. B. M. Biagioni, James Eriksson, Jakob Univ Illinois Dept Comp Sci Chicago IL 60607 USA

In an online GPS tracking system, a fundamental trade-off exists between timeliness, the average time interval between a recorded change in location and a change in the reported location;accuracy, the average error between the actual location and the reported location;and uplink usage, the average amount of data used per second of tracking. While tracking efficiency has been addressed in the literature, our thrifty tracking system presents the first unified view of timeliness, accuracy, and uplink usage, allowing the user to specify desired targets for any two of these objectives, while optimizing the third. We also provide a closed-form characterization of this three-way trade-off, and demonstrate that our system converges to the predicted performance.

关键词： spatial databases and gis mobile communication systems mobile computing client/server data compaction and compression data communications data communications aspects system applications and experience

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Real-Time City-Scale Taxi Ridesharing

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2015年第7期27卷 1782-1795页

作者： Ma, Shuo Zheng, Yu Wolfson, Ouri Univ Illinois Dept Comp Sci Chicago IL 60607 USA Microsoft Res Beijing 100080 Peoples R China

We proposed and developed a taxi-sharing system that accepts taxi passengers' real-time ride requests sent from smartphones and schedules proper taxis to pick up them via ridesharing, subject to time, capacity, and monetary constraints. The monetary constraints provide incentives for both passengers and taxi drivers: passengers will not pay more compared with no ridesharing and get compensated if their travel time is lengthened due to ridesharing;taxi drivers will make money for all the detour distance due to ridesharing. While such a system is of significant social and environmental benefit, e. g., saving energy consumption and satisfying people's commute, real-time taxi-sharing has not been well studied yet. To this end, we devise a mobile-cloud architecture based taxi-sharing system. Taxi riders and taxi drivers use the taxi-sharing service provided by the system via a smart phone App. The Cloud first finds candidate taxis quickly for a taxi ride request using a taxi searching algorithm supported by a spatio-temporal index. A scheduling process is then performed in the cloud to select a taxi that satisfies the request with minimum increase in travel distance. We built an experimental platform using the GPS trajectories generated by over 33,000 taxis over a period of three months. A ride request generator is developed (available at http://***/similar to sma/ridesharing) in terms of the stochastic process modelling real ride requests learned from the data set. Tested on this platform with extensive experiments, our proposed system demonstrated its efficiency, effectiveness and scalability. For example, when the ratio of the number of ride requests to the number of taxis is 6, our proposed system serves three times as many taxi riders as that when no ridesharing is performed while saving 11 percent in total travel distance and 7 percent taxi fare per rider.

关键词： spatial databases and gis taxi-sharing GPS trajectory ridesharing urban computing intelliegent transportation systems

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Managing Evolving Uncertainty in Trajectory databases

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2014年第7期26卷 1692-1705页

作者： Jeung, Hoyoung Lu, Hua Sathe, Saket Yiu, Man Lung SAP Res Brisbane Qld 4105 Australia Aalborg Univ Dept Comp Sci DK-9220 Aalborg Denmark Ecole Polytech Fed Lausanne CH-1015 Lausanne Switzerland Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong Peoples R China

Modern positioning technologies enable collecting trajectories from moving objects across different locations over time, typically containing time-varying measurement errors of positioning systems. Unfortunately, current models on uncertain trajectories are incapable of capturing dynamically changing uncertainty in trajectory data, and lack the support of recent progress made in improving localization accuracy. In order to tackle these problems, we address three important issues centric to uncertain trajectory management. First, we propose a flexible trajectory modeling approach that takes into account model-inferred actual positions, time-varying uncertainty, and nondeterministic uncertainty ranges. Second, we develop three estimators that effectively infer evolving densities of trajectory data. Last, we present an efficient mechanism to evaluate probabilistic range queries on those evolving-density trajectories. Empirical results on two large-scale real datasets demonstrate the quality and efficiency of our approach.

