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This document describes a simulation of parking spot availability that was created by Chakravarthy Narnindi Sharad. It is intended for everyday commuters, parking offices, and business owners to help find available parking spots. The simulation uses sensors in each spot and wireless access to update a discrete model every 10 seconds to reflect the dynamic parking environment. Randomly assigning values of 0 or 1 every 10 seconds to each spot in a database simulates the occupancy status for demonstration purposes. Future work could include porting it to mobile clients, allowing users to book spots, locate their vehicle, and get driving directions to available spots.
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Introduction
Problems
Analysis
Evaluation
Adaptive approach
Conclusion
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Memory consumptions
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benchmarks.
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This document discusses the speaker's 8 years of experience using open source platforms for commercial web applications. It provides an overview of projects the speaker developed using various open source technologies like PHP, Java, Firebird, PostgreSQL and others. It also outlines technical and business requirements for commercial web applications and lessons learned, including choosing a minimal but complete set of technologies, considering fewer upgrades, and not adopting new technologies too early. The speaker believes open source can work for commercial projects when adopted in a business-like manner.
FME World Tour 2015 - Around the World - Ken Bragg
The document discusses how Pelmorex leverages FME Cloud to generate over 880,000 web map tiles from meteorological data every 12 hours in near real-time, using AWS services like S3, SQS, and Lambda to dynamically provision compute capacity and process the large volume of data more cost effectively than maintaining their own on-premises servers. FME Cloud allows Pelmorex to generate the time-sensitive map tiles much faster and at a lower annual cost than maintaining their own hardware infrastructure.
Ph d defense_Department of Information Technology, Uppsala University, Sweden
Querying Data Providing Web Services
Manivasakan Sabesan
Department of Information Technology
Uppsala University
Sweden.
Abstract
Web services are often used for search computing where data is retrieved from servers providing information of different kinds. Such data providing web services return a set of objects for a given set of parameters without any side effects. There is need to enable general and scalable search capabilities of data from data providing web services, which is the topic of this Thesis.
The Web Service MEDiator (WSMED) system automatically provides relational views of any data providing web service operations by reading the WSDL documents describing them. These views can be queried with SQL. Without any knowledge of the costs of executing specific web service operations the WSMED query processor automatically and adaptively finds an optimized parallel execution plan calling queried data providing web services.
For scalable execution of queries to data providing web services, an algebra operator PAP adaptively parallelizes calls in execution plans to web service operations until no significant performance improvement is measured, based on monitoring the flow from web service operations without any cost knowledge or extensive memory usage.
To comply with the Everything as a Service (XaaS) paradigm WSMED itself is implemented as a web service that provides web service operations to query and combine data from data providing web services. A web based demonstration of the WSMED web service provides general SQL queries to any data providing web service operations from a browser.
WSMED assumes that all queried data sources are available as web services. To make any data providing system into a data providing web service WSMED includes a subsystem, the web service generator, which generates and deploys the web service operations to access a data source. The WSMED web service itself is generated by the web service generator.
Oracle Coherence: in-memory datagrid
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- 1. Simulation of Parking Spot Availability Project byby Chakravarthy Narnindi Sharad Acknowledgements Kate Beard Constance Holden
- 2. Introduction • Parking Spot Availability • Dynamic Environment • Implementation Issues
- 3. Expected User In general, Every day commuter who has the problem of finding a parking space. Parking Office, track illegal parking during non-permit times. Commercially, Any Business owner who cares for customer satisfaction.
- 4. Assumptions Sensors in each parking spot WAP enabled Mobile Clients
- 5. Modeling the Dynamic Environment Discrete Model Refresh Rate – 10 sec Practically Continuous
- 6. Data Source
- 7. Preprocessing of Data Projection of all data into NAD 1983 East Maine State Plane Coordinate System. Overlay Address Matching
- 8. Implementation For simulation of the data actually to be provided by the sensors- Add one more field in the feature database file (.dbf file) associated with its shapefile, which gives the status of the parking space i.e. whether a spot is occupied (1) or not (0). Randomly assign a 0 or 1 periodically (every 10 sec) to a spot and update the database file.
- 9. Work Flow HTML Web Form ASCII File Avenue Script Hit Zoom Update Show Route Summary PanGeo-code Geo-code Query the Ftab Update Display Randomly assign occupancy JavaScript Inputs summary route submit zoom pan
- 10. Demo Lets find the Parking Situation in Down Town Bangor
- 11. Future Work Portability to Mobile Client Booking a Parking Spot Locating the vehicle in the Lot Driving directions to the spot