关键词： Query processing spatial databases and gis probabilistic algorithms

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Using Incomplete Information for Complete Weight Annotation of Road Networks

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2014年第5期26卷 1267-1279页

作者： Yang, Bin Kaul, Manohar Jensen, Christian S. Aarhus Univ Dept Comp Sci DK-8200 Aarhus Denmark Aalborg Univ Dept Comp Sci DK-9220 Aalborg Denmark

We are witnessing increasing interests in the effective use of road networks. For example, to enable effective vehicle routing, weighted-graph models of transportation networks are used, where the weight of an edge captures some cost associated with traversing the edge, e. g., greenhouse gas (GHG) emissions or travel time. It is a precondition to using a graph model for routing that all edges have weights. Weights that capture travel times and GHG emissions can be extracted from GPS trajectory data collected from the network. However, GPS trajectory data typically lack the coverage needed to assign weights to all edges. This paper formulates and addresses the problem of annotating all edges in a road network with travel cost based weights from a set of trips in the network that cover only a small fraction of the edges, each with an associated ground-truth travel cost. A general framework is proposed to solve the problem. Specifically, the problem is modeled as a regression problem and solved by minimizing a judiciously designed objective function that takes into account the topology of the road network. In particular, the use of weighted PageRank values of edges is explored for assigning appropriate weights to all edges, and the property of directional adjacency of edges is also taken into account to assign weights. Empirical studies with weights capturing travel time and GHG emissions on two road networks (Skagen, Denmark, and North Jutland, Denmark) offer insight into the design properties of the proposed techniques and offer evidence that the techniques are effective.

关键词： spatial databases and gis correlation and regression analysis

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Interoperable spatial Information Model and Design Environment Based on ucR Technology

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2013年第1期E96D卷 51-63页

作者： Shigesada, Yukihiko Kobayashi, Shinsuke Koshizuka, Noboru Sakamura, Ken Hosei Univ Tokyo 1028160 Japan YRP Ubiquitous Networking Lab Tokyo 1410031 Japan Univ Tokyo Tokyo 1130033 Japan

Context awareness is one of the ultimate goals of ubiquitous computing, and spatial information plays an important role in building context awareness. In this paper, we propose a new interoperable spatial information model, which is based on ucode relation (ucR) and Place Identifier (PI), for realizing ubiquitous spatial infrastructure. In addition, we propose a design environment for spatial information database using our model. Our model is based on ucode and its relation. ucode is 128 bits number and the number itself has no meaning. Hence, it is difficult to manage the relation between ucodes without using a tool. Our design environment provides to describe connection between each ucode visually and is able to manipulate data using the target space map interactively. To evaluate the proposed model and environment, we designed three spaces using our tool. In addition, we developed a web application using our spatial model. From evaluation, we have been showed that our model is effective and our design environment is useful to develop our spatial information model.

关键词： spatial information system ubiquitous computing ubiquitous spatial infrastructure spatial databases and gis web based services

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Geo-Store: A Framework for Supporting Semantics-Enabled Location-Based Services

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IEEE INTERNET COMPUTING 2013年第2期17卷 35-43页

作者： Ku, Wei-Shinn Chen, Haiquan Wang, Chih-Jye Liu, Chuan-Ming Auburn Univ Dept Comp Sci & Software Engn Auburn AL 36849 USA Valdosta State Univ Dept Math & Comp Sci Valdosta GA USA Natl Taipei Univ Technol Dept Comp Sci & Informat Engn Taipei Taiwan

Location-based services (LBSs) are popular information services for mobile users, who access them using location-aware mobile devices over wireless networks. To enable devices to understand and exchange information on the Web, LBS providers use Semantic Web data sources to develop semantics-enabled LBSs. However, there are currently limited solutions for processing spatial queries, the building blocks of most LBSs, on Semantic Web data to support these services. The Geo-Store system evaluates spatial queries on RDF triple stores (Semantic Web data management systems) to provide semantics-enabled LBSs.

关键词： Data models Mobile handsets Query processing Resource description framework spatial databases database applications database management information technology and systems query processing spatial databases and gis

